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@@ -1,17 +1,33 @@
-FROM rocker/shiny-verse:latest
-
-WORKDIR /code
-
-# Install stable packages from CRAN
-RUN install2.r --error \
-    ggExtra \
-    shiny
-
-# Install development packages from GitHub
-RUN installGithub.r \
-    rstudio/bslib \
-    rstudio/httpuv
-
-COPY . .
-
-CMD ["R", "--quiet", "-e", "shiny::runApp(host='0.0.0.0', port=7860)"]
+FROM bioconductor/bioconductor_docker:RELEASE_3_19
+
+# Update apt-get and install necessary libraries
+RUN apt-get update \
+    && apt-get install -y libcurl4-openssl-dev libxml2-dev openjdk-11-jdk \
+    libcairo2-dev libxt-dev \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install R packages
+# Install R packages
+RUN R -e "install.packages(c('shinyjqui','BiocManager','remotes', 'devtools', 'shiny','shinyscreenshot', 'readr', 'shinyAce', 'ggplot2', 'dplyr', 'shinythemes', 'openintro', 'plotly', 'DT', 'ggprism', 'ggbeeswarm', 'shinyFiles', 'stringr', 'shinyBS', 'shinydashboard', 'shinyWidgets', 'tidyr', 'pheatmap', 'grid', 'gridExtra', 'ggeasy', 'ggtext', 'colorspace', 'shinyjqui', 'tidyverse', 'gprofiler2', 'colourpicker', 'shinydashboardPlus', 'jsonlite', 'reshape2'))"
+RUN R -e 'BiocManager::install("graph")'
+RUN R -e "source('https://install-github.me/dreamRs/esquisse')"
+
+# Install plumber and cyjshiny
+RUN R -e "install.packages(c('plumber','cyjShiny','svglite'))"
+
+COPY ./app/ui.R /srv/app/
+COPY ./app/server.R /srv/app/
+COPY ./app/plumber.R /srv/app/
+COPY ./app/R /srv/app/modules/
+COPY ./app/data /srv/app/pathwaymap/
+COPY ./app/svg /srv/app/svg/
+COPY ./app/www /srv/app/www/
+COPY ./scripts/start.sh /usr/local/bin/start.sh
+
+RUN chmod +x /usr/local/bin/start.sh
+
+EXPOSE 9000
+EXPOSE 1028
+
+CMD ["sh", "/usr/local/bin/start.sh"]

LICENCE

@@ -0,0 +1,7 @@
+Copyright (c) 2024, Takaki OKA
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

README.md

@@ -1,12 +1,53 @@
----
-title: Msdial2cytoscape
-emoji: 📚
-colorFrom: blue
-colorTo: yellow
-sdk: docker
-pinned: false
-license: mit
-short_description: test
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# msdial2cytoscape4lipidomics
+
+<!-- badges: start -->
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+
+<!-- badges: end -->
+
+## Overview
+
+This Shiny application is designed to facilitate the analysis of non-targeted lipidomics data. It allows users to easily upload alignment result tables generated by MS-DIAL and, optionally, integrate sample class information for further data exploration. The application provides interactive data visualizations, enabling users to inspect lipid species distributions, compare sample groups, and generate pathway analysis diagrams.
+
+Key features include:
+
+- Simple file upload interface for MS-DIAL alignment results
+- Integration of sample metadata for enhanced analysis
+- Interactive visualizations for exploring lipid species across samples
+- Customizable generation of pathway analysis diagrams with Cytoscape desktop app
+
+
+
+## Run msdial2cytoscape4lipidomics locally
+
+### Step 1: Clone this repository
+
+Open the terminal and run:
+
+``` bash
+git clone "https://github.com/systemsomicslab/msdial2cytoscape-for-lipidomics.git"
+```
+
+### Step 2: Bulid Docker image
+
+``` bash
+docker build -t msdial2cytoscape4lipidomics .
+```
+
+### Step 3: Run Docker image
+
+Run the container on your terminal once it has been bulied.
+
+``` bash
+docker run --rm -p 1028:1028 -p 9000:9000 msdial2cytoscape4lipidomics
+```
+
+### Step 4: Run msdial2cytoscape for lipidomics in your browser
+
+Open your browser and paste `http://localhost:1028`. 
+
+## Code of Conduct
+
+
+

app/R/data_processing.R

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+##' Checking duplicated metabolites from alignment table
+##'
+##' @title Checking duplicated metabolites from alignment table
+##' @param data Lipidomics alignment file form MS-DIAL analysis
+##' @return The alignment table with duplicated metabolites removed.
+##' @examples
+##' data <- read.csv("D:/100cells/20240222/lipid_metabolome.csv",header = F)
+##' result <- Metabolite_duplicate_check(data)
+##' @references 
+##' @author Takaki Oka
+##' @export
+Metabolite_duplicate_check <- function(data){
+  # convert rownames to column for row index
+  
+  ontology_column <- 12
+  batch_id_row <- 2
+  peakinfo_column <- 1:35
+  header_row <- 5
+  peaktable <- data[, !data[batch_id_row, ] %in% NA, drop = FALSE]
+  originalcolnum <- colnames(peaktable)
+  peaktable <- peaktable %>%
+    setNames(peaktable[5,]) %>%
+    rownames_to_column()
+  
+  # Find rows with max 'Fill %' for each 'Metabolite name'
+  check_duplicates <- peaktable %>%
+    group_by(`Metabolite name`) %>%
+	slice_max(`Fill %`,n=1) %>%
+     ungroup()
+  
+  id <- check_duplicates$rowname
+  datav2 <- peaktable %>%
+    filter(rowname %in% c(id, 1:5)) %>%
+    dplyr::select(-rowname)
+  colnames(datav2) <- originalcolnum
+  return(datav2)
+}
+
+##' Converting alignment file
+##'
+##' @title Converting alignment file to dataframe
+##' @param data alignment file form MS-DIAL analysis
+##' @return dataframe of alignment file
+##' @examples
+##' process_alignment_file(data)
+##' @references 
+##' @author Takaki OKA
+##' @export
+process_alignment_file <- function(data) {
+  ontology_column <- 12
+  batch_id_row <- 2
+  peakinfo_column <- 1:35
+  header_row <- 5
+  data <- Metabolite_duplicate_check(data)
+  #data <- Median_normalize_to_alignment_format(data)
+  peaktable <- data[, !data[batch_id_row, ] %in% NA, drop = FALSE]
+  peaktable <- peaktable[, peaktable[batch_id_row, ] == "Sample", drop = FALSE]
+  sample_info <- data.frame(name = unlist(peaktable[5, ]),
+                            Class = unlist(peaktable[1, ]))
+  
+  peaktable <- cbind(data[, peakinfo_column], peaktable)
+  colnames(peaktable) <- peaktable[header_row, ]
+  peaktable <- peaktable[-c(1:header_row), ] 
+  
+  peaktable[, -peakinfo_column] <- data.frame(lapply(peaktable[, -peakinfo_column], as.numeric)) 
+  peaktable <-  distinct(peaktable,`Metabolite name`,.keep_all = TRUE)
+  lipid_info <- peaktable[, colnames(peaktable) %in% c("Metabolite name","Ontology",sample_info$name)]
+  peak_info <- peaktable[, !colnames(peaktable) %in% c("Metabolite name", sample_info$name)]
+  
+  return(list(lipid_info,sample_info,peak_info))
+}
+
+##' Median normalizeing of alignment table wuth retaining alignment format
+##'
+##' @title Median normalizeing of alignment table
+##' @param data Lipidomics alignment file form MS-DIAL analysis
+##' @return Median normalized data with alignment format
+##' @examples
+##' data <- read.csv("D:/100cells/20240222/lipid_metabolome.csv",header = F)
+##' result <- Median_normalize(data)
+##' @references 
+##' @author Nami Sakamoto, Takaki Oka
+##' @export
+Median_normalize_to_alignment_format <- function(data){
+  
+  # Extract lipidontinf
+  peakinfo <- data[5:nrow(data), c(1:35)]
+  lipidontinf <- data[5:nrow(data), c(4, 12)]
+  colnames(lipidontinf) <- lipidontinf[1,]
+  lipidontinf <- lipidontinf[-1,]
+  rownames(lipidontinf) <- NULL
+  
+  # Extract sample information
+  sampleinf <- t(data[1:4, 35:ncol(data)])
+  sampledata <- t(data[5:nrow(data), 36:ncol(data)])
+  Metabolitename <- t(data[-c(1:4), 4])
+  
+  # Combine sample information
+  colnames(sampledata) <- colnames(Metabolitename)
+  datav2_v2 <- cbind(data.frame(sampleinf, rbind(data.frame(Metabolitename), data.frame(sampledata))))
+  colnames(datav2_v2) <- datav2_v2[1,]
+  datav2_v2 <- datav2_v2[-1,]
+  rownames(datav2_v2) <- NULL
+  names(datav2_v2)[5] <- "name"
+  
+  # Filter out 'Batch ID' values and process numeric data
+  lipidmetabolomedata_all <- datav2_v2 %>%
+    filter(!`Batch ID` %in% c('Average', 'Stdev'))
+  numericdata <- lipidmetabolomedata_all[, -c(1:4)]
+  rownames(numericdata) <- NULL
+  numericdatax <- as.data.frame(sapply(numericdata[, -1], as.numeric))
+  rownames(numericdatax) <- lipidmetabolomedata_all$name
+  numericdatax2 <- numericdatax %>%
+    tibble::rownames_to_column() %>%
+    dplyr::rename(sampleid = rowname) %>%
+    pivot_longer(!sampleid, names_to = "lipidname", values_to = "value")
+  
+  log2value <- numericdatax2 %>%
+    mutate(log2value = log2(value)) %>%
+    dplyr::select(-value) %>%
+    pivot_wider(names_from = "lipidname", values_from = "log2value") %>%
+    column_to_rownames(var = "sampleid")
+  
+  samplemedian <- log2value %>% apply(1,median) %>% as.data.frame()
+  colnames(samplemedian) <- "median"
+  
+  mean_forsamplemedian <- mean(samplemedian$median)
+  
+  log2mediannormalizedata <- rownames_to_column(log2value) %>%
+    dplyr::rename(sampleid = rowname) %>%
+    left_join(rownames_to_column(samplemedian), by = c("sampleid" = "rowname")) %>%
+    pivot_longer(!c(sampleid, median), names_to = "lipidname", values_to = "log2value") %>%
+    mutate(mediannormvalue = log2value - median + mean_forsamplemedian) %>%
+    dplyr::select(-c(log2value, median)) %>%
+    pivot_wider(names_from = "lipidname", values_from = "mediannormvalue") %>%
+    column_to_rownames(var = "sampleid")
+  
+  log2_2xmediannormalizedata <- 2^log2mediannormalizedata
+  log2_2xmediannormalizedata_0 <- lipidmetabolomedata_all[, c(1:5)] %>%
+    left_join(rownames_to_column(log2_2xmediannormalizedata), by = c("name" = "rowname")) %>% t() %>% data.frame()%>% rownames_to_column("V0")
+  aligntable <- right_join(peakinfo,log2_2xmediannormalizedata_0,by = c("V4" = "V0"))
+  headerrow <- tail(aligntable,n = 5)
+  aligntable <- rbind(headerrow,aligntable)
+  aligntable[1:5,1:35] <- data[1:5,1:35]
+  aligntable <- filter(aligntable,is.na(V1)==F)
+  return(aligntable)
+}
+##' Converting alignment file to expression data of lipid class
+##'
+##' @title Converting alignment file to dataframe
+##' @param data alignment file form MS-DIAL analysis
+##' @return Expression data of lipid class and sample meta data 
+##' @examples
+##' convert_msdial_export_to_lipid_class_dataframe(data)
+##' @references 
+##' @author Takaki OKA
+##' @export
+convert_msdial_export_to_lipid_class_dataframe <- function(data) {
+  data_frame <- process_alignment_file(data)
+  lipid_info <- data_frame[[1]]
+  sample_info <- data_frame[[2]]
+  
+  lipidtable <- lipid_info[,colnames(lipid_info) %in% c("Metabolite name","Ontology", sample_info$name)] %>% pivot_longer(cols = -(1:2)) 
+  lipidtable <- lipidtable %>%
+    group_by(name, Ontology) %>%
+    mutate(mean = mean(value)) %>%
+    ungroup() %>%
+    distinct(name, Ontology, .keep_all = TRUE) %>%
+    dplyr::select(-c("Metabolite name", value)) %>%
+    pivot_wider(values_from = mean, names_from = Ontology)
+  return(list(lipidtable,sample_info))
+}
+
+##' Converting alignment file to expression data of lipid molecules
+##'
+##' @title Converting alignment file to dataframe
+##' @param data alignment file form MS-DIAL analysis
+##' @return Expression data of lipid molecules and sample meta data 
+##' @examples
+##' convert_msdial_export_to_lipid_molecules_dataframe(data)
+##' @references 
+##' @author Takaki OKA
+##' @export
+convert_msdial_export_to_lipid_molecules_dataframe <- function(data) {
+  data_frame <- process_alignment_file(data)
+  lipid_info <- data_frame[[1]]
+  sample_info <- data_frame[[2]]
+  
+  lipidtable <- lipid_info[,colnames(lipid_info) %in% c("Metabolite name", sample_info$name)] %>% pivot_longer(cols = -(1))  %>%  pivot_wider(names_from = `Metabolite name`,values_from = value) 
+  return(list(lipidtable,sample_info))
+}
+
+##' Updating select input with file upload
+##'
+##' @title Updating select input with file upload
+##' @param data alignment file form MS-DIAL analysis
+##' @return Expression data of lipid molecules and sample meta data 
+##' @examples
+##' convert_msdial_export_to_lipid_molecules_dataframe(data)
+##' @references 
+##' @author Takaki OKA
+##' @export
+processAndUpdateInputs <- function(data, session, metadata, metainfocol) {
+  shiny::updateSelectInput(session, "y", selected = paste(colnames(data)[c(metainfocol + 1)]), choices = colnames(data)[-c(1:metainfocol)])
+  shiny::updateSelectInput(session, "w", selected = "Class", choices = colnames(data)[c(2:metainfocol)])
+  shiny::updateSelectInput(session, "z", selected = "Class", choices = colnames(data)[c(2:metainfocol)])
+}
+
+processAndUpdateInputs2 <- function(data, session, metadata, metainfocol) {
+  #shiny::updateSelectInput(session, "y", selected = paste(colnames(data)[c(metainfocol + 1)]), choices = colnames(data)[-c(1:metainfocol)])
+  shiny::updateSelectInput(session, "X1", selected = paste(colnames(data)[c(metainfocol + 1)]), choices = colnames(data)[-c(1:metainfocol)])
+  shiny::updateSelectInput(session, "X2", selected = paste(colnames(data)[c(metainfocol + 1)]), choices = colnames(data)[-c(1:metainfocol)])
+  #shiny::updateSelectInput(session, "z", selected = "Class", choices = colnames(data)[c(2:metainfocol)])
+}
+# update_select_input <- function(input,session) {
+# 
+#     
+#   
+# }
+
+scale_rows <- function(x) {
+  t(apply(x, 1, function(row) scales::rescale(row, to = c(-2, 2))))
+}
+
+lipidmeancalforgroupnode <- function(data, metadata, selectclass) {
+  Ontology_column <- 12
+  BatchID_row <- 2
+  peakinfo_column <- 1:35
+  header_row <- 5
+  processed_data <- process_alignment_file(data)
+  lipid_data_classmean <- processed_data[[1]]
+  sampleinfo <- processed_data[[2]]
+  lipid_data_lipidclassmean <- pivot_longer(lipid_data_classmean, cols = -c(1:2)) %>%
+    dplyr::select(`Metabolite name`, Ontology, name, value) %>%
+    inner_join(metadata, by = "name") %>%
+    dplyr::select(`Metabolite name`,Ontology ,selectclass, name, value) %>%
+    group_by(`Metabolite name`, across(all_of(selectclass))) %>%
+    mutate(mean = mean(value)) %>%
+    ungroup() %>%
+    distinct(`Metabolite name`,across(all_of(selectclass)), .keep_all = TRUE) %>%
+    dplyr::select(`Metabolite name`, Ontology, selectclass, mean) %>%
+    pivot_wider(names_from = selectclass, values_from = mean)
+  return(lipid_data_lipidclassmean)
+}
+
+processSampleInRows <- function(originaldata, session, input) {
+  colnames(originaldata) <- originaldata[1,]
+  originaldata <- originaldata[-1,]
+  originaldata[, -c(1:2)] <- apply(originaldata[, -c(1:2)], 2, as.numeric)
+  lipidont <- read.csv(input$ontfile$datapath, check.names = FALSE)
+  colnames(lipidont)[1] <- "lipid"
+  colnames(originaldata)[1] <- "name"
+  if (length(input$file2) != 0) {
+    metadata <- read.csv(input$file2$datapath)
+    colnames(metadata)[1] <- "name"
+    data <- originaldata %>%
+      pivot_longer(cols = -c(1:2), names_to = "lipid") %>%
+      inner_join(lipidont, by = c("lipid")) %>%
+      group_by(name, Ontology) %>%
+      mutate(mean = mean(value)) %>%
+      ungroup() %>%
+      distinct(name, Ontology, .keep_all = TRUE) %>%
+      dplyr::select(1, 2, 5, 6) %>%
+      pivot_wider(names_from = "Ontology", values_from = "mean")
+    data <- inner_join(metadata, data, by = c("name" = "name"))
+  } else {
+    metadata <- data.frame(name = originaldata[,1],Class = originaldata[,2])
+    data <- originaldata %>%
+      pivot_longer(cols = -c(1:2), names_to = "lipid") %>%
+      inner_join(lipidont, by = c("lipid")) %>%
+      group_by(name, Ontology) %>%
+      mutate(mean = mean(value)) %>%
+      ungroup() %>%
+      distinct(name, Ontology, .keep_all = TRUE) %>%
+      dplyr::select(1, 5, 6) %>%
+      pivot_wider(names_from = "Ontology", values_from = "mean")
+    data <- inner_join(metadata, data, by = c("name" = "name"))
+  }
+  return(list(data,metadata))
+}
+
+processMSDIALExport <- function(originaldata, session, input) {
+  if (length(input$file2) != 0) {
+  tablelist <- originaldata %>% convert_msdial_export_to_lipid_class_dataframe()
+  data <- tablelist[[1]]
+  metadata <- read.csv(input$file2$datapath)
+  colnames(metadata)[1] <- "name"
+  metadata <- inner_join(tablelist[[2]], metadata, by = c("name"))
+  data <- inner_join(metadata, data, by = c("name" = "name"))
+  metainfocol <- ncol(metadata)
+  } else {
+  tablelist <- originaldata %>% convert_msdial_export_to_lipid_class_dataframe()
+  data <- tablelist[[1]]
+  metadata <- tablelist[[2]]
+  metainfocol <- ncol(metadata)
+  data <- inner_join(metadata, data, by = c("name" = "name"))
+  }
+  return(list(data,metadata))
+}
+
+processMSDIALExporttomoldata <- function(originaldata, session, input) {
+  if (length(input$file2) != 0) {
+  tablelist <- originaldata %>% convert_msdial_export_to_lipid_molecules_dataframe()
+  data <- tablelist[[1]]
+  metadata <- read.csv(input$file2$datapath)
+  colnames(metadata)[1] <- "name"
+  metadata <- inner_join(tablelist[[2]], metadata, by = c("name"))
+  data <- inner_join(metadata, data, by = c("name" = "name"))
+  metainfocol <- ncol(metadata)
+  } else {
+  tablelist <- originaldata %>% convert_msdial_export_to_lipid_molecules_dataframe()
+  data <- tablelist[[1]]
+  metadata <- tablelist[[2]]
+  metainfocol <- ncol(metadata)
+  data <- inner_join(metadata, data, by = c("name" = "name"))
+  }
+  return(list(data,metadata))
+}
+
+processSampleInRowstomoldata <- function(originaldata, session, input) {
+  moldata <- originaldata 
+  colnames(moldata) <- moldata[1,]
+  moldata <- moldata[, !duplicated(colnames(moldata))]
+  moldata <- moldata[-1,]
+  moldata[,-c(1,2)] <- apply(moldata[,-c(1,2)],2,as.numeric) %>% data.frame()
+  colnames(moldata)[1] <- "name"
+  if (length(input$file2) != 0) {
+    metadata <- read.csv(input$file2$datapath)
+    colnames(metadata)[1] <- "name"
+    data <- inner_join(metadata, moldata, by = c("name" = "name"))
+  } else {
+    metadata <- data.frame(name = originaldata[,1],Class = originaldata[,2])
+    data <- moldata
+  }
+  return(list(data,metadata))
+}
+
+read_graph_json <- function(file_path) {
+  tryCatch({
+    paste(readLines(file_path), collapse = "")
+  }, error = function(e) {
+    message("Error reading graph JSON file: ", e$message)
+    return(NULL)
+  })
+}
+
+
+pvaluecheckbox =reactiveVal()
+pvaluecheckbox <<- ""

app/R/heatmap_utils.R

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+groupnodeheatmap <- function(lipidclassproperties,data,metadata,class,levels,inputclass,input){
+  # lipidclassproperties
+  if(input$filetype == "MS-DIAL export"){
+  lipid_data_classmean <<- right_join(lipidclassproperties,lipidmeancalforgroupnode(data,metadata,input$w) ,by = c("LbmClass"="Ontology"))
+  }
+  
+  if(input$filetype == "Sample in rows"){
+    colnames(data) <- data[1,]
+    data <- data[-1,]
+    data[, -c(1:2)] <- apply(data[, -c(1:2)], 2, as.numeric)
+	colnames(data)[1] <- "name"
+	colnames(metadata)[1] <- "name"
+    lipid <- data %>% pivot_longer(cols = -c(1:2),names_to = "Metabolite name") %>%  
+      inner_join(metadata,by = c("name","Class")) %>% 
+      select(c(paste(input$w,"",sep=""),`Metabolite name`,name,value)) %>%
+      group_by_at(c("Metabolite name",input$w)) %>%
+      mutate(mean = mean(value)) %>%
+      ungroup() %>%
+      distinct(`Metabolite name`,!!as.symbol(input$w),.keep_all = T) %>%
+      select(c(1,2,5)) %>%
+      pivot_wider(names_from = paste(input$w,"",sep=""),values_from = mean)
+    lipidont <- read.csv(input$ontfile$datapath,check.names = F)
+    lipid <- inner_join(lipidont,lipid,by =c("lipid" = "Metabolite name"))
+    lipid <- rename(lipid,`Metabolite name`  = lipid)
+    lipid_data_classmean <- right_join(lipidclassproperties,lipid,by = c("LbmClass"="Ontology")) %>% filter(TotalChain != 0)# %>% filter(`Annotation tag (VS1.0)` == "410")
+  }
+  
+  #lipid_data_classmean <- right_join(lipidclassproperties,lipidmeancalforgroupnode(data,metadata,paste(class,"",sep="")) ,by = c("LbmClass"="Ontology")) # %>% filter(`Annotation tag (VS1.0)` == "410")
+  lipid_data_classmean <- filter(lipid_data_classmean,LbmClass == inputclass)
+  if(unique(lipid_data_classmean$TotalChain) == "1"){
+    targetmonoacylchain <- c("16:0","16:1","18:0","18:1","18:2","18:3","20:3","20:4","20:5","22:4","22:5","22:6")
+    monoacyl <- lipid_data_classmean %>% filter(TotalChain == "1") %>% filter(!LbmClass %in% c("AHexCS","AHexSTS"))
+    targetlipidclass <- monoacyl$LbmClass %>% unique()
+    monoacyl <- monoacyl[,-c(2:7)]
+    if(input$acylfilter == T){
+      
+      acyllist <- list()
+      for (i in 1:nrow(monoacyl)) {
+        a <- unlist(str_split(monoacyl$`Metabolite name`[i],pattern = " "))[2]
+        
+        if (str_detect(a,pattern = ";") == TRUE){
+          acyl <- a %>% str_split(pattern = ";") %>% unlist()
+          if(str_detect(acyl[1],pattern = "-")){
+            acyl <- acyl[1] %>% str_split(pattern = "-") %>% unlist()
+            acyllist[i] <- a[2]
+          }else{
+            acyllist[i] <- acyl[1]
+          }
+          
+        }else if(str_detect(a,pattern = "/")==TRUE){
+          acyl <- a %>% str_split(pattern = "/") %>% unlist()
+          acyllist[i] <- acyl[2]
+        }else{
+          if(str_detect(a,pattern = "-")){
+            acyl <- a %>% str_split(pattern = "-") %>% unlist()
+            acyllist[i] <- acyl[2]
+          }else{
+            acyllist[i] <- a
+          }
+        }
+      }
+      
+      
+      
+      monoacyl$acyl <- unlist(acyllist)
+      #
+      targetmonoacyllipid <- monoacyl %>% filter(acyl %in% targetmonoacylchain) %>% select(-c(acyl))
+    }
+    else{
+      targetmonoacyllipid <- monoacyl
+    }
+    targetlipidclass <- unique(targetmonoacyllipid$LbmClass)
+    monoacyl <- targetmonoacyllipid
+    
+    Lipidclassdata<- filter(monoacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(LbmClass))
+      n <- nrow(d)
+      BreaksList <- seq(-2,2, by = 0.5)
+      height <- n*0.9
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 0),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+    }}
+  if(unique(lipid_data_classmean$TotalChain) == "2"&& unique(lipid_data_classmean$Categories) != "Sphingolipids" && unique(lipid_data_classmean$Categories) != "Sterol Lipids"){
+    targetdiacylchain <- c("16:0","16:1","18:0","18:1","18:2","18:3","20:3","20:4","20:5","22:4","22:5","22:6")
+    diacyl <- lipid_data_classmean %>% filter(TotalChain == "2", Categories != "Sphingolipids")
+    targetlipidclass <- diacyl$LbmClass %>% unique()
+    diacyl <- diacyl[,-c(3:7)]
+    if(input$acylfilter == T){
+      acyl1list <- list()
+      acyl2list <- list()
+      for (i in 1:nrow(diacyl) ) {
+        if(str_detect(diacyl$`Metabolite name`[i],pattern = "\\|") == TRUE){
+          a <-  unlist(str_split(diacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ") %>% unlist()
+          if(str_detect(a[2],pattern = "_") == TRUE){
+            a <- a[2] %>% str_split(pattern = "_") %>% unlist()
+            if(str_detect(a[1],pattern = "-") == TRUE){
+              acyl1 <- a[1] %>% str_split(pattern = "-") %>% unlist()
+              acyl1list[i] <- acyl1[2]
+            }else{
+              acyl1list[i] <- a[1]
+            }
+            if(str_detect(a[2],pattern = ";") == TRUE){
+              acyl2 <- a[2] %>% str_split(pattern = ";") %>% unlist()
+              acyl2list[i] <- acyl2[1]
+            }else{
+              acyl2list[i] <- a[2]
+            }
+          }else{
+            a <- unlist(a)[2] %>% str_split(pattern = "\\)") %>% unlist()
+            acyl1 <- a[1] %>%  str_split(pattern = " ") %>% unlist()
+            acyl1list[i] <- acyl1[2]
+            acyl2list[i] <- a[2]
+          }
+        }
+        else{
+          acyl1list[i] <- NA
+          acyl2list[i] <- NA
+        }
+      }
+      
+      diacyl$acyl1 <- unlist(acyl1list)
+      diacyl$acyl2 <- unlist(acyl2list)
+      
+      targetdiacyllipid <- diacyl %>% filter(acyl1 %in% targetdiacylchain, acyl2 %in% targetdiacylchain)
+      
+      # if(input$sn == T){
+      #   targetdiacyllipid$acyl1 <- paste(targetdiacyllipid$LbmClass," ",targetdiacyllipid$acyl1," (sn-1)",sep ="")
+      #   targetdiacyllipid$acyl2 <- paste(targetdiacyllipid$LbmClass," ",targetdiacyllipid$acyl2," (sn-2)",sep ="")
+      #   targetdiacyllipid <- targetdiacyllipid %>% select( `Metabolite name`,LbmClass,acyl1,acyl2,everything()) %>% pivot_longer(cols = -c(1:4)) %>% group_by(name,acyl1) %>% mutate(mean1 = mean(value)) %>% ungroup() %>% group_by(name,acyl2) %>% mutate(mean2 = mean(value)) %>% ungroup()
+      #   sn1 <- select(targetdiacyllipid,c(LbmClass,name,acyl1,mean1)) %>% distinct(name,acyl1,.keep_all = T)
+      #   colnames(sn1) <- c("LbmClass","name","Metabolite name","value")
+      #   sn2 <- select(targetdiacyllipid,c(LbmClass,name,acyl2,mean2))%>% distinct(name,acyl2,.keep_all = T)
+      #   colnames(sn2) <- c("LbmClass","name","Metabolite name","value")
+      #   diacyl <- rbind(sn1,sn2) %>% pivot_wider(names_from = "name",values_from = "value") #%>% data.frame()
+      # }
+      
+      
+      diacyl <- targetdiacyllipid %>% select(-c(acyl1,acyl2))
+      
+    }
+    else{}
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      BreaksList <- seq(-2,2, by = 0.5)
+      # print(d)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+    }}
+  
+  if(unique(lipid_data_classmean$TotalChain) == "2"&& unique(lipid_data_classmean$Categories) == "Sterol Lipids" && unique(lipid_data_classmean$LbmClass) != "WE"){
+    targetdiacylchain <- c("16:0","16:1","18:0","18:1","18:2","18:3","20:3","20:4","20:5","22:4","22:5","22:6")
+    diacyl <- lipid_data_classmean %>% filter(TotalChain == "2", LbmClass != "WE")# %>%
+    targetlipidclass <- diacyl$LbmClass %>% unique()
+    diacyl <- diacyl[,-c(3:7)]
+    if(input$acylfilter == T){
+      acyl1list <- list()
+      acyl2list <- list()
+      for (i in 1:nrow(diacyl) ) {
+        
+        if(str_detect(diacyl$`Metabolite name`[i],pattern = "\\|") == TRUE){
+          a <-  unlist(str_split(diacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ") %>% unlist()
+          if(str_detect(a[2],pattern = "/") == TRUE){
+            a <- a[2] %>% str_split(pattern = "/") %>% unlist()
+            acyl1list[i] <- a[1]
+            acyl2list[i] <- a[2]
+          }
+        }
+        else{
+          acyl1list[i] <- NA
+          acyl2list[i] <- NA
+        }
+      }
+      diacyl$acyl1 <- unlist(acyl1list)
+      diacyl$acyl2 <- unlist(acyl2list)
+      
+      targetdiacyllipid <- diacyl %>% filter(acyl1 %in% targetdiacylchain, acyl2 %in% targetdiacylchain)
+      
+      # if(input$sn == T){
+      #   targetdiacyllipid$acyl1 <- paste(targetdiacyllipid$LbmClass," ",targetdiacyllipid$acyl1," (sn-1)",sep ="")
+      #   targetdiacyllipid$acyl2 <- paste(targetdiacyllipid$LbmClass," ",targetdiacyllipid$acyl2," (sn-2)",sep ="")
+      #   targetdiacyllipid <- targetdiacyllipid %>% select( `Metabolite name`,LbmClass,acyl1,acyl2,everything()) %>% pivot_longer(cols = -c(1:4)) %>% group_by(name,acyl1) %>% mutate(mean1 = mean(value)) %>% ungroup() %>% group_by(name,acyl2) %>% mutate(mean2 = mean(value)) %>% ungroup()
+      #   sn1 <- select(targetdiacyllipid,c(LbmClass,name,acyl1,mean1)) %>% distinct(name,acyl1,.keep_all = T)
+      #   colnames(sn1) <- c("LbmClass","name","Metabolite name","value")
+      #   sn2 <- select(targetdiacyllipid,c(LbmClass,name,acyl2,mean2))%>% distinct(name,acyl2,.keep_all = T)
+      #   colnames(sn2) <- c("LbmClass","name","Metabolite name","value")
+      #   diacyl <- rbind(sn1,sn2) %>% pivot_wider(names_from = "name",values_from = "value") #%>% data.frame()
+      # }
+      
+      
+      diacyl <- targetdiacyllipid %>% select(-c(acyl1,acyl2))
+      
+    }
+    else{}
+    
+    
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+    }}
+  
+  if(unique(lipid_data_classmean$TotalChain) == "2"&&unique(lipid_data_classmean$Categories) == "Sphingolipids"&&unique(lipid_data_classmean$LbmClass) != "ASM"){
+    targetSphingoidBase <- c("18:0;O2","18:1;O2","18:2;O2","18:0;O3","18:0;2O","18:1;2O","18:2;2O","18:0;3O")
+    targetnacylchain <- c("16:0","16:1","18:0", "20:0", "22:0", "24:0", "24:1", "26:0", "26:1")
+    epidermalacylceramide <- c("Cer_EODS","Cer_EOS","Cer_EBDS","HexCer_EOS")
+    epidermalacylceramidetargetacylchain <- c("18:2")
+    diacyl <- lipid_data_classmean %>% filter(TotalChain == "2",Categories == "Sphingolipids",LbmClass != "ASM")
+    targetlipidclass <- diacyl$LbmClass %>% unique()
+    diacyl <- diacyl[,-c(3:7)]
+    
+    if(input$acylfilter == T){
+      acyl1list <- list()
+      acyl2list <- list()
+      for (i in 1:nrow(diacyl)) {
+        if(str_detect(diacyl$`Metabolite name`[i],pattern = "\\|") == TRUE){
+          a <-  unlist(str_split(diacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ")
+          if(str_detect(unlist(a)[2],pattern = "/") == TRUE){
+            a <- unlist(a)[2] %>% str_split(pattern = "/") %>% unlist()
+            acyl1list[i] <- a[1]
+            if(str_detect(a[2],pattern = ";") == TRUE){
+              
+              acyl2 <- a[2] %>% str_split(pattern = ";") %>% unlist()
+              acyl2list[i] <- acyl2[1]
+            }
+            else if(str_detect(a[2],pattern = "\\(") == TRUE){
+              acyl2 <- a[2] %>% str_split(pattern = "\\(") %>% unlist()
+              acyl2list[i] <- acyl2[1]
+            }
+            else{
+              acyl2list[i] <- a[2]
+            }
+          }
+          else{
+            acyl1list[i] <- NA
+            acyl2list[i] <- NA
+          }
+        }
+        else{
+          acyl1list[i] <- NA
+          acyl2list[i] <- NA
+        }
+      }
+      diacyl$acyl1 <- unlist(acyl1list)
+      diacyl$acyl2 <- unlist(acyl2list)
+      targetdiacyllipidnotEOS <- diacyl %>% filter(!Categories %in% epidermalacylceramide) %>% filter(acyl1 %in% targetSphingoidBase, acyl2 %in% targetnacylchain)
+      targetdiacyllipidEOS  <- diacyl %>% filter(Categories %in% epidermalacylceramide) %>% filter(acyl1 %in% targetSphingoidBase, acyl2 %in% epidermalacylceramidetargetacylchain)
+      targetdiacyllipid <- rbind(targetdiacyllipidEOS,targetdiacyllipidnotEOS)
+      targetlipidclass <- unique(targetdiacyllipid$LbmClass)
+      
+      # if(input$sn == T){
+      #   targetdiacyllipid$acyl1 <- paste(targetdiacyllipid$LbmClass," C",targetdiacyllipid$acyl1,sep ="")
+      #   targetdiacyllipid$acyl2 <- paste(targetdiacyllipid$LbmClass," C",targetdiacyllipid$acyl2,sep ="")
+      #   targetdiacyllipid <- targetdiacyllipid %>% select( `Metabolite name`,LbmClass,acyl1,acyl2,everything()) %>% pivot_longer(cols = -c(1:4)) %>% group_by(name,acyl1) %>% mutate(mean1 = mean(value)) %>% ungroup() %>% group_by(name,acyl2) %>% mutate(mean2 = mean(value)) %>% ungroup()
+      #   sn1 <- select(targetdiacyllipid,c(LbmClass,name,acyl1,mean1)) %>% distinct(name,acyl1,.keep_all = T)
+      #   colnames(sn1) <- c("LbmClass","name","Metabolite name","value")
+      #   sn2 <- select(targetdiacyllipid,c(LbmClass,name,acyl2,mean2))%>% distinct(name,acyl2,.keep_all = T)
+      #   colnames(sn2) <- c("LbmClass","name","Metabolite name","value")
+      #   diacyl <- sn2 %>% pivot_wider(names_from = "name",values_from = "value")
+      # }
+      
+      
+      diacyl <- targetdiacyllipid %>% select(-c(acyl1,acyl2))
+      
+      
+    }
+    else{
+    }
+    
+    
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      n <- nrow(d)
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+      
+    }}
+  
+  if(unique(lipid_data_classmean$LbmClass) == "ASM"){
+    targetnacylchain <- c("16:0","16:1","18:0", "20:0", "22:0", "24:0", "24:1", "26:0", "26:1")
+    diacyl <- lipid_data_classmean %>% filter(LbmClass == "ASM")# %>%
+    targetlipidclass <- diacyl$LbmClass %>% unique()
+    diacyl <- diacyl[,-c(3:7)]
+    
+    if(input$acylfilter == T){
+      
+      acyl1list <- list()
+      for (i in 1:nrow(diacyl)) {
+        if(str_detect(diacyl$`Metabolite name`[i],pattern = "\\(") == TRUE){
+          a <- str_split(diacyl$`Metabolite name`[i],pattern = "\\(") %>% unlist()
+          a1 <- a[2] %>%  str_split(pattern = "\\)") %>% unlist()
+          a2 <- a1[1] %>% str_split(pattern = " ") %>% unlist()
+          acyl1list[i] <- a2[2]
+        }
+        else{
+          acyl1list[i] <- NA
+        }
+      }
+      
+      diacyl$acyl1 <- unlist(acyl1list)
+      targetdiacyllipid <- diacyl %>%  filter(acyl1 %in% targetnacylchain) %>% select(-c(Categories))
+      
+      targetlipidclass <- unique(targetdiacyllipid$LbmClass)
+      
+      
+      
+      diacyl <- targetdiacyllipid %>% select(-c(acyl1))
+      
+      
+      
+    }
+    else{
+      
+    }
+    
+    
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      n <- nrow(d)
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+      
+    }
+  }
+  if(unique(lipid_data_classmean$TotalChain) == "0"){
+    targetnacylchain <- c("16:0","16:1","18:0", "20:0", "22:0", "24:0", "24:1", "26:0", "26:1")
+    diacyl <- lipid_data_classmean %>% filter(TotalChain == "0")# %>%
+    targetlipidclass <- diacyl$LbmClass %>% unique()
+    diacyl <- diacyl[,-c(3:7)]
+    if(input$acylfilter == T){
+      
+      acyl1list <- list()
+      acyl2list <- list()
+      
+      for (i in 1:nrow(diacyl)) {
+        acyl1list[i] <- NA
+      }
+      
+      diacyl$acyl1 <- unlist(acyl1list)
+      targetdiacyllipid <- diacyl %>%  filter(acyl1 %in% targetnacylchain) %>% select(-c(Categories))
+      targetlipidclass <- unique(targetdiacyllipid$LbmClass)
+      
+      namelist <- list()
+      pathlist <- list()
+      
+      diacyl <- targetdiacyllipid %>% select(-c(acyl1))
+      
+      
+      
+    }
+    else{
+      
+    }
+    
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      n <- nrow(d)
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+      
+    }}
+  if(unique(lipid_data_classmean$TotalChain) > 2 && unique(lipid_data_classmean$LbmClass) %in% c("TG","OxTG","HBMP","EtherTG")){
+    targettriacylchain <- c("16:0","16:1","18:0","18:1","18:2","18:3","20:3","20:4","20:5","22:4","22:5","22:6")
+    Triacyl <- lipid_data_classmean %>% filter(TotalChain > 2, LbmClass %in% c("TG","OxTG","HBMP","EtherTG"))
+    targetlipidclass <- Triacyl$LbmClass %>% unique()
+    Triacyl <- Triacyl[,-c(3:7)]
+    if(input$acylfilter == T){
+      acyllist1 <- list()
+      acyllist2 <- list()
+      acyllist3 <- list()
+      for (i in 1:nrow(Triacyl)) {
+        if(Triacyl$LbmClass[i] == "TG"){
+          
+          a <-  unlist(str_split(Triacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ")
+          a <- unlist(a)[2] %>% str_split(pattern = "_") %>% unlist()
+          acyllist1[i] <- a[1]
+          acyllist2[i] <- a[2]
+          acyllist3[i] <- a[3]
+        }else if(Triacyl$LbmClass[i] =="OxTG"){
+          
+          a <-  unlist(str_split(Triacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ")
+          a <- unlist(a)[2] %>% str_split(pattern = "_") %>% unlist()
+          acyllist1[i] <- a[1]
+          acyllist2[i] <- a[2]
+          b <- a[3] %>% str_split(pattern = ";") %>% unlist()
+          acyllist3[i] <- b[1]
+        }else if(Triacyl$LbmClass[i] =="HBMP"){
+          a <-  unlist(str_split(Triacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ")
+          a <- unlist(a)[2] %>% str_split(pattern = "_") %>% unlist()
+          b <- a[1] %>% str_split(pattern = "/") %>% unlist()
+          acyllist1[i] <-  b[1]
+          acyllist2[i] <-  b[2]
+          acyllist3[i] <-  a[2]
+        }else if(Triacyl$LbmClass[i] =="EtherTG"){
+          a <-  unlist(str_split(Triacyl$`Metabolite name`[i],pattern = "\\|"))[2] %>% str_split(pattern = " ")
+          a <- unlist(a)[2] %>% str_split(pattern = "_") %>% unlist()
+          acyl <- a[1] %>% str_split(pattern = "-") %>% unlist()
+          acyllist1[i] <- acyl[2]
+          acyllist2[i] <- a[2]
+          acyllist3[i]<- a[3]
+        }
+      }
+      
+      Triacyl$acyl1 <- unlist(acyllist1)
+      Triacyl$acyl2 <- unlist(acyllist2)
+      Triacyl$acyl3 <- unlist(acyllist3)
+      
+      targettriacyllipid <- Triacyl %>% filter(acyl1 %in% targettriacylchain, acyl2 %in% targettriacylchain,acyl3 %in% targettriacylchain) %>% select(-c(acyl1,acyl2,acyl3,Categories))
+    }
+    else{
+      targettriacyllipid <- Triacyl
+    }
+    Triacyl <- targettriacyllipid
+    # i <-
+    Lipidclassdata<- filter(Triacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- select(d,-c(`Metabolite name`,LbmClass))
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+      
+    }}
+  if(unique(lipid_data_classmean$TotalChain) > 2 && ! unique(lipid_data_classmean$LbmClass) %in% c("TG","OxTG","HBMP","EtherTG")){
+    Triacyl <- lipid_data_classmean %>% filter(TotalChain > 2, ! LbmClass %in% c("TG","OxTG","HBMP","EtherTG"))
+    targetlipidclass <- Triacyl$LbmClass %>% unique()
+    Triacyl <- Triacyl[,-c(3:7)]
+    diacyl <- Triacyl
+    Lipidclassdata<- filter(diacyl , LbmClass == inputclass) %>% distinct(`Metabolite name`,.keep_all = TRUE)
+    if(length(Lipidclassdata$LbmClass) != 0){
+      d <- Lipidclassdata
+      rowname <- as.matrix((d$`Metabolite name`))
+      d <- d <- select(d,-c(`Metabolite name`,LbmClass))
+      n <- nrow(d)
+      BreaksList <- seq(-2,2, by = 0.5)
+      n <- nrow(d)
+      height <- n/10*3
+      list <- c(-2,0,2)
+      lipid <- d
+      lipid <- lipid[,-1]
+      rownames(lipid) <- rowname
+      lipid <- scale_rows(lipid) %>% as.data.frame()
+      lipid <- tibble::rownames_to_column(lipid, "Metabolite name")
+      lipid <- pivot_longer(lipid,cols = -c(`Metabolite name`))
+      lipid <- mutate(lipid, name = name %>% factor(levels = input$levels))
+      ghm <- ggplot(lipid, aes(x = name, y =`Metabolite name` , fill = value))
+      ghm <- ghm + geom_tile(color = "black") + scale_fill_gradientn(
+        colors=c("navy","white","red"),limits=c(min(lipid$value), max(lipid$value))
+      ) + theme(axis.text.x = element_text(angle = 90, hjust = 1),axis.text = element_text(size = input$Fontsize))
+      print(ghm)
+      
+    }}
+  
+}

app/R/librarys.R

@@ -0,0 +1,40 @@
+library(shiny)
+library(readr)
+library(shinyAce)
+library(ggplot2)
+library(dplyr)
+library(shinythemes)
+library(openintro)
+library(plotly)
+library(DT)
+library(ggprism)
+library(ggbeeswarm)
+library(reshape2)
+library(shinyFiles)
+library(stringr)
+library(shinyBS)
+library(shinyjs)
+library(shinydashboard)
+library(shinyWidgets)
+library(svglite)
+library(tidyr)
+library(pheatmap)
+library(grid)
+library(gridExtra)
+#library(RCy3)
+# library(rcdk)
+library(ggeasy)
+library(ggtext)
+library(colorspace)
+library(shinyjqui)
+library(tidyverse)
+library(gprofiler2)
+library(colourpicker)
+library(shinydashboardPlus)
+library(shiny)
+library(cyjShiny)
+library(graph)
+library(jsonlite)
+library(dplyr)
+library(reshape2)
+library(shinyjqui)

app/R/modaldialog_utils.R

@@ -0,0 +1,37 @@
+ShowtestModaldialog = function(data,input,col){
+  showModal(modalDialog(
+    h2("Appearance setting"),
+    
+    div( class = "dynamicSI",
+         lapply(1:length(names(col)), function(i){
+           
+           column(3,   
+                  colorPickr(paste0(names(col)[i],"_selectcolor"),theme = "monolith",label = paste0(names(col)[i],""),  selected  = col[i],interaction =  list(
+                    clear = T,
+                    save = T,
+                    RGBA = TRUE,
+                    input=TRUE,
+                    hex =TRUE
+                    
+                  ))       
+                  
+           )})),
+    br(),
+    br(),
+    br(),
+    br(),
+    br(),
+    easyClose = TRUE,
+    footer = NULL
+  ))
+}
+
+ShowtestModaldialog2 = function(data,input,col){
+  showModal(modalDialog(
+    title = "Plot in Dialog",
+    plotOutput("mappingraph"),
+    actionButton("actionplottest","pathway mapping",onclick = "$(tab).removeClass('disabled')"),
+    easyClose = TRUE,
+    footer = NULL
+  ))
+}

app/R/plot_utils.R

@@ -0,0 +1,487 @@
+create_boxplot <- function(data, x_var, y_var, col, alpha, size, ylab_text, ggtitle_text) {
+  p <- ggplot(data,aes_string(x = x_var, y = y_var, fill = x_var)) +
+     geom_boxplot(color = "black", lwd = 1, alpha = alpha) +
+    ggbeeswarm::geom_beeswarm(aes(text = name), dodge.width = 0.1,
+                               cex = 0.1,
+                               shape = 21,
+                               size = size) +
+    ylab(ylab_text) +
+    ggtitle(paste(ggtitle_text, "", sep = "")) +
+    scale_fill_manual(values = unlist(col))
+  p
+
+}
+
+process_boxplot <- function(input,yval,dataa,col) {
+  
+  y <- yval %>% as.character() 
+  p <- create_boxplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                        label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                          limits = c(min(tukey_result$y.min.position), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                        )
+  }
+  p  <- p + theme_classic() + theme(
+    axis.text.x = element_text(angle = 90, hjust = 1),
+    axis.title.x = element_blank(),
+    aspect.ratio = 0.75,
+    text = element_text(size = input$Fontsize)
+  )
+  ggplotly(p,tooltip = c("name","x"))
+}
+
+process_boxplot_diagram <- function(input,yval,dataa,col) {
+  
+    y <- yval %>% as.character()
+    p <- create_boxplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+    p <- p + theme_prism(
+      base_fontface = "plain",
+      base_line_size = 0.9,
+      base_family = "Arial"
+    ) +
+      scale_x_discrete(
+        guide = guide_prism_bracket(width = 0.1),
+        labels = scales::wrap_format(5)
+      ) +
+      theme(
+        legend.position = "none",
+        axis.title.x = element_blank(),
+        aspect.ratio = 1.0,
+        text = element_text(size = input$Fontsize)
+      )
+    if (input$q != "" && input$pvaluecheck == TRUE) {
+      tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+      p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                          label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                            limits = c(min(dataa[[y]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                          )
+    }
+    p
+}
+
+process_action_boxplot <- function(input,dataa,metainfocol,svg_path,col,output) {
+  
+  withProgress(message = 'Calculation in progress', detail = 'This may take a while...', value = 1, {
+    startnum <- 1 + metainfocol
+    for (i in startnum:ncol(dataa)) {
+      yval <- colnames(dataa)[i]
+      p <- create_boxplot(dataa, input$w, dataa[[yval]], col, input$alpha, input$size, input$yAxisLabel, "")
+      p <- p + theme_prism(
+        base_fontface = "plain",
+        base_line_size = 0.9,
+        base_family = "Arial"
+      ) +
+        scale_x_discrete(
+          guide = guide_prism_bracket(width = 0.1),
+          labels = scales::wrap_format(5)
+        ) +
+        theme(
+          legend.position = "none",
+          axis.title.x = element_blank(),
+          aspect.ratio = 1.0,
+          text = element_text(size = input$Fontsize)
+        )
+      if (input$q != "" && input$pvaluecheck == TRUE) {
+        tukey_result <-  process_tukey_result(input,yval,input$q,p,dataa,0.05,input$Fontsize)
+        p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                            label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                              limits = c(min(dataa[[yval]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                            )
+      }
+      svg(paste("./svg/",colnames(dataa)[i], ".svg", sep = ""))
+      plot(p)
+      dev.off()
+      incProgress(1 / ncol(dataa))
+      Sys.sleep(0.25)
+    }
+  })
+  data.frame(name = colnames(dataa)[-c(1:metainfocol)], path = paste("file:/", svg_path, "/", colnames(dataa)[-c(1:metainfocol)], ".svg", sep = "")) %>% write.csv("./svg/path.csv")
+  output$testtext1 <- renderText({
+    "Finish"
+  })
+}
+
+create_barplot <- function(data, x_var, y_var, col, alpha, size, ylab_text, ggtitle_text) {
+  p <- ggplot(data, aes_string(x = x_var, y = y_var, fill = x_var)) +
+    geom_bar(color = "black", stat = "summary",fun = "mean",lwd = 1.2,width = 0.6) +
+    ylab(ylab_text) +
+    ggtitle(paste(ggtitle_text, "", sep = "")) +
+    scale_fill_manual(values = unlist(col))
+  
+  p
+}
+
+process_barplot <- function(input,yval,dataa,col) {
+  y <- yval %>% as.character()
+  p <- create_barplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result,remove.bracket = TRUE,
+                        bracket.size = 0.000001,
+                        label = "{symbol}",
+                        tip.length = 0,
+                        label.size = tukey_result$size,inherit.aes = FALSE,y.position = tukey_result$y.position_barplot)
+  }
+  p  <- p + theme(
+    axis.text.x = element_text(angle = 90, hjust = 1),
+    axis.title.x = element_blank(),
+    aspect.ratio = 0.75,
+    text = element_text(size = input$Fontsize)
+  )
+  ggplotly(p)
+}
+
+
+process_barplot_diagram <- function(input,yval,dataa,col) {
+  
+  y <- yval %>% as.character()
+  p <- create_barplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  p <- p + theme_prism(
+    base_fontface = "plain",
+    base_line_size = 0.9,
+    base_family = "Arial") +
+    scale_x_discrete(
+      guide = guide_prism_bracket(width = 0.1),
+      labels = scales::wrap_format(5)) +
+    theme(
+      legend.position = "none",
+      axis.title.x = element_blank(),
+      aspect.ratio = 1.0,
+      text = element_text(size = input$Fontsize))
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result,remove.bracket = TRUE,
+                        bracket.size = 0.000001,
+                        label = "{symbol}",
+                        tip.length = 0,
+                        label.size = tukey_result$size,inherit.aes = FALSE,y.position = tukey_result$y.position_barplot)
+  }
+  p
+}
+
+
+
+process_action_barplot <- function(input,dataa,metainfocol,svg_path,col,output) {
+  withProgress(message = 'Calculation in progress', detail = 'This may take a while...', value = 1, {
+    startnum <- 1 + metainfocol
+    for (i in startnum:ncol(dataa)) {
+      yval <- colnames(dataa)[i]
+      p <- create_barplot(dataa, input$w, dataa[[yval]], col, input$alpha, input$size, input$yAxisLabel, "")
+      p <- p + theme_prism(
+        base_fontface = "plain",
+        base_line_size = 0.9,
+        base_family = "Arial") +
+        scale_x_discrete(
+          guide = guide_prism_bracket(width = 0.1),
+          labels = scales::wrap_format(5)) +
+        theme(
+          legend.position = "none",
+          axis.title.x = element_blank(),
+          aspect.ratio = 1.0,
+          text = element_text(size = input$Fontsize))
+      if (input$q!= "" && input$pvaluecheck == TRUE) {
+        tukey_result <-  process_tukey_result(input,yval,input$q,p,dataa,0.05,input$Fontsize)
+        p <- p + add_pvalue(tukey_result,remove.bracket = TRUE,
+                            bracket.size = 0.000001,
+                            label = "{symbol}",
+                            tip.length = 0,
+                            label.size = tukey_result$size,inherit.aes = FALSE,y.position = tukey_result$y.position_barplot) 
+      }
+      svg(paste("./svg/",colnames(dataa)[i], ".svg", sep = ""))
+      plot(p)
+      dev.off()
+    }
+	      incProgress(1 / ncol(dataa))
+      Sys.sleep(0.25)
+  })
+  data.frame(name = colnames(dataa)[-c(1:metainfocol)], path = paste("file:/", svg_path, "/", colnames(dataa)[-c(1:metainfocol)], ".svg", sep = "")) %>% write.csv("./svg/path.csv")
+  output$testtext1 <- renderText({
+    "Finish"
+  })
+}
+
+process_violinplot <- function(input,yval,dataa,col) {
+  
+  y <- yval %>% as.character()
+  p <- create_violinplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  if (input$q != "" &&input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                        label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                          limits = c(min(dataa[[y]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                        ) 
+  }
+  p  <- p + theme(
+    #legend.position = "none",
+    axis.text.x = element_text(angle = 90, hjust = 1),
+    axis.title.x = element_blank(),
+    aspect.ratio = 0.75,
+    text = element_text(size = input$Fontsize)
+  )
+  ggplotly(p)
+  # }
+}
+
+
+create_violinplot <- function(data, x_var, y_var, col, alpha, size, ylab_text, ggtitle_text) {
+  p <- ggplot(data, aes_string(x = x_var, y = y_var, fill = x_var)) +
+    geom_violin(adjust = 2,trim = FALSE) +
+    ylab(ylab_text) +
+    ggtitle(paste(ggtitle_text, "", sep = "")) +
+    scale_fill_manual(values = unlist(col))+
+    stat_summary(fun = "mean",geom = "crossbar",color = "black",linewidth = 0.5, width = 0.5)
+  
+  p
+}
+
+process_violinplot_diagram <- function(input,yval,dataa,col) {
+
+  y <- yval %>% as.character()
+  p <- create_violinplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  p <- p + theme_prism(
+    base_fontface = "plain",
+    base_line_size = 0.9,
+    base_family = "Arial") +
+    scale_x_discrete(
+      guide = guide_prism_bracket(width = 0.1),
+      labels = scales::wrap_format(5)) +
+    theme(
+      legend.position = "none",
+      axis.title.x = element_blank(),
+      aspect.ratio = 1.0,
+      text = element_text(size = input$Fontsize))
+  if (input$q != "" &&input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                        label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                          limits = c(min(dataa[[y]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                        ) 
+  }
+  p
+}
+
+process_action_violinplot <- function(input,dataa,metainfocol,svg_path,col,output) {
+  withProgress(message = 'Calculation in progress', detail = 'This may take a while...', value = 1, {
+    startnum <- 1 + metainfocol
+    for (i in startnum:ncol(dataa)) {
+      yval <- colnames(dataa)[i]
+      p <- create_violinplot(dataa, input$w, dataa[[yval]], col, input$alpha, input$size, input$yAxisLabel, "")
+      p <- p + theme_prism(
+        base_fontface = "plain",
+        base_line_size = 0.9,
+        base_family = "Arial") +
+        scale_x_discrete(
+          guide = guide_prism_bracket(width = 0.1),
+          labels = scales::wrap_format(5)) +
+        theme(
+          legend.position = "none",
+          axis.title.x = element_blank(),
+          aspect.ratio = 1.0,
+          text = element_text(size = input$Fontsize))
+      if (input$q!= "" && input$pvaluecheck == TRUE) {
+        tukey_result <-  process_tukey_result(input,yval,input$q,p,dataa,0.05,input$Fontsize)
+        p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                            label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                              limits = c(min(dataa[[yval]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                            )
+      }
+      svg(paste("./svg/",colnames(dataa)[i], ".svg", sep = ""))
+      plot(p)
+      dev.off()
+    }
+    incProgress(1 / ncol(dataa))
+    Sys.sleep(0.25)
+  })
+  data.frame(name = colnames(dataa)[-c(1:metainfocol)], path = paste("file:/", svg_path, "/", colnames(dataa)[-c(1:metainfocol)], ".svg", sep = "")) %>% write.csv("./svg/path.csv")
+  output$testtext1 <- renderText({
+    "Finish"
+  })
+}
+process_polarplot <- function(input,yval,dataa,col) {
+  
+  # if(is.na(unique(select(dataa,input$w))) != TRUE){
+  y <- yval %>% as.character()
+  p <- create_polarplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y, input$Fontsize)
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result,remove.bracket = TRUE,
+                        bracket.size = 0.000001,
+                        label = "{symbol}",
+                        tip.length = 0,
+                        label.size = tukey_result$size,inherit.aes = FALSE,y.position = tukey_result$y.position_barplot)
+  }
+  plot(p)
+  # }
+}
+
+create_polarplot <- function(data, x_var, y_var, col, alpha, size, ylab_text, ggtitle_text, Fontsize) {
+  p <- ggplot(data, aes_string(x = x_var, y = y_var, fill = x_var)) +
+    geom_bar(color = "black", stat = "summary",fun = "mean",lwd = 1.2,width = 0.6) +
+    coord_polar()+
+    scale_fill_manual(values = unlist(col))+
+    labs(
+      x="", 
+      y="")+
+    theme_minimal(10) +
+    theme(
+      axis.text.x = element_text(size = Fontsize, angle = 360,hjust=0.8),
+      axis.title.x = element_blank(),
+      panel.grid.minor = element_blank(),
+      axis.ticks.y = element_blank())+
+    easy_remove_axes()
+  
+  return(p)
+}
+
+
+
+process_dotplot <- function(input,yval,dataa,col) {
+  y <- yval %>% as.character()
+  p <- create_dotplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                        label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                          limits = c(min(tukey_result$y.min.position), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                        ) 
+  }
+  p <- p + theme(
+    axis.title.x = element_blank(),
+    aspect.ratio = 0.2,
+    axis.text.x = element_text(angle = 90, hjust = 1),
+    text = element_text(size = input$Fontsize)
+  )
+  ggplotly(p,tooltip = c("name","x"))
+}
+
+
+create_dotplot <- function(data, x_var, y_var, col, alpha, size, ylab_text, ggtitle_text) {
+  p <- ggplot(data,aes_string(x = x_var, y = y_var, fill = x_var)) +
+    ggbeeswarm::geom_beeswarm(aes(text = name),
+                              cex = 0.1,
+                              shape = 21,
+                              size = size)+stat_summary(fun = "mean",geom = "crossbar",color = "red",linewidth = 0.5, width = 0.5)+
+    ylab(ylab_text) +
+    ggtitle(paste(ggtitle_text, "", sep = "")) +
+	theme_classic() +
+	theme(aspect.ratio = 1.0)+
+    scale_fill_manual(values = unlist(col)) 
+  p
+}
+
+process_dotplot_diagram <- function(input,yval,dataa,col) {
+  
+  
+  y <- yval %>% as.character()
+  p <- create_dotplot(dataa, input$w, y, col, input$alpha, input$size, input$yAxisLabel, y)
+  p <- p + theme_prism(
+    base_fontface = "plain",
+    base_line_size = 0.9,
+    base_family = "Arial"
+  ) +
+    scale_x_discrete(
+      guide = guide_prism_bracket(width = 0.1),
+      labels = scales::wrap_format(5)
+    ) +
+    theme(
+      legend.position = "none",
+      axis.title.x = element_blank(),
+      aspect.ratio = 1.0,
+      text = element_text(size = input$Fontsize)
+    )
+  if (input$q != "" && input$pvaluecheck == TRUE) {
+    tukey_result <-  process_tukey_result(input,y,input$q,p,dataa,0.05,input$Fontsize)
+    p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                        label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                          limits = c(min(dataa[[y]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                        )
+  }
+  p
+}
+
+process_action_dotplot <- function(input,dataa,metainfocol,svg_path,col,output) {
+  
+  withProgress(message = 'Calculation in progress', detail = 'This may take a while...', value = 1, {
+    startnum <- 1 + metainfocol
+    for (i in startnum:ncol(dataa)) {
+      yval <- colnames(dataa)[i]
+      p <- create_dotplot(dataa, input$w, dataa[[yval]], col, input$alpha, input$size, input$yAxisLabel, "")
+      p <- p + theme_prism(
+        base_fontface = "plain",
+        base_line_size = 0.9,
+        base_family = "Arial"
+      ) +
+        scale_x_discrete(
+          guide = guide_prism_bracket(width = 0.1),
+          labels = scales::wrap_format(5)
+        ) +
+        theme(
+          legend.position = "none",
+          axis.title.x = element_blank(),
+          aspect.ratio = 1.0,
+          text = element_text(size = input$Fontsize)
+        )
+      if (input$q != "" && input$pvaluecheck == TRUE) {
+        tukey_result <-  process_tukey_result(input,yval,input$q,p,dataa,0.05,input$Fontsize)
+        p <- p + add_pvalue(tukey_result, remove.bracket = TRUE, bracket.size = 0.000001, label = "{symbol}", tip.length = 0,
+                            label.size = tukey_result$size, inherit.aes = FALSE,y.position = tukey_result$y.position_boxplot) + scale_y_continuous(
+                              limits = c(min(dataa[[yval]]), (max(tukey_result$y.position_boxplot) + max(tukey_result$y.position_boxplot) / 30))
+                            )
+      }
+      svg(paste("./svg/",colnames(dataa)[i], ".svg", sep = ""))
+      plot(p)
+      dev.off()
+      incProgress(1 / ncol(dataa))
+      Sys.sleep(0.25)
+    }
+  })
+  data.frame(name = colnames(dataa)[-c(1:metainfocol)], path = paste("file:/", svg_path, "/", colnames(dataa)[-c(1:metainfocol)], ".svg", sep = "")) %>% write.csv("./svg/path.csv")
+  output$testtext1 <- renderText({
+    "Finish"
+  })
+}
+
+process_select_color_input <- function(input,data) {
+  if (length(grep(paste0(unique(as.matrix(select(data, input$w)))[1], "_selectcolor"), names(input), value = TRUE)) != 0) {
+    inputlist <- grep("selectcolor", names(input), value = TRUE)
+    for (input_name in inputlist) {
+      collist[str_remove_all(input_name, pattern = "_selectcolor")] <- input[[input_name]]
+    }
+    cola <<- unlist(collist)
+    cola <- cola[c(unique(data[[input$w]]))]
+    return(cola)
+  }
+}
+
+
+
+process_tukey_result <- function(input,yval, q,plot_obj, dataa, p_adj_threshold, Fontsize) {
+  yval <- gsub("`","",yval)
+  y <- dataa %>% pull(as.symbol(yval))
+  w <- dataa %>% pull(as.symbol(input$w))
+  tukey_result <- TukeyHSD(aov(y ~ w, data = dataa))
+  tukey_result <- data.frame(tukey_result$w)
+  a <- str_split_fixed(rownames(tukey_result), "-", 2)
+  colnames(a) <- c("Class1", "Class2")
+  
+  tukey_result <- cbind(a, tukey_result)
+  maxvalue <- select(dataa,input$w,yval) %>%
+    group_by_(input$w) %>%
+    mutate(Mean = mean(!!as.symbol(yval))) %>%
+    ungroup() %>%
+    distinct(!!as.symbol(input$w),.keep_all = TRUE )
+  
+  maxvalue <- max(maxvalue$Mean)
+  tukey_result <- filter(tukey_result, Class1 %in% q | Class2 %in% q) %>%
+    mutate(group2 = ifelse(Class1 == q, Class2, Class1)) %>%
+    mutate(group1 = paste0(q)) %>%
+    mutate(symbol = ifelse(p.adj < p_adj_threshold, "*", "")) %>%
+    select(group1, group2, p.adj, symbol) %>%
+    mutate(y.position_boxplot = max(dataa[[yval]])) %>%
+    mutate(y.position_barplot = maxvalue-maxvalue/15 ) %>%
+    mutate(y.min.position = min(dataa[[yval]])) %>%
+    mutate(size = ifelse(symbol != "*", 0, Fontsize))
+  return(tukey_result)
+}

app/R/runShinyApp.R

@@ -0,0 +1,2 @@
+shiny::runApp(appDir = getwd())
+

app/R/runplumber.R

@@ -0,0 +1,52 @@
+library(plumber)
+# 'plumber.R' is the location of the file shown above
+#
+ # RUN = "TRUE"
+ # while(RUN == "TRUE"){
+ #   a <- readLines("./runShinyApp.Rout")
+ #   b <- grepl("Close the program", a)
+ #   if(TRUE %in% b) {
+ #     RUN = "FALSE"
+ #     stop()
+ #   }
+ # }
+pr("./shiny/plumber.R") %>%
+  pr_run()
+
+
+# library(plumbplumb)
+# library(plumber)
+# 
+# .state <- new.env(parent = emptyenv()) #create .state when package is first loaded
+# 
+# start_plumber3 <- function(path) {
+#   trml <- rstudioapi::terminalCreate(show = FALSE)
+#   rstudioapi::terminalSend(trml, "R\n") 
+#   Sys.sleep(2)
+#   cmd <- sprintf('plumber::plumb("%s")$run()\n', path)
+#   rstudioapi::terminalSend(trml, cmd)
+#   
+#   .state[["trml"]] <- trml #store terminal name
+#   invisible(trml)
+# }
+# 
+# kill_plumber <- function() {
+#   rstudioapi::terminalKill(.state[["trml"]]) #access terminal name
+# }
+# 
+# 
+# 
+# plumber_path <- system.file("./shiny/plumber.R", package = "plumbplumb")
+# start_plumber3(plumber_path)
+
+# while (TRUE) {
+#   a <- readLines("./runShinyApp.Rout")
+#   b <- grepl("Close the program", a)
+#   print("ccccc")
+#   if (TRUE %in% b) {
+#     message("Stopping the loop...")
+#     future::plan("sequential")
+#     quit()
+#   }
+#   Sys.sleep(1)
+# }

app/R/selectcolor_utils.R

@@ -0,0 +1,12 @@
+collist <- list()
+colset <- function(input,col){
+  if(length(grep("selectcolor", names(input), value = TRUE)) != 0){
+    inputlist<- grep("selectcolor", names(input), value = TRUE) 
+    for (input_name in inputlist) {
+      
+      collist[str_remove_all(input_name,pattern = "_selectcolor")] <- input[[input_name]]
+      
+    }
+    col <<- unlist(collist)
+    col <<- col[c(unique(data[[input$x]]))]
+  }}

app/R/ui_modules.R

@@ -0,0 +1,268 @@
+library(shinyjs)
+plotTabAppearanceUI <- function(
+    title, imgSrc, width, height, outputId, outputId2, textOutputId
+) {
+  mainPanel(
+    width = 10,
+    h3(title),
+    wellPanel(
+      plotlyOutput(outputId, width = "100%", height = "600px")
+    ),
+    selectInput(
+      inputId = "mol",
+      label = "molecule:",
+      choices = NULL
+    ),
+    wellPanel(
+      plotlyOutput(outputId2, width = "100%", height = "600px")
+    ),
+    textOutput(outputId = textOutputId),
+    br(), br(), br(), br()
+  )
+}
+
+
+footer <- dashboardFooter(
+  left = tagList(
+    # Define shared style for dropdown buttons and container
+    tags$head(tags$style(HTML("
+      #Colorpicker, #exportgraph {
+        background-color: #3D3D3D;
+        border-color: #3D3D3D;
+      }
+      .button-container {
+        display: flex;
+        flex-direction: row;
+        align-items: center;
+        gap: 10px;  /* 間隔を調整 */
+      }
+    "))),
+    
+    # Container for buttons
+    div(class = "button-container",
+      # Color Picker Dropdown Button
+      dropdownButton(
+        inputId = "Colorpicker",
+        circle = TRUE, 
+        status = "danger",
+        icon = icon("palette"), 
+        width = "500px", 
+        tooltip = tooltipOptions(title = "Color option!")
+      ),
+      
+      # Export Graph Dropdown Button
+      dropdownButton(
+        inputId = "exportgraph",
+        circle = TRUE, 
+        status = "danger",
+        icon = icon("diagram-project"), 
+        width = "500px", 
+        tooltip = tooltipOptions(title = "Mapping option!")
+      )
+    )
+  )
+)
+
+         
+createCustomSidebar <- function(y_id, w_id, z_id, alpha_id, size_id, fontsize_id,orderInputId, pValueCheckId, qInputId) {
+  sidebarPanel(
+    width = 2,
+    tags$h2("Plot setting"),
+	h3("Plot type"),
+    esquisse::dropInput(
+      inputId = "mydrop",
+      choicesNames = tagList(
+        list(img(
+          src = "./boxplot.png",
+          style = "margin-left: 5px; margin-bottom: 4px; margin-top: 0px; width: 50px; height: 50px;"
+        ), style = "width: 100px;"),
+        list(img(
+          src = "./barplot.png",
+          style = "margin-left: 5px; margin-bottom: 4px; margin-top: 0px; width: 50px; height: 50px;"
+        ), style = "width: 100px;"),
+        list(img(
+          src = "./violin2.png",
+          style = "margin-left: 5px; margin-bottom: 4px; margin-top: 0px; width: 50px; height: 50px;"
+        ), style = "width: 100px;"),
+        list(img(
+          src = "./dotplot.png",
+          style = "margin-left: 5px; margin-bottom: 4px; margin-top: 0px; width: 50px; height: 50px;"
+        ), style = "width: 100px;")
+      ),
+      choicesValues = c("box", "bar", "violin", "coding"),
+      dropWidth = "220px"
+    ),
+    selectInput(inputId = y_id, label = "Y-axis:", choices = NULL),
+    selectInput(inputId = w_id, label = "X-axis:", choices = c("Class"), selected = "Class"),
+    sliderInput(inputId = alpha_id, label = "Alpha:", min = 0, max = 1, value = 1),
+    chooseSliderSkin("Round", color = "DarkTurquoise"),
+    sliderInput(inputId = size_id, label = "Size:", min = 0, max = 10, value = 5),
+    numericInput(inputId = fontsize_id, label = "Fontsize:", value = 20, min = 1, max = 30),
+	textInput("yAxisLabel", "Enter y-axis label:", "Normalized expression"),
+    orderInput(
+      inputId = orderInputId,
+      label = "Factor level order",
+      items = c(""),
+      width = "100%"
+    ),
+    checkboxInput(
+      inputId = pValueCheckId,
+      label = "Add p-value",
+      value = FALSE
+    ),
+    selectInput(
+      inputId = qInputId,
+      label = "p-value (Tukey-Kramer test) from:",
+      choices = c(""),
+      selected = ""
+    ),
+    br(),
+    br(),
+    h5("Ver 1.20240906"),
+    br(),
+    footer
+  )
+}
+
+transcriptomeuploadpanel <- wellPanel(
+  h3("Other Omics Data", style = "color: #2c3e50; border-bottom: 2px solid #2c3e50; padding-bottom: 10px;"),
+  selectInput(
+    inputId = "transcriptomefiletype",
+    label = "Input format:",
+    choices = c("Sample in cols"),
+    selected = "Sample in cols"
+  ),
+  fileInput(
+    inputId = "transcriptomefile",
+    label = "Input transcriptome data:",
+    accept = c("text/csv", "text/comma-separated-values,text/plain", ".csv")
+  ),
+  hr(),
+  h3("Input Meta Data", style = "color: #2c3e50; border-bottom: 2px solid #2c3e50; padding-bottom: 10px;"),
+  h5("If necessary, you can add class information.", style = "font-style: italic; color: #7f8c8d;"),
+  fileInput(
+    inputId = "file2",
+    label = "Input meta data file:",
+    accept = c("text/csv", "text/comma-separated-values,text/plain", ".csv")
+  )
+)
+
+uploadpanel <- tabPanel(
+  value = "uploadtab",
+  tagList(
+    div(
+      style = "display: flex; align-items: center; justify-content: center; margin-bottom: 15px;",
+      img(src = "./upload.png", style = "width: 50px; height: 50px; margin-right: 10px;"),
+      div(style = "font-size: 18px; color: #000000; font-weight: bold;", "Data Upload")
+    )
+  ),
+  fluidRow(
+    column(
+      width = 3,
+      wellPanel(
+        h3("Input Metabolome Table (.csv)", style = "color: #2c3e50; border-bottom: 2px solid #2c3e50; padding-bottom: 10px;"),
+        selectInput(
+          inputId = "filetype",
+          label = "Input format:",
+          choices = c("MS-DIAL export", "Sample in rows"),
+          selected = "MS-DIAL export"
+        ),
+        fileInput(
+          inputId = "file1",
+          label = "Input peak table:",
+          accept = c("text/csv", "text/comma-separated-values,text/plain", ".csv")
+        ),
+        fileInput(
+          inputId = "ontfile",
+          label = "Input ontology file:",
+          accept = c("text/csv", "text/comma-separated-values,text/plain", ".csv")
+        ),
+		hr(),
+		h3("Try Our Test Data", style = "color: #2c3e50; border-bottom: 2px solid #2c3e50; padding-bottom: 10px;"),
+        fluidRow(
+          column(2, radioButtons("radio", "", choices = c(" "))),
+          column(10, downloadLink(outputId = "downloadData", label = "Download Aging Mouse Data", class = "btn btn-info btn-block"))
+        ),
+        div(style = "margin-top: 20px;",
+          actionButton(
+            inputId = "submit",
+            label = "Submit Data",
+            class = "btn-primary",
+            style = "font-size: 16px; padding: 8px 24px; width: auto;"
+          )
+        )
+      )
+    ),
+    column(
+      width = 3,
+      transcriptomeuploadpanel
+    )
+  )
+)
+
+originalplotTabAppearanceUI <- tabPanel(
+  value = "test",
+  tagList(
+    img(
+      src = "./cord.png",
+      style = "margin-left: 5px; margin-bottom: 4px; margin-top: 0px; width: 50px; height: 50px;"
+    ),
+    div(
+      style = "font-size: 10px; color: #000000; text-align: center;",
+      HTML(' '), "coding", HTML(' ')
+    )
+  ),
+  mainPanel(
+    width = 10,
+    h3("original"),
+    fluidRow(
+      column(
+        width = 6,
+        aceEditor(
+          "code",
+          value = "p <- ggplot(data = data, aes(y = Yvariable, x = Class)) + 
+                  ggbeeswarm::geom_beeswarm(aes(fill = Class), 
+                                            dodge.width = 0.1, 
+                                            shape = 21,
+                                            size = 3,
+                                            cex = 1
+                  ) +
+                  stat_summary(
+                    geom = \"crossbar\",
+                    aes(fill = Class),
+                    fun = mean,
+                    position = position_dodge(0.9),
+                    colour = \"red\",
+                    linewidth = 0.5, width = 0.7,
+                    show.legend = FALSE
+                  ) +
+                  theme_prism(
+                    base_fontface = \"plain\", 
+                    base_line_size = 0.9, 
+                    base_family = \"Arial\"
+                  ) +
+                  scale_x_discrete(
+                    guide = guide_prism_bracket(width = 0.1),
+                    labels = scales::wrap_format(5)
+                  ) +
+                  theme(aspect.ratio = 1.0)
+          p"
+        ),
+        actionButton("runButton", "Run Code")
+      ),
+      column(
+        width = 6,
+        plotOutput("plot"),
+        downloadButton("downloadPlot", "Download Plot")
+      )
+    )
+  )
+)
+
+
+
+
+
+
+
+

app/data/ceramidepathway.cyjs

@@ -0,0 +1,2528 @@
+{
+  "format_version" : "1.0",
+  "generated_by" : "cytoscape-3.10.0",
+  "target_cytoscapejs_version" : "~2.1",
+  "data" : {
+    "shared_name" : "Network(1)",
+    "name" : "Network(1)",
+    "SUID" : 51687,
+    "__Annotations" : [ "" ],
+    "selected" : true
+  },
+  "elements" : {
+    "nodes" : [ {
+      "data" : {
+        "id" : "60361",
+        "Shape" : "Ellipse",
+        "Fillcolor" : "#ffffff",
+        "Color" : "",
+        "label" : " ",
+        "Label_size" : 1,
+        "shared_name" : "Node 18",
+        "LabelFont" : "",
+        "path" : "http://localhost:9000/plot?str1=Node1.svg",
+        "pathpng" : "http://localhost:9000/png?str2=(Node1).png",
+        "name" : "Node 18",
+        "Ensembl_ID" : "",
+        "SUID" : 60361,
+        "Height" : 1,
+        "Width" : 1,
+        "selected" : false
+      },
+      "position" : {
+        "x" : -772.3715110031136,
+        "y" : -442.24842702277897
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59880",
+        "Shape" : "Ellipse",
+        "Fillcolor" : "#ffffff",
+        "Color" : "",
+        "label" : " ",
+        "Label_size" : 1,
+        "shared_name" : "Node 13",
+        "LabelFont" : "",
+        "path" : "http://localhost:9000/plot?str1=Node1.svg",
+        "pathpng" : "http://localhost:9000/png?str2=(Node1).png",
+        "name" : "Node 13",
+        "Ensembl_ID" : "",
+        "SUID" : 59880,
+        "Height" : 1,
+        "Width" : 1,
+        "selected" : false
+      },
+      "position" : {
+        "x" : -1180.4239308066317,
+        "y" : -358.0486505034973
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59874",
+        "Shape" : "Ellipse",
+        "Fillcolor" : "#ffffff",
+        "Color" : "",
+        "label" : " ",
+        "Label_size" : 1,
+        "shared_name" : "Node 2",
+        "LabelFont" : "",
+        "path" : "http://localhost:9000/plot?str1=Node1.svg",
+        "pathpng" : "http://localhost:9000/png?str2=(Node1).png",
+        "name" : "Node 2",
+        "Ensembl_ID" : "",
+        "SUID" : 59874,
+        "Height" : 1,
+        "Width" : 1,
+        "selected" : false
+      },
+      "position" : {
+        "x" : -1182.4911756886006,
+        "y" : 111.7836490135568
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59832",
+        "Shape" : "Ellipse",
+        "Fillcolor" : "#ffffff",
+        "Color" : "",
+        "label" : " ",
+        "Label_size" : 1,
+        "shared_name" : "Node 6",
+        "LabelFont" : "",
+        "path" : "http://localhost:9000/plot?str1=Node1.svg",
+        "pathpng" : "http://localhost:9000/png?str2=(Node1).png",
+        "name" : "Node 6",
+        "Ensembl_ID" : "",
+        "SUID" : 59832,
+        "Height" : 1,
+        "Width" : 1,
+        "selected" : false
+      },
+      "position" : {
+        "x" : -937.4993548517596,
+        "y" : -50.61982027825535
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59829",
+        "Shape" : "Ellipse",
+        "Fillcolor" : "#ffffff",
+        "Color" : "",
+        "label" : " ",
+        "Label_size" : 1,
+        "shared_name" : "Node 4",
+        "LabelFont" : "",
+        "path" : "http://localhost:9000/plot?str1=Node1.svg",
+        "pathpng" : "http://localhost:9000/png?str2=(Node1).png",
+        "name" : "Node 4",
+        "Ensembl_ID" : "",
+        "SUID" : 59829,
+        "Height" : 1,
+        "Width" : 1,
+        "selected" : false
+      },
+      "position" : {
+        "x" : -937.6842371049761,
+        "y" : 59.53152187837176
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59826",
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+        "interaction" : "interacts with",
+        "SUID" : 51934,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51932",
+        "source" : "51822",
+        "target" : "51776",
+        "shared_name" : "Cer_NDS (interacts with) Cer_NS",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_NDS (interacts with) Cer_NS",
+        "interaction" : "interacts with",
+        "SUID" : 51932,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51930",
+        "source" : "51822",
+        "target" : "51732",
+        "shared_name" : "Cer_NDS (interacts with) HexCer_NDS",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_NDS (interacts with) HexCer_NDS",
+        "interaction" : "interacts with",
+        "SUID" : 51930,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51928",
+        "source" : "51818",
+        "target" : "51820",
+        "shared_name" : "St3gal5 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "St3gal5 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51928,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51926",
+        "source" : "51798",
+        "target" : "51804",
+        "shared_name" : "B4galt5 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "B4galt5 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51926,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51924",
+        "source" : "51794",
+        "target" : "51812",
+        "shared_name" : "Gal3st1 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "Gal3st1 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51924,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51922",
+        "source" : "51794",
+        "target" : "51716",
+        "shared_name" : "Gal3st1 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "Gal3st1 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51922,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51920",
+        "source" : "51792",
+        "target" : "51828",
+        "shared_name" : "Cer_AS (interacts with) HexCer_HS",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_AS (interacts with) HexCer_HS",
+        "interaction" : "interacts with",
+        "SUID" : 51920,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51918",
+        "source" : "51788",
+        "target" : "51790",
+        "shared_name" : "UGT8a (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "UGT8a (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51918,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51914",
+        "source" : "51788",
+        "target" : "51802",
+        "shared_name" : "UGT8a (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "UGT8a (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51914,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51912",
+        "source" : "51780",
+        "target" : "51850",
+        "shared_name" : "GM3 (interacts with) GM2",
+        "shared_interaction" : "interacts with",
+        "name" : "GM3 (interacts with) GM2",
+        "interaction" : "interacts with",
+        "SUID" : 51912,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51910",
+        "source" : "51776",
+        "target" : "51784",
+        "shared_name" : "Cer_NS (interacts with) Sph",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_NS (interacts with) Sph",
+        "interaction" : "interacts with",
+        "SUID" : 51910,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51908",
+        "source" : "51776",
+        "target" : "51746",
+        "shared_name" : "Cer_NS (interacts with) HexCer_NS",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_NS (interacts with) HexCer_NS",
+        "interaction" : "interacts with",
+        "SUID" : 51908,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51906",
+        "source" : "51776",
+        "target" : "51748",
+        "shared_name" : "Cer_NS (interacts with) SM",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_NS (interacts with) SM",
+        "interaction" : "interacts with",
+        "SUID" : 51906,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51904",
+        "source" : "51772",
+        "target" : "51808",
+        "shared_name" : "SMS (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "SMS (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51904,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51902",
+        "source" : "51768",
+        "target" : "51786",
+        "shared_name" : "DEGS2 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "DEGS2 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51902,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51898",
+        "source" : "51764",
+        "target" : "51778",
+        "shared_name" : "DEGS1 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "DEGS1 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51898,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51896",
+        "source" : "51764",
+        "target" : "51782",
+        "shared_name" : "DEGS1 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "DEGS1 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51896,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51892",
+        "source" : "51756",
+        "target" : "51760",
+        "shared_name" : "FA2H (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "FA2H (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51892,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59850",
+        "source" : "51754",
+        "target" : "59829",
+        "shared_name" : "2OH-FA (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "2OH-FA (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 59850,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51890",
+        "source" : "51752",
+        "target" : "51800",
+        "shared_name" : "Cer_AP (interacts with) HexCer_AP",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_AP (interacts with) HexCer_AP",
+        "interaction" : "interacts with",
+        "SUID" : 51890,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51888",
+        "source" : "51750",
+        "target" : "51752",
+        "shared_name" : "Cer_ADS (interacts with) Cer_AP",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_ADS (interacts with) Cer_AP",
+        "interaction" : "interacts with",
+        "SUID" : 51888,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51886",
+        "source" : "51750",
+        "target" : "51792",
+        "shared_name" : "Cer_ADS (interacts with) Cer_AS",
+        "shared_interaction" : "interacts with",
+        "name" : "Cer_ADS (interacts with) Cer_AS",
+        "interaction" : "interacts with",
+        "SUID" : 51886,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51884",
+        "source" : "51746",
+        "target" : "51730",
+        "shared_name" : "HexCer_NS (interacts with) Hex2Cer",
+        "shared_interaction" : "interacts with",
+        "name" : "HexCer_NS (interacts with) Hex2Cer",
+        "interaction" : "interacts with",
+        "SUID" : 51884,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51882",
+        "source" : "51746",
+        "target" : "51826",
+        "shared_name" : "HexCer_NS (interacts with) SHexCer",
+        "shared_interaction" : "interacts with",
+        "name" : "HexCer_NS (interacts with) SHexCer",
+        "interaction" : "interacts with",
+        "SUID" : 51882,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51880",
+        "source" : "51437",
+        "target" : "51852",
+        "shared_name" : "B3galt4 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "B3galt4 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51880,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51878",
+        "source" : "51435",
+        "target" : "51814",
+        "shared_name" : "B4galnt1 (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "B4galnt1 (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 51878,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59893",
+        "source" : "51738",
+        "target" : "59880",
+        "shared_name" : "FA (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "FA (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 59893,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "59788",
+        "source" : "51738",
+        "target" : "59754",
+        "shared_name" : "FA (interacts with) Node 1",
+        "shared_interaction" : "interacts with",
+        "name" : "FA (interacts with) Node 1",
+        "interaction" : "interacts with",
+        "SUID" : 59788,
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "51872",
+        "source" : "51730",
+        "target" : "51780",
+        "shared_name" : "Hex2Cer (interacts with) GM3",
+        "shared_interaction" : "interacts with",
+        "name" : "Hex2Cer (interacts with) GM3",
+        "interaction" : "interacts with",
+        "SUID" : 51872,
+        "selected" : false
+      },
+      "selected" : false
+    } ]
+  }
+}

app/data/lipidclassproperties.csv

@@ -0,0 +1,177 @@
+LbmClass,Categories,AcylChain,AlkylChain,SphingoChain,ExtraAcylChain,TotalChain
+Undefined,Undefined,0,0,0,0,0
+Others,Others,0,0,0,0,0
+Unknown,Unknown,0,0,0,0,0
+SPLASH,SPLASH,0,0,0,0,0
+FA,Fatty acyls,1,0,0,0,1
+FAHFA,Fatty acyls,1,0,0,1,1
+OxFA,Fatty acyls,1,0,0,0,1
+CAR,Fatty acyls,1,0,0,0,1
+NAE,Fatty acyls,1,0,0,0,1
+NAGly,Fatty acyls,1,0,0,1,1
+NAGlySer,Fatty acyls,1,0,0,1,1
+NAOrn,Fatty acyls,1,0,0,1,1
+NAPhe,Fatty acyls,1,0,0,1,1
+NATau,Fatty acyls,1,0,0,1,1
+PA,Glycerophospholipids,2,0,0,0,2
+PC,Glycerophospholipids,2,0,0,0,2
+PE,Glycerophospholipids,2,0,0,0,2
+PG,Glycerophospholipids,2,0,0,0,2
+PI,Glycerophospholipids,2,0,0,0,2
+PS,Glycerophospholipids,2,0,0,0,2
+PT,Glycerophospholipids,2,0,0,0,2
+BMP,Glycerophospholipids,2,0,0,0,2
+HBMP,Glycerophospholipids,3,0,0,0,3
+EtherPC,Glycerophospholipids,1,1,0,0,2
+EtherPE,Glycerophospholipids,1,1,0,0,2
+EtherPI,Glycerophospholipids,1,1,0,0,2
+EtherPS,Glycerophospholipids,1,1,0,0,2
+EtherPG,Glycerophospholipids,1,1,0,0,2
+OxPA,Glycerophospholipids,2,0,0,0,2
+OxPC,Glycerophospholipids,2,0,0,0,2
+OxPS,Glycerophospholipids,2,0,0,0,2
+OxPE,Glycerophospholipids,2,0,0,0,2
+OxPG,Glycerophospholipids,2,0,0,0,2
+OxPI,Glycerophospholipids,2,0,0,0,2
+EtherOxPC,Glycerophospholipids,1,1,0,0,2
+EtherOxPE,Glycerophospholipids,1,1,0,0,2
+LPC,Glycerophospholipids,1,0,0,0,1
+LPE,Glycerophospholipids,1,0,0,0,1
+LPA,Glycerophospholipids,1,0,0,0,1
+LPS,Glycerophospholipids,1,0,0,0,1
+LPI,Glycerophospholipids,1,0,0,0,1
+LPG,Glycerophospholipids,1,0,0,0,1
+PMeOH,Glycerophospholipids,2,0,0,0,2
+PEtOH,Glycerophospholipids,2,0,0,0,2
+PBtOH,Glycerophospholipids,2,0,0,0,2
+EtherLPC,Glycerophospholipids,0,1,0,0,1
+EtherLPE,Glycerophospholipids,0,1,0,0,1
+EtherLPG,Glycerophospholipids,0,1,0,0,1
+EtherLPS,Glycerophospholipids,0,1,0,0,1
+EtherLPI,Glycerophospholipids,0,1,0,0,1
+LNAPE,Glycerophospholipids,2,0,0,0,2
+LNAPS,Glycerophospholipids,2,0,0,0,2
+MLCL,Glycerophospholipids,3,0,0,0,3
+DLCL,Glycerophospholipids,2,0,0,0,2
+CL,Glycerophospholipids,4,0,0,0,4
+MG,Glycerolipids,1,0,0,0,1
+DG,Glycerolipids,2,0,0,0,2
+TG,Glycerolipids,3,0,0,0,3
+MGDG,Glycerolipids,2,0,0,0,2
+DGDG,Glycerolipids,2,0,0,0,2
+SQDG,Glycerolipids,2,0,0,0,2
+DGTS,Glycerolipids,2,0,0,0,2
+DGTA,Glycerolipids,2,0,0,0,2
+DGGA,Glycerolipids,2,0,0,0,2
+ADGGA,Glycerolipids,3,0,0,0,3
+LDGTS,Glycerolipids,1,0,0,0,1
+LDGTA,Glycerolipids,1,0,0,0,1
+LDGCC,Glycerolipids,1,0,0,0,1
+DGCC,Glycerolipids,2,0,0,0,2
+EtherMGDG,Glycerolipids,1,1,0,0,2
+EtherDGDG,Glycerolipids,1,1,0,0,2
+EtherTG,Glycerolipids,2,1,0,0,3
+EtherDG,Glycerolipids,1,1,0,0,2
+EtherSMGDG,Glycerolipids,1,1,0,0,2
+SMGDG,Glycerolipids,2,0,0,0,2
+Sph,Sphingolipids,1,0,0,0,1
+DHSph,Sphingolipids,1,0,0,0,1
+PhytoSph,Sphingolipids,1,0,0,0,1
+SM,Sphingolipids,2,0,0,0,2
+CerP,Sphingolipids,1,0,1,0,2
+Cer_ADS,Sphingolipids,1,0,1,0,2
+Cer_AS,Sphingolipids,1,0,1,0,2
+Cer_BDS,Sphingolipids,1,0,1,0,2
+Cer_BS,Sphingolipids,1,0,1,0,2
+Cer_OS,Sphingolipids,1,0,1,0,2
+Cer_EODS,Sphingolipids,1,0,1,1,2
+Cer_EOS,Sphingolipids,1,0,1,1,2
+Cer_NDS,Sphingolipids,1,0,1,0,2
+Cer_NS,Sphingolipids,1,0,1,0,2
+Cer_NP,Sphingolipids,1,0,1,0,2
+Cer_AP,Sphingolipids,1,0,1,0,2
+Cer_EBDS,Sphingolipids,1,0,1,1,2
+Cer_HS,Sphingolipids,1,0,1,0,2
+Cer_HDS,Sphingolipids,1,0,1,0,2
+Cer_NDOS,Sphingolipids,1,0,1,0,2
+HexCer_NS,Sphingolipids,1,0,1,0,2
+HexCer_NDS,Sphingolipids,1,0,1,0,2
+HexCer_AP,Sphingolipids,1,0,1,0,2
+HexCer_HS,Sphingolipids,1,0,1,0,2
+HexCer_HDS,Sphingolipids,1,0,1,0,2
+HexCer_EOS,Sphingolipids,1,0,1,1,2
+Hex2Cer,Sphingolipids,1,0,1,0,2
+Hex3Cer,Sphingolipids,1,0,1,0,2
+SHexCer,Sphingolipids,1,0,1,0,2
+GM3,Sphingolipids,1,0,1,0,2
+AHexCer,Sphingolipids,2,0,1,0,3
+ASM,Sphingolipids,1,0,1,1,8
+PE_Cer,Sphingolipids,2,0,0,0,2
+PI_Cer,Sphingolipids,2,0,0,0,2
+SL,Sphingolipids,2,0,0,0,2
+Ac2PIM1,Glycerophospholipids,2,0,0,0,2
+Ac2PIM2,Glycerophospholipids,2,0,0,0,2
+Ac3PIM2,Glycerophospholipids,3,0,0,0,2
+Ac4PIM2,Glycerophospholipids,4,0,0,0,2
+LipidA,Saccharolipids,4,0,0,2,4
+Vitamin_E,Prenol Lipids,0,0,0,0,0
+Vitamin_D,Sterol Lipids,0,0,0,0,0
+CoQ,Prenol Lipids,0,0,0,0,0
+CE,Sterol Lipids,1,0,0,0,1
+DCAE,Sterol Lipids,1,0,0,0,1
+GDCAE,Sterol Lipids,1,0,0,0,1
+GLCAE,Sterol Lipids,1,0,0,0,1
+TDCAE,Sterol Lipids,1,0,0,0,1
+TLCAE,Sterol Lipids,1,0,0,0,1
+BileAcid,Sterol Lipids,0,0,0,0,0
+VAE,Prenol Lipids,1,0,0,0,1
+BRSE,Sterol Lipids,1,0,0,0,1
+CASE,Sterol Lipids,1,0,0,0,1
+SISE,Sterol Lipids,1,0,0,0,1
+STSE,Sterol Lipids,1,0,0,0,1
+AHexBRS,Sterol Lipids,1,0,0,0,1
+AHexCAS,Sterol Lipids,1,0,0,0,1
+AHexCS,Sterol Lipids,1,0,0,0,1
+AHexSIS,Sterol Lipids,1,0,0,0,1
+AHexSTS,Sterol Lipids,1,0,0,0,1
+SPE,Unknown,0,0,0,0,0
+SHex,Sterol Lipids,0,0,0,0,0
+SPEHex,Unknown,0,0,0,0,0
+SPGHex,Unknown,0,0,0,0,0
+CSLPHex,Unknown,1,0,0,0,1
+BRSLPHex,Unknown,1,0,0,0,1
+CASLPHex,Unknown,1,0,0,0,1
+SISLPHex,Unknown,1,0,0,0,1
+STSLPHex,Unknown,1,0,0,0,1
+CSPHex,Unknown,2,0,0,0,2
+BRSPHex,Unknown,2,0,0,0,2
+CASPHex,Unknown,2,0,0,0,2
+SISPHex,Unknown,2,0,0,0,2
+STSPHex,Unknown,2,0,0,0,2
+SSulfate,Sterol Lipids,0,0,0,0,0
+BAHex,Sterol Lipids,0,0,0,0,0
+BASulfate,Sterol Lipids,0,0,0,0,0
+LCAE,Sterol Lipids,1,0,0,0,1
+KLCAE,Sterol Lipids,1,0,0,0,1
+KDCAE,Sterol Lipids,1,0,0,0,1
+MMPE,Glycerophospholipids,2,0,0,0,2
+DMPE,Glycerophospholipids,2,0,0,0,2
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+        "id" : "2804",
+        "source" : "2271",
+        "target" : "1900",
+        "shared_name" : "LPE (interacts with) Node1",
+        "name" : "LPE (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2804,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "9726",
+        "source" : "2238",
+        "target" : "9712",
+        "shared_name" : "PC (interacts with) Node1",
+        "name" : "PC (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 9726,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2800",
+        "source" : "2238",
+        "target" : "2205",
+        "shared_name" : "PC (interacts with) LPC",
+        "name" : "PC (interacts with) LPC",
+        "interaction" : "interacts with",
+        "SUID" : 2800,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2798",
+        "source" : "2205",
+        "target" : "1844",
+        "shared_name" : "LPC (interacts with) Node1",
+        "name" : "LPC (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2798,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2796",
+        "source" : "2164",
+        "target" : "2162",
+        "shared_name" : "Group1 (interacts with) Node1",
+        "name" : "Group1 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2796,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2794",
+        "source" : "2118",
+        "target" : "2116",
+        "shared_name" : "Group2 (interacts with) Node1",
+        "name" : "Group2 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2794,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2792",
+        "source" : "2096",
+        "target" : "2094",
+        "shared_name" : "LCCAT1 (interacts with) Node1",
+        "name" : "LCCAT1 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2792,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2790",
+        "source" : "2094",
+        "target" : "2469",
+        "shared_name" : "Node1 (interacts with) CL",
+        "name" : "Node1 (interacts with) CL",
+        "interaction" : "interacts with",
+        "SUID" : 2790,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2788",
+        "source" : "2045",
+        "target" : "2043",
+        "shared_name" : "Group3 (interacts with) Node1",
+        "name" : "Group3 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2788,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2786",
+        "source" : "2043",
+        "target" : "2502",
+        "shared_name" : "Node1 (interacts with) PG",
+        "name" : "Node1 (interacts with) PG",
+        "interaction" : "interacts with",
+        "SUID" : 2786,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2784",
+        "source" : "1999",
+        "target" : "1997",
+        "shared_name" : "Group4 (interacts with) Node1",
+        "name" : "Group4 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2784,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2782",
+        "source" : "1997",
+        "target" : "2535",
+        "shared_name" : "Node1 (interacts with) PI",
+        "name" : "Node1 (interacts with) PI",
+        "interaction" : "interacts with",
+        "SUID" : 2782,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2780",
+        "source" : "1953",
+        "target" : "1951",
+        "shared_name" : "Group5 (interacts with) Node1",
+        "name" : "Group5 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2780,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2778",
+        "source" : "1951",
+        "target" : "2568",
+        "shared_name" : "Node1 (interacts with) PS",
+        "name" : "Node1 (interacts with) PS",
+        "interaction" : "interacts with",
+        "SUID" : 2778,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2776",
+        "source" : "1902",
+        "target" : "1900",
+        "shared_name" : "Group6 (interacts with) Node1",
+        "name" : "Group6 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2776,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2774",
+        "source" : "1900",
+        "target" : "2304",
+        "shared_name" : "Node1 (interacts with) PE",
+        "name" : "Node1 (interacts with) PE",
+        "interaction" : "interacts with",
+        "SUID" : 2774,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2772",
+        "source" : "1846",
+        "target" : "1844",
+        "shared_name" : "Group7 (interacts with) Node1",
+        "name" : "Group7 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2772,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2770",
+        "source" : "1844",
+        "target" : "2238",
+        "shared_name" : "Node1 (interacts with) PC",
+        "name" : "Node1 (interacts with) PC",
+        "interaction" : "interacts with",
+        "SUID" : 2770,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    }, {
+      "data" : {
+        "id" : "2768",
+        "source" : "1842",
+        "target" : "1840",
+        "shared_name" : "Node1 (interacts with) Node1",
+        "name" : "Node1 (interacts with) Node1",
+        "interaction" : "interacts with",
+        "SUID" : 2768,
+        "shared_interaction" : "interacts with",
+        "selected" : false
+      },
+      "selected" : false
+    } ]
+  }
+}

app/data/styles.xml

@@ -0,0 +1,142 @@
+<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
+<vizmap id="VizMap-2024_08_27-19_52" documentVersion="3.1">
+    <visualStyle name="default_1_0">
+        <network>
+            <visualProperty default="true" name="NETWORK_EDGE_SELECTION"/>
+            <visualProperty default="550.0" name="NETWORK_SIZE"/>
+            <visualProperty default="false" name="NETWORK_NODE_LABEL_SELECTION"/>
+            <visualProperty default="0.0" name="NETWORK_DEPTH"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_Y_LOCATION"/>
+            <visualProperty default="true" name="NETWORK_NODE_SELECTION"/>
+            <visualProperty default="550.0" name="NETWORK_WIDTH"/>
+            <visualProperty default="false" name="NETWORK_FORCE_HIGH_DETAIL"/>
+            <visualProperty default="false" name="NETWORK_ANNOTATION_SELECTION"/>
+            <visualProperty default="#FFFFFF" name="NETWORK_BACKGROUND_PAINT"/>
+            <visualProperty default="1.0" name="NETWORK_SCALE_FACTOR"/>
+            <visualProperty default="400.0" name="NETWORK_HEIGHT"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_Z_LOCATION"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_X_LOCATION"/>
+            <visualProperty default="" name="NETWORK_TITLE"/>
+        </network>
+        <node>
+            <dependency value="true" name="nodeCustomGraphicsSizeSync"/>
+            <dependency value="false" name="nodeSizeLocked"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_9"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_9, name=Node Custom Paint 9)" name="NODE_CUSTOMPAINT_9"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_3"/>
+            <visualProperty default="SansSerif.plain,plain,12" name="NODE_LABEL_FONT_FACE"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_6, name=Node Custom Paint 6)" name="NODE_CUSTOMPAINT_6"/>
+            <visualProperty default="RECTANGLE" name="NODE_SHAPE"/>
+            <visualProperty default="NONE" name="NODE_LABEL_BACKGROUND_SHAPE"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_7"/>
+            <visualProperty default="15" name="NODE_LABEL_FONT_SIZE"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_7"/>
+            <visualProperty default="255" name="NODE_TRANSPARENCY"/>
+            <visualProperty default="#F7FCF5" name="NODE_FILL_COLOR"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_6"/>
+            <visualProperty default="200.0" name="NODE_LABEL_WIDTH"/>
+            <visualProperty default="ROUND_RECTANGLE" name="COMPOUND_NODE_SHAPE"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_4"/>
+            <visualProperty default="0.0" name="NODE_Y_LOCATION"/>
+            <visualProperty default="5.0" name="NODE_BORDER_WIDTH"/>
+            <visualProperty default="#252525" name="NODE_BORDER_PAINT"/>
+            <visualProperty default="#1E90FF" name="NODE_PAINT"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_5, name=Node Custom Paint 5)" name="NODE_CUSTOMPAINT_5"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_4"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_6"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_3"/>
+            <visualProperty default="140.0" name="NODE_HEIGHT">
+                <passthroughMapping attributeName="Height" attributeType="float"/>
+            </visualProperty>
+            <visualProperty default="35.0" name="NODE_SIZE"/>
+            <visualProperty default="0.0" name="NODE_DEPTH"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_7"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_2"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_6"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_4"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_9"/>
+            <visualProperty default="255" name="NODE_BORDER_TRANSPARENCY"/>
+            <visualProperty default="140.0" name="NODE_WIDTH">
+                <passthroughMapping attributeName="Width" attributeType="float"/>
+            </visualProperty>
+            <visualProperty default="" name="NODE_TOOLTIP"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_2, name=Node Custom Paint 2)" name="NODE_CUSTOMPAINT_2"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_1">
+                <passthroughMapping attributeName="path" attributeType="string"/>
+            </visualProperty>
+            <visualProperty default="#B6B6B6" name="NODE_LABEL_BACKGROUND_COLOR"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_8"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_8"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_5"/>
+            <visualProperty default="SOLID" name="NODE_BORDER_STROKE"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_7, name=Node Custom Paint 7)" name="NODE_CUSTOMPAINT_7"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_3"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_5"/>
+            <visualProperty default="255" name="NODE_LABEL_BACKGROUND_TRANSPARENCY"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_3, name=Node Custom Paint 3)" name="NODE_CUSTOMPAINT_3"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_1, name=Node Custom Paint 1)" name="NODE_CUSTOMPAINT_1"/>
+            <visualProperty default="10.0" name="COMPOUND_NODE_PADDING"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_5"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_8, name=Node Custom Paint 8)" name="NODE_CUSTOMPAINT_8"/>
+            <visualProperty default="#FFFF00" name="NODE_SELECTED_PAINT"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_8"/>
+            <visualProperty default="DefaultVisualizableVisualProperty(id=NODE_CUSTOMPAINT_4, name=Node Custom Paint 4)" name="NODE_CUSTOMPAINT_4"/>
+            <visualProperty default="0.0" name="NODE_X_LOCATION"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_1"/>
+            <visualProperty default="255" name="NODE_LABEL_TRANSPARENCY"/>
+            <visualProperty default="true" name="NODE_NESTED_NETWORK_IMAGE_VISIBLE"/>
+            <visualProperty default="false" name="NODE_SELECTED"/>
+            <visualProperty default="#000000" name="NODE_LABEL_COLOR"/>
+            <visualProperty default="N,N,c,0.00,0.00" name="NODE_LABEL_POSITION"/>
+            <visualProperty default="50.0" name="NODE_CUSTOMGRAPHICS_SIZE_2"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_9"/>
+            <visualProperty default="true" name="NODE_VISIBLE"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_1"/>
+            <visualProperty default="0.0" name="NODE_LABEL_ROTATION"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_2"/>
+            <visualProperty default="" name="NODE_LABEL">
+                <passthroughMapping attributeName="label" attributeType="string"/>
+            </visualProperty>
+            <visualProperty default="0.0" name="NODE_Z_LOCATION"/>
+        </node>
+        <edge>
+            <dependency value="false" name="arrowColorMatchesEdge"/>
+            <visualProperty default="2.0" name="EDGE_WIDTH"/>
+            <visualProperty default="" name="EDGE_LABEL"/>
+            <visualProperty default="#FF0000" name="EDGE_SELECTED_PAINT"/>
+            <visualProperty default="#FF0000" name="EDGE_STROKE_SELECTED_PAINT"/>
+            <visualProperty default="" name="EDGE_BEND"/>
+            <visualProperty default="#FFFF00" name="EDGE_TARGET_ARROW_SELECTED_PAINT"/>
+            <visualProperty default="0.5" name="EDGE_STACKING_DENSITY"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="EDGE_LABEL_POSITION"/>
+            <visualProperty default="0.0" name="EDGE_LABEL_ROTATION"/>
+            <visualProperty default="6.0" name="EDGE_TARGET_ARROW_SIZE"/>
+            <visualProperty default="NONE" name="EDGE_SOURCE_ARROW_SHAPE"/>
+            <visualProperty default="#B6B6B6" name="EDGE_LABEL_BACKGROUND_COLOR"/>
+            <visualProperty default="#000000" name="EDGE_TARGET_ARROW_UNSELECTED_PAINT"/>
+            <visualProperty default="#323232" name="EDGE_PAINT"/>
+            <visualProperty default="false" name="EDGE_LABEL_AUTOROTATE"/>
+            <visualProperty default="AUTO_BEND" name="EDGE_STACKING"/>
+            <visualProperty default="#848484" name="EDGE_STROKE_UNSELECTED_PAINT"/>
+            <visualProperty default="255" name="EDGE_LABEL_BACKGROUND_TRANSPARENCY"/>
+            <visualProperty default="#000000" name="EDGE_SOURCE_ARROW_UNSELECTED_PAINT"/>
+            <visualProperty default="#404040" name="EDGE_UNSELECTED_PAINT"/>
+            <visualProperty default="10" name="EDGE_LABEL_FONT_SIZE"/>
+            <visualProperty default="0.0" name="EDGE_Z_ORDER"/>
+            <visualProperty default="6.0" name="EDGE_SOURCE_ARROW_SIZE"/>
+            <visualProperty default="true" name="EDGE_VISIBLE"/>
+            <visualProperty default="Dialog.plain,plain,10" name="EDGE_LABEL_FONT_FACE"/>
+            <visualProperty default="NONE" name="EDGE_LABEL_BACKGROUND_SHAPE"/>
+            <visualProperty default="SOLID" name="EDGE_LINE_TYPE"/>
+            <visualProperty default="200.0" name="EDGE_LABEL_WIDTH"/>
+            <visualProperty default="#000000" name="EDGE_LABEL_COLOR"/>
+            <visualProperty default="true" name="EDGE_CURVED"/>
+            <visualProperty default="" name="EDGE_TOOLTIP"/>
+            <visualProperty default="255" name="EDGE_TRANSPARENCY"/>
+            <visualProperty default="#FFFF00" name="EDGE_SOURCE_ARROW_SELECTED_PAINT"/>
+            <visualProperty default="255" name="EDGE_LABEL_TRANSPARENCY"/>
+            <visualProperty default="NONE" name="EDGE_TARGET_ARROW_SHAPE"/>
+            <visualProperty default="false" name="EDGE_SELECTED"/>
+        </edge>
+    </visualStyle>
+</vizmap>

app/plumber.R

@@ -0,0 +1,48 @@
+
+library(plumber)
+
+
+# Title
+#* @apiTitle resr4cyjs
+# Description
+#* @apiDescription This is a resr4cyjs API.
+# Version
+#* @apiVersion 0.0.1
+# Tag Description
+#* @apiTag resr4cyjs "resr4cyjs API"
+
+
+#* @filter cors
+cors <- function(req, res) {
+  res$setHeader("Access-Control-Allow-Origin", "*")
+  if (req$REQUEST_METHOD == "OPTIONS") {
+   res$setHeader("Access-Control-Allow-Methods", "GET")
+    res$setHeader(
+      "Access-Control-Allow-Headers",
+      req$HTTP_ACCESS_CONTROL_REQUEST_HEADERS
+    )
+   res$status <- 200
+   return(list())
+  } else {
+    plumber::forward()
+  }
+}
+
+
+
+#* @serializer contentType list(type="image/svg+xml")
+#* @get /plot
+#* @arg str1
+function(str1) {
+  thefolder <- "/srv/app/svg/"
+  svg_file_path <- paste(thefolder,str1,sep = "")
+  if(file.exists(svg_file_path) == TRUE){
+  readBin(svg_file_path, "raw", file.info(svg_file_path)$size)}
+  else{
+    svg_file_path <- "/srv/app/www/background.svg"
+    readBin(svg_file_path, "raw", file.info(svg_file_path)$size)
+  }
+}
+
+
+

app/server.R

@@ -0,0 +1,445 @@
+server <- function(input, output,session) {
+  options(shiny.maxRequestSize=150*1024^2)
+  originaldir <- reactiveValues(datapath = getwd()) # directry of shiny R script
+  global <- reactiveValues(datapath = getwd()) # directory of file path in lipidomics tab
+  col = reactiveValues(col = col)
+  svg_path <- paste(getwd(),"/svg",sep = "")
+
+    observeEvent(input$filetype,{
+    if(input$filetype =="Sample in rows"){
+      shinyjs::show("ontfile")
+    }else{
+      shinyjs::hide("ontfile")
+    }
+	if(input$ClassorMol =="TRUE"){
+      shinyjs::show("X1")
+	  shinyjs::show("X2")
+    }else{
+      shinyjs::hide("X1")
+	  shinyjs::hide("X2")
+    }
+	})
+	
+	observeEvent(input$ClassorMol,{
+	if(input$ClassorMol =="TRUE"){
+      shinyjs::show("X1")
+	  shinyjs::show("X2")
+    }else{
+      shinyjs::hide("X1")
+	  shinyjs::hide("X2")
+    }
+	})
+	
+ observeEvent(input$file1, {	
+ tryCatch({
+    originaldata <- read.csv(input$file1$datapath, header = F, check.names = F, fileEncoding = "UTF-8-BOM")
+  }, error = function(e) {
+    showNotification(paste("Failed to load the file", e$message), type = "error")
+  })
+	observeEvent(input$submit,{
+  tryCatch({
+  if(input$filetype == "Sample in rows"){
+    
+    Lipidomedata <- processSampleInRows(originaldata, session, input)[[1]]
+    lipidont <- read.csv(input$ontfile$datapath, sep = ",", check.names = FALSE)
+    metadata <- processSampleInRows(originaldata, session, input)[[2]]
+    alitable <- read.csv(input$ontfile$datapath, check.names = FALSE, fileEncoding = "UTF-8-BOM")
+    colnames(alitable) <- c("Metabolite name","Ontology")
+    letchoice <- c(colnames(Lipidomedata)[!colnames(Lipidomedata) %in% colnames(metadata)],"Others")
+    moldata <- processSampleInRowstomoldata(originaldata, session, input)[[1]]
+  }else if(input$filetype == "MS-DIAL export"){
+  Lipidomedata <- processMSDIALExport(originaldata, session, input)[[1]]
+  metadata <- processMSDIALExport(originaldata, session, input)[[2]]
+  alitable <- process_alignment_file(originaldata)[[1]] %>% select(c(1,2))
+  moldata <- processMSDIALExporttomoldata(originaldata, session, input)[[1]] 
+  }
+  if(length(input$transcriptomefile) !=0){
+    transcriptome <- read.csv(input$transcriptomefile$datapath,check.names = F,fileEncoding ="UTF-8-BOM") %>% t()
+    colnames(transcriptome) <- transcriptome[1,]
+    transcriptome <- transcriptome[-1,] %>% data.frame()
+    transcriptome[,-c(1)] <- apply(transcriptome[,-c(1)],2,as.numeric) %>% data.frame()
+    transcriptome <-  rownames_to_column(transcriptome,"name")
+    transcriptome[,2] <- as.character(transcriptome[,2])
+  }
+  
+  if(length(input$file1) !=0 & length(input$transcriptomefile) != 0){
+    
+    Ensembl <- gconvert(query = colnames(transcriptome)[-c(1:2)] , organism = "mmusculus",#sapiens
+                       target="ENSG", mthreshold = Inf, filter_na = TRUE) %>% select(input,target)
+    transcriptome <- transcriptome %>% select(-2)
+    data <- inner_join(Lipidomedata,transcriptome,by =c("name"))
+	moldata <- inner_join(moldata,transcriptome,by =c("name"))
+  }
+  else{
+    data <- Lipidomedata
+  }
+  }, error = function(e) {
+    showNotification(paste("Error:Invalid CSV file format. Please ensure your file is a properly formatted CSV.", e$message), type = "error")
+  })
+  
+  metainfocol <- ncol(metadata)
+  lipidclassproperties <- read_csv("./pathwaymap/lipidclassproperties.csv")
+  
+  processAndUpdateInputs(data, session, metadata, metainfocol)
+  processAndUpdateInputs2(moldata, session, metadata, metainfocol)
+  observeEvent(input$y,{
+    targetclass <- filter(alitable,Ontology %in% input$y)
+    shiny::updateSelectInput(session, "mol", selected = targetclass$`Metabolite name`[1], choices = targetclass$`Metabolite name`)
+  })
+
+  shinyjs::onclick(id = "Colorpicker",{
+    ShowtestModaldialog(data,input,col$col)
+  }
+  )
+  shinyjs::onclick(id = "exportgraph",{
+    ShowtestModaldialog2(data,input,col$col)
+  }
+  )
+
+  observeEvent(input$w,{
+    updateOrderInput(session, "levels",
+                     items = c(unique(as.matrix(select(data,input$w)))),
+                     item_class = "success")
+    shiny::updateSelectInput(session, "q", selected = c(unique(as.matrix(select(data,input$w))))[1], choices = c(unique(as.matrix(select(data,input$w)))))
+    col$col <<- rainbow_hcl(length(unique(as.matrix(select(data,input$w)))))
+    col$col <<- setNames(col$col,unique(as.matrix(select(data,input$w))))
+  })
+  
+  observeEvent(input$levels,{
+    if (!is.null(input$levels) && any(input$levels != "")) {
+      dataa <<- mutate(data, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+      moldataa <<- mutate(moldata, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+      
+    }
+  })
+  
+  observe({
+    if (length(grep("selectcolor", names(input), value = TRUE)) != 0) {
+      col$col <<-  process_select_color_input(input,data)
+    }
+  })
+  
+  observeEvent(input$levels,{
+    observe({
+      if (!is.null(input$mol) && input$mol != "") {
+        if(!is.null(input$levels) && any(input$levels != "")){
+          
+          output$plottest <- renderPlotly({
+            
+            if(input$mydrop == "box"){
+              process_boxplot(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "bar"){
+              process_barplot(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "violin"){
+              process_violinplot(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "polar"){
+              process_polarplot(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "coding"){
+              process_dotplot(input,input$y,dataa,col$col)
+            }
+          }
+          )
+          output$mappingraph <- renderPlot({
+            
+            if(input$mydrop == "box"){
+              process_boxplot_diagram(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "bar"){
+              process_barplot_diagram(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "violin"){
+              process_violinplot_diagram(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "polar"){
+              process_polar_diagram(input,input$y,dataa,col$col)
+            }
+            else if(input$mydrop == "coding"){
+              process_dotplot_diagram(input,input$y,dataa,col$col)
+            }
+          }
+          )
+          
+          observeEvent(input$mol,{
+            
+            output$plottest2 <- renderPlotly({
+              if(input$mydrop == "box"){
+                process_boxplot(input, paste("`",input$mol,"`",sep =""),moldataa,col$col)
+              }
+              else if(input$mydrop == "bar"){
+                process_barplot(input, paste("`",input$mol,"`",sep =""),moldataa,col$col)
+              }
+              else if(input$mydrop == "violin"){
+                process_violinplot(input,paste("`",input$mol,"`",sep =""),moldataa,col$col)
+              }
+              else if(input$mydrop == "polar"){
+                process_polarplot(input,paste("`",input$mol,"`",sep =""),moldataa,col$col)
+              }
+              else if(input$mydrop == "coding"){
+                process_dotplot(input,paste("`",input$mol,"`",sep =""),moldataa,col$col)
+              }
+              
+            })
+          })
+		   }
+      }
+    })
+  })
+  
+  graph_json <- reactive({
+    if (input$pathwaytype == "Global pathway") {
+      read_graph_json("./pathwaymap/globalpathway.cyjs")
+    } else if (input$pathwaytype == "Ceramide pathway") {
+      read_graph_json("./pathwaymap/ceramidepathway.cyjs")
+    } else if (input$pathwaytype == "Remodeling pathway") {
+      read_graph_json("./pathwaymap/remodeling.cyjs")
+    }
+  })
+  
+  style_file_path <- "./pathwaymap/nodestyle1.js"
+  styles_xml_path <- "./pathwaymap/styles.xml"
+  # CYJSファイルのダウンロード
+  output$exportCYJS <- downloadHandler(
+    filename = function() {
+      paste0(input$pathwaytype, "_", format(Sys.Date(), "%Y%m%d"), ".cyjs")
+    },
+    content = function(file) {
+      writeLines(graph_json, file)
+    },
+    contentType = "application/json"
+  )
+  
+  # styles.xmlファイルのダウンロード
+  output$exportStyles <- downloadHandler(
+    filename = function() {
+      "styles.xml"
+    },
+    content = function(file) {
+      file.copy(styles_xml_path, file)
+    },
+    contentType = "application/xml"
+  )
+  #observeEvent(input$sidebarCollapse, {
+  #  toggleClass(id = "content", class = "active")
+  #})
+  
+   observeEvent(input$toggle_sidebar, {
+    shinyjs::runjs("toggleSidebar()")
+  })
+  
+  observeEvent(input$pathway, {
+    output$graphContainer <- renderUI({
+      cyjShinyOutput("cyjShinytest", height = "90%", width = "90%")
+    })
+  })
+          output$cyjShinytest <- renderCyjShiny({
+            #p <- input$pathway           
+            #if (p != 0) {
+              if (input$pathwaytype == "Global pathway") {
+                graph_json <<- paste(readLines("./pathwaymap/globalpathway.cyjs"), collapse = "")
+              } else if (input$pathwaytype == "Ceramide pathway") {
+                graph_json <<- paste(readLines("./pathwaymap/ceramidepathway.cyjs"), collapse = "")    
+              } else if (input$pathwaytype == "Remodeling pathway") {
+                graph_json <<- paste(readLines("./pathwaymap/remodeling.cyjs"), collapse = "")   
+              }
+              
+              test <- fromJSON(graph_json)
+              test <- as.data.frame(test$elements$nodes)
+              
+              if (input$viewacyllevel == TRUE) {
+                cyjShiny(graph_json, layoutName = "preset", styleFile = "./pathwaymap/nodestyle1.js")
+              } else {
+                cyjShiny(graph_json, layoutName = "preset", styleFile = "./pathwaymap/nodestyle2.js")
+              }
+           # } else {
+              
+            #}
+          })
+		  
+		  
+		  
+          observeEvent(input$getSelectedNodes, ignoreInit=TRUE, {
+            output$selectedNodesDisplay <- renderText({" "})
+            getSelectedNodes(session)
+          })
+          
+          
+          output$corselect <- renderPlotly({
+            if(input$pathwaytype == "Global pathway"){
+              graph_json <<- paste(readLines("./pathwaymap/globalpathway.cyjs"), collapse="")
+            }else if(input$pathwaytype == "Ceramide pathway"){
+              graph_json <<- paste(readLines("./pathwaymap/ceramidepathway.cyjs"), collapse="")    
+            }else if(input$pathwaytype == "Remodeling pathway"){
+              graph_json <<- paste(readLines("./pathwaymap/remodeling.cyjs"), collapse="")      
+            }
+            test <- fromJSON(graph_json)
+            test <- as.data.frame(test$elements$nodes)
+            test1 <- test[test$data$id %in% unlist(input$selectedNodes),]
+            dataa <- mutate(data, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+            
+            if(length(test1$data$shared_name) == 2){
+            moldataa <- mutate(moldata, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+            targetclass <- filter(alitable,Ontology %in% test1$data$shared_name)
+              if(! test1$data$shared_name[1] %in% colnames(data)) {
+                a <- Ensembl[Ensembl$target %in% test1$data$Ensembl_ID[1],]
+                test1$data$shared_name[1] <- a$input
+              }
+              if(! test1$data$shared_name[2] %in% colnames(data)) {
+                b <- Ensembl[Ensembl$target %in% test1$data$Ensembl_ID[2],]
+                test1$data$shared_name[2] <- b$input
+              }
+			  if(input$ClassorMol == FALSE){
+			  cor_value <- cor(dataa[,test1$data$shared_name[1]], dataa[,test1$data$shared_name[2]],method = "spearman")
+              g <- ggplot(dataa,aes_string(test1$data$shared_name[1],test1$data$shared_name[2],fill = input$w,size = input$size))+geom_point(shape =21,color = "black")+
+    scale_fill_manual(values = unlist(col$col)) + ggtitle(paste("r = ",round(cor_value, 2)))
+			  }else{
+			  moldataa <- mutate(moldata, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+	cor_value <- cor(moldataa[,input$X1], moldataa[,input$X2],method = "spearman")
+			  g <- ggplot(moldataa,aes_string(paste("`",input$X1,"`",sep =""),paste("`",input$X2,"`",sep =""),fill = input$w,size = input$size))+geom_point(shape =21,color = "black")+
+    scale_fill_manual(values = unlist(col$col))+ ggtitle(paste("r = ",round(cor_value, 2)))
+			  }
+			  plotly::ggplotly(g)
+            }
+            
+          })
+		  output$textOutput <- renderText({
+		  if(input$ClassorMol == FALSE){
+    "Select two nodes from the network to analyze their correlation."}
+	else{
+	"Select two features to analyze their correlation."
+	}
+  })
+		  
+
+
+		  
+		     observeEvent(input$selectedNodes, {
+      if(input$pathwaytype == "Global pathway"){
+        graph_json <<- paste(readLines("./pathwaymap/globalpathway.cyjs"), collapse="")
+      }else if(input$pathwaytype == "Ceramide pathway"){
+        graph_json <<- paste(readLines("./pathwaymap/ceramidepathway.cyjs"), collapse="")    
+      }else if(input$pathwaytype == "Remodeling pathway"){
+        graph_json <<- paste(readLines("./pathwaymap/remodeling.cyjs"), collapse="")      
+      }
+      test <- fromJSON(graph_json)
+      test <- as.data.frame(test$elements$nodes)
+      test1 <- test[test$data$id %in% unlist(input$selectedNodes),]
+      moldataa <- mutate(moldata, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+      targetclass <- filter(alitable,Ontology %in% test1$data$shared_name)
+        shiny::updateSelectInput(session, "selectmol", selected = targetclass$`Metabolite name`[1], choices = targetclass$`Metabolite name`)
+      },ignoreNULL = TRUE)
+	  
+		  output$corselect2 <- renderPlot({
+        if(input$pathwaytype == "Global pathway"){
+          graph_json <<- paste(readLines("./pathwaymap/globalpathway.cyjs"), collapse="")
+        }else if(input$pathwaytype == "Ceramide pathway"){
+          graph_json <<- paste(readLines("./pathwaymap/ceramidepathway.cyjs"), collapse="")    
+        }else if(input$pathwaytype == "Remodeling pathway"){
+          graph_json <<- paste(readLines("./pathwaymap/remodeling.cyjs"), collapse="")      
+        }
+        test <- fromJSON(graph_json)
+        test <- as.data.frame(test$elements$nodes)
+        test1 <- test[test$data$id %in% unlist(input$selectedNodes),]
+        moldataa <- mutate(moldata, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+        targetclass <- filter(alitable,Ontology %in% test1$data$shared_name)
+        if(length(test1$data$shared_name) > 0 && input$selectmol != " "){
+          if(test1$data$shared_name[1] %in% colnames(data)) {
+          if(input$mydrop == "box"){
+			g <- process_boxplot_diagram(input,paste("`",input$selectmol,"`",sep =""),moldataa,col$col)
+          }
+          else if(input$mydrop == "bar"){
+			g <- process_barplot_diagram(input,paste("`",input$selectmol,"`",sep =""),moldataa,col$col)
+          }
+          else if(input$mydrop == "violin"){
+			g <- process_violinplot_diagram(input,paste("`",input$selectmol,"`",sep =""),moldataa,col$col)
+          }
+          else if(input$mydrop == "polar"){
+			g <- process_polar_diagram(input,paste("`",input$selectmol,"`",sep =""),moldataa,col$col)
+          }
+          else if(input$mydrop == "coding"){
+
+			g <- process_dotplot_diagram(input,paste("`",input$selectmol,"`",sep =""),moldataa,col$col)
+          }}
+          plot(g)
+        }
+        
+      })
+          
+
+  observeEvent(input$save_pdf,{
+            shinyscreenshot::screenshot(selector="#cyjShinytest")
+          })
+  #Creating heatmap
+  observeEvent(input$actionplottest, {
+             waiter::waiter_show(
+               id = NULL,
+               html = tagList(waiter::spin_loader(),
+                              "Loading ..."),
+               color = "#333e48",
+               logo = "",
+               image = ""
+             )
+			 file_list <- list.files(svg_path)
+             if (length(unlist(file_list)) > 0) {
+                file.remove(file.path(svg_path, file_list))
+             } else {
+			 }
+            if(is.null(input$transcriptomefile) == FALSE){
+               Ensembl <- gconvert(query = colnames(transcriptome)[-c(1:2)] , organism = "mmusculus",#sapiens
+                                   target="ENSG", mthreshold = Inf, filter_na = TRUE) %>% select(input,target)
+              graph_json1 <- paste(readLines("./pathwaymap/ceramidepathway.cyjs"), collapse="")  %>% fromJSON()
+              graph_json2 <- paste(readLines("./pathwaymap/remodeling.cyjs"), collapse="") %>% fromJSON()
+              Ensemblinmap <- c(graph_json1$elements$nodes$data$Ensembl_ID,graph_json2$elements$nodes$data$Ensembl_ID)
+              Ensemblinmap <- Ensemblinmap[-which(Ensemblinmap %in% "")]
+	
+              geneinmap <- Ensembl[Ensembl[,2] %in% Ensemblinmap,]
+
+              transcriptome2 <- colnames(transcriptome)[colnames(transcriptome) %in% geneinmap$input]
+			  
+              data <- data[,colnames(data) %in% c(colnames(data)[1:metainfocol],colnames(Lipidomedata),transcriptome2)]
+			  dataa <- mutate(data, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+			  names(dataa)[match(geneinmap$input, names(dataa))] <- geneinmap$target
+			  
+			  } else {
+			  dataa <- mutate(data, !!as.symbol(input$w) := !!as.symbol(input$w) %>% factor(levels = input$levels))
+			 }
+            
+           # if (length(grep("selectcolor", names(input), value = TRUE)) != 0) {
+           #   col <<-  process_select_color_input(input,data)
+           # }
+            if(input$mydrop == "box"){
+              process_action_boxplot(input,dataa,metainfocol,svg_path,col$col,output) 
+            }
+            else if(input$mydrop == "bar"){
+              process_action_barplot(input,dataa,metainfocol,svg_path,col$col,output) 
+            }
+            else if(input$mydrop == "violin"){
+              process_action_violinplot(input,dataa,metainfocol,svg_path,col$col,output) 
+            }
+            else if(input$mydrop == "polar"){
+              process_action_polarplot(input,dataa,metainfocol,svg_path,col$col,output) 
+            }
+            else if(input$mydrop == "coding"){
+              process_action_dotplot(input,dataa,metainfocol,svg_path,col$col,output) 
+            }
+            # if(input$filetype == "MS-DIAL export"){
+            #   exportgroupnodeheatmap(originaldata,metadata,paste(global$datapath,"",sep =""),input$w,input$levels,originaldir,input)}
+            Sys.sleep(3)
+             waiter::waiter_hide()
+        }
+          )
+  observeEvent(input$w,{
+   
+  output$heatmap <- renderPlot({
+  if(length(unlist(input$selectedNodes)) > 0 ) {
+        test <- fromJSON(graph_json)
+      test <- as.data.frame(test$elements$nodes)
+      test1 <- test[test$data$id %in% unlist(input$selectedNodes),]
+     groupnodeheatmap(lipidclassproperties,originaldata,metadata,input$w,input$levels,test1$data$shared_name[1],input)
+	 }
+  })
+  })
+} )})}

app/svg/.gitkeep

@@ -0,0 +1 @@
+

app/ui.R

@@ -0,0 +1,214 @@
+source("./modules/librarys.R")
+source("./modules/data_processing.R")
+source("./modules/plot_utils.R")
+source("./modules/heatmap_utils.R")
+source("./modules/modaldialog_utils.R")
+source("./modules/selectcolor_utils.R")
+source("./modules/ui_modules.R")
+
+shinyUI(
+  fluidPage(
+    useShinyjs(),
+    tags$head(
+      tags$style(HTML(
+        "
+        .well { background-color: initial; border: initial; }
+        .navbar { margin-bottom: 5px; }
+        .container-fluid { padding-right: 10px; padding-left: 10px; }
+        #sidebar {
+          position: fixed;
+          left: 0;
+          width: 250px;
+          height: calc(100% - 160px);  
+          top: 160px;  
+          background: #f8f9fa;
+          transition: all 0.3s;
+          padding: 15px;
+          z-index: 1000;
+        }
+        #sidebar.inactive {
+          left: -250px;
+        }
+		#content {
+        margin-left: 60px;
+        transition: all 0.3s;
+        height: calc(100vh - 50px);
+      }
+	  #content.active {
+        margin-left: 310px;
+      }
+        #main-content {
+          margin-left: 250px;
+          transition: all 0.3s;
+          padding-top: 80px;  
+        }
+        #main-content.inactive {
+          margin-left: 0;
+        }
+        #toggle_sidebar {
+          position: fixed;
+          left: 260px;
+          top: 160px;  
+          z-index: 1001;
+          width: 40px;
+          height: 40px;
+          background: #343a40;
+          color: #fff;
+          border: none;
+          border-radius: 5px;
+          transition: all 0.3s;
+        }
+        #toggle_sidebar.inactive {
+          left: 10px;
+        }
+        #graphContainer {
+          height: 100%;
+          width: 100%;
+        }
+        #tab3 {
+          margin-top: 70px;
+        }
+        "
+      ))
+    ),
+    navbarPage(
+      "MSDIAL2Cytoscape",
+      theme = shinytheme("yeti"),
+      tabPanel(
+        waiter::useWaiter(),
+        uiOutput("dynamicSidebar"),
+        uiOutput("dynamicSidebarToggle"),
+        tabsetPanel(
+          id = "mainTabs",
+          uploadpanel,
+          tabPanel(
+            value = "tab2",
+              tagList(
+    div(
+      style = "display: flex; align-items: center; justify-content: center; margin-bottom: 15px;",
+      img(src = "./barplot.png", style = "width: 50px; height: 50px; margin-right: 10px;"),
+      div(style = "font-size: 18px; color: #000000; font-weight: bold;", "Plot")
+    )
+  ),
+            fluidRow(
+              column(
+                width = 12,
+				createCustomSidebar("y", "w", "z", "alpha", "size", "Fontsize", "levels", "pvaluecheck", "q"),
+                plotTabAppearanceUI(
+                  "", "./bar.png", "50px", "50px", "plottest", "plottest2", "testtext"
+                )
+              )
+            )
+          ),
+          tabPanel(
+  value = "tab3",   
+
+    tagList(
+    div(
+      style = "display: flex; align-items: center; justify-content: center; margin-bottom: 15px;",
+      img(src = "./network2.png", style = "width: 50px; height: 50px; margin-right: 10px;"),
+      div(style = "font-size: 18px; color: #000000; font-weight: bold;", "Pathway analysis")
+    )
+  ),
+
+ actionButton("toggle_sidebar", icon("bars"), class = "btn-info"), 
+
+    div(
+      id = "sidebar",
+      wellPanel(
+        id = "pathway-controls",
+        selectInput("pathwaytype", "Pathway type", 
+                    choices = c("Global pathway", "Ceramide pathway", "Remodeling pathway"), 
+                    selected = "Global pathway"),
+        actionButton("pathway", "Pathway mapping", class = "btn-primary btn-block"),
+        actionButton("save_pdf", "Save as PNG", class = "btn-success btn-block"),
+        downloadButton("exportCYJS", "Export CYJS", class = "btn-block"),
+        downloadButton("exportStyles", "Export styles.xml", class = "btn-block"),
+        checkboxInput("viewacyllevel", "Close-up nodes", value = TRUE)
+      )
+    ),
+        div(
+      id = "main-content",
+      fluidRow(
+        column(
+          width = 9,
+          div(id = "content", 
+              uiOutput("graphContainer")
+          )
+        ),
+        column(
+  width = 3,
+
+  actionButton("getSelectedNodes", "Click nodes in the Network and Confirm Selection", class = "btn-primary btn-block"),
+  br(), 
+  tabsetPanel(
+    id = "sideTabset",
+    tabPanel("Lipid Species Visualization",
+      div(id = "tabContent",
+	  wellPanel(
+        selectInput(
+          inputId = "selectmol",
+          label = "Select molecule to display",
+          choices = c(" "),
+          selected = " "
+        ),
+        plotOutput(outputId = "corselect2")),
+		wellPanel(
+		plotOutput(outputId = "heatmap",height = "600px" ,width = "100%"),
+        checkboxInput(inputId = "acylfilter", label = "Filtering common acylchains (16:0, 16:1, 18:0, 18:1, 18:2, 18:3, 20:3, 20:4, 20:5, 22:4, 22:5, 22:6)", value = TRUE),
+        checkboxInput(inputId = "sn", label = "sn", value = FALSE))
+      )
+    ),
+    tabPanel("Correlation Plot",
+      div(id = "tabContent",
+	  wellPanel(
+	  textOutput("textOutput"), 
+	  br(),
+	  plotlyOutput(outputId = "corselect")),
+        checkboxInput(inputId = "ClassorMol", label = "Correlation of lipid species", value = FALSE),
+        selectInput(
+          inputId = "X1",
+          label = "X",
+          choices = c(" "),
+          selected = " "
+        ),
+        selectInput(
+          inputId = "X2",
+          label = "Y",
+          choices = c(" "),
+          selected = " "
+        )
+      )
+    )
+  )
+)
+      )
+    ),
+    tags$script(HTML(
+      "
+      function toggleSidebar() {
+        var sidebar = $('#sidebar');
+        var mainContent = $('#main-content');
+        var toggleBtn = $('#toggle_sidebar');
+        
+        sidebar.toggleClass('inactive');
+        mainContent.toggleClass('inactive');
+        toggleBtn.toggleClass('inactive');
+        
+        if (sidebar.hasClass('inactive')) {
+          toggleBtn.find('i').removeClass('fa-times').addClass('fa-bars');
+        } else {
+          toggleBtn.find('i').removeClass('fa-bars').addClass('fa-times');
+        }
+      }
+      "
+    ))
+)
+        )
+      )
+    )
+  )
+)
+
+
+

scripts/start.sh

@@ -0,0 +1,5 @@
+R -e "library(dplyr)"
+
+R -e "plumber::pr_run(plumber::pr('/srv/app/plumber.R'), port=9000, host='0.0.0.0')" &
+
+R -e "shiny::runApp('/srv/app', host='0.0.0.0', port=1028)"