sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
ccdb1a622f7729ad352f05e74c9be58fe6f778733ab51eadb168ed35a7abc85c | R | 24,713 | 715 | rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
library(magrittr)
library(harmony)
library(R... |
00bb0508aae323dbae1e65fc02ea1866a6d6d22d43bb1dee8271736b9e789294 | R | 24,715 | 718 | rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
library(magrittr)
library(harmony)
library(R... |
4d9424d1a7259334340989c0329a5c97fe70ad82b64e408617526bb5b6bd20e4 | R | 24,800 | 732 | # Calculate average channel intensity per sample
# Input data:
# - area_measurement.csv (SIMPLI output)
#### 0. Load libraries ####
library(stringr)
library(tidyverse)
library(plyr)
library(readr)
library(stringr)
#install.packages("rqdatatable")
library(rqdatatable)
library(dplyr)
#library(ggExtra)
library(gridEx... |
b432b2a4909be8bf27750e175b94a1677f3d28b709d34f7b9503f3dfebbafb75 | R | 24,823 | 504 | #Example code: Exploring a Dataset (with more detail)
#Megan Hagenauer
#July 13, 2023
##################################
#This code document is set up to provide an example of analyzing a single Gemma dataset
#It combines many elements that we've already talked about.
#To keep things neat and tidy, I'm only analyzing... |
758213cd03f833e50025ba877bc25843b26ffcb999eaa25a412b12d9c984f6a8 | R | 25,026 | 783 | #' assess the classifiers performance based on validation data
#' @param stDat sample table
#' @param expDat normalized expression matrix
#' @param nimCells the minimal number of cells one would like to have in each cell type
#' @param dThresh detection threshold
#' @param propTrain the proportion of the training... |
b58c1374abff684678924dcecb563e31d4bf7c69d5f4800eb7687c96211a6214 | R | 25,247 | 582 | rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
library(doubletFinder)
library(harmony)
libr... |
6fc3a60434825189c0f736739725ed8e5da707dc28e3a3fa889ebdfd0ee4946b | R | 25,465 | 561 | ---
title: "Compare read and molecule counts in single cells per batch"
author: "PoYuan Tung & Joyce Hsiao"
date: 2015-09-22
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache ... |
48739d27d92851242b370a3b163e02b26c3e53ae4918bbad62219a0a940dba66 | R | 25,737 | 612 | #######################################################
### Goal: Try PLSR with plsRglm
### Author: Janay Fox
### R script
#######################################################
## Set up ##
#install packages
#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages("methylKit")
#install.packages(lme4... |
cabdd185c0e81feee43bbf31fac60c14e326dfcc98660a45c722cfe81e89107d | R | 25,810 | 573 | ---
title: "QC of single cell libraries"
author: "PoYuan Tung"
date: 2015-10-23
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(fig.width = 8, fig.height = 8)
```
## Input
```{r... |
3a109a2930f4c489b28b48a3220a32d3f04d9e3cbae60c724f09c64daa5a941e | R | 26,007 | 786 | ---
title: "Additional analysis for the manuscript"
date: 2016-06-23
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(fig.width = 8, fig.height = 8)
```
```{r packages, message=F... |
94bc9ff65dd578fe35a95a026c32f9e9ccf67980c813c8e6c8f8ef10029c78d2 | R | 26,199 | 450 | ##
## Global differential expression analysis (DEA) ##
##
library(Seurat) # SeuratObject_4.1.4 Seurat_4.3.0
library(openxlsx) # openxlsx_4.2.5.2
library(ggplot2) # ggplot2_3.5.1
set.seed(1)
load("./data/sctrans2.RData")
# Set sample identities to celltype/condition combinations
orig.ident <- sctrans2$orig.ident
sctr... |
4beef0ea64f6944be6687969cfe1b6f6e0d7b9e97dcec22efaf1ed6f6219f6b7 | R | 26,352 | 664 | source("mouse global.R", local = TRUE)
header <- function(){
dashboardHeader(title = "Welcome to GD-CAT!")
}
sidebar <- function(){
dashboardSidebar(
sidebarMenu(
id = "tabs",
class= "hide",
menuItem("Instruction", tabName = "t2",icon = icon("dashboard")),
menuItem("Settin... |
1a812ae84ea0d26efe8eda32a242de23a1feae8eddd1335d77281ded36dc617f | R | 26,466 | 488 | #' Estimate the effectize sample size
#'
#' @param plinkFile character. Path to plink file to be used for calculating elements of the genetic relationship matrix (GRM). minMAFforGRM can be used to specify the minimum MAF of markers in he plink file to be used for constructing GRM. Genetic markers are also randomly sel... |
de27eb5b5fec11eff07efa89a41bc24e7724ef5c42fefb94f33eaa967d00de99 | R | 26,542 | 849 |
#'@exports
#'@title MultiExpMLR
#'@description run a multiple linear regression on the differential expression
#'analysis.
#'@param me an object of class multiexperiment
#'@param features a dataframe containing the features of interests, it must contain
#'a the keys of the MultiExperiment of interest.
#'@param us... |
b73034d3c5a8a1ed6e59f44ca47870f5cf0b4f9614100431b2d8225ba108dcf6 | R | 26,614 | 534 | ```{r}
library(dplyr)
library(Timecourse)
library(simspec)
library(destiny)
library(ggplot2)
library(MetBrewer)
library(simspec)
library(tidyverse)
library(Seurat)
library(MetBrewer)
```
```{r}
setwd("~/polybox/Jain_Gut_et_al_2023/Timecourse")
Timecourse <- readRDS("Timecourse.rds")
p1 <- UMAPPlot(Timecourse, group... |
aaf8f1572e0629ba9c84977b6edca043b7b8573eed279006b4e0c82d832ed132 | R | 26,633 | 541 | #Example code: Exploring a Dataset (with more detail)
#Megan Hagenauer
#July 13, 2023
##################################
#This code document is set up to provide an example of analyzing a single Gemma dataset
#It combines many elements that we've already talked about.
#To keep things neat and tidy, I'm only analyzing... |
04d7d0caf7a16b2c6d078d176f956e03a572e19fe31a278c3dfe7cf13a0bfbe3 | R | 26,742 | 798 | ---
title: "Translation Initiation"
author: "Di Fraia"
date: "2023-01-20"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Set Theme
```{r}
#Create all the colors
col_code <- c("Transcriptome"="#377EB8","Proteome"="#E41A1C",
"Transl.Eff (TE)"= "#984EA3")... |
c44a9309d45ad0ea8e0e3ff5388bd51728a248a079c3cfd4685798fd54212ee7 | R | 26,783 | 525 | ### Loads the data and creates data frames for the analysis ###
fpath <- paste(getwd(),"/Parkinson-UPDRS-TMS-cohort-main/data_UDPRS_TMS/",sep = "")
RCtable <- read.table(file = paste(fpath,"IOCurves.csv",sep = ""), sep = ",", header = TRUE)
RCtable$Period <- factor(RCtable$Period)
RCtable$ID <- factor(RCtable$ID)
RCtab... |
0b2a47b4cda044ddde8eddadd22ed00e6565070a07c3a8bf92db80a83fff097b | R | 26,885 | 598 | ################################################################################
#################### EMA Microglia Bulk RNA-seq ###############################
################################################################################
setwd("~/Dropbox/2023_EMA_Manuscript/Analyses/June2023")
options(stringsAsFa... |
b073a02788337123037874bb4857da4c265ad4aa59fa8384435381739f37ef3c | R | 27,062 | 289 | ---
bibliography: refs.bib
---
```{r chunk-options, include=FALSE}
source("chunk-options-paper.R")
```
## Methods
### Ethics statement
The YRI cell lines were purchased from CCR.
The original samples were collected by the HapMap project between 2001-2005.
All of the samples were collected with extensive community e... |
f869e59308b2c464a72ba687744218c150badcfaf37a2b464a9a65cb532e8cdf | R | 27,083 | 790 | # Functions
# ------------------ The function GPCor is for calculating the correlation of gene-peak pairs
############## INPUT: 1. peak-cell matrix; 2. scRNA-seq matrix or gene activity matrix; 3. reference genome in Granges form
############## OUTPUT: A dataframe of peak-gene correlation
GPCor <- function(cre.mat=cre.... |
a22388d443e31a774f7ad06afc819e1bd051c59d62e69020192ff48bd14c7824 | R | 27,258 | 702 | ---
title: "Harris October 2024 scRNA-seq Ascl1 NSCs"
subtitle: "Pseudobulk differential expression analysis"
author: "Rebecca Johnston and Lachlan Harris"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r original-data-directory}
#... |
d139cd26ef5aa2ef60b54236b399a1eaef8cc3ce0c95d7026884d34c68d948ac | R | 27,327 | 883 | # some useful functions
# --- (2) --- child_node ----------------------------------------------------------------------------------
#' find child nodes
#'
#' Extract all nodes of a neuron \code{xneu} downstream of a node(s) \code{xroot}
#' @param xneu a nat neuron
#' @param xroot a dataframe of nodes
#'
#' @return a... |
e84f7a0ad641033306ee273bef2cee691da0366c8c3dcbef7112b65b5caac2d7 | R | 27,338 | 732 | ---
title: "Casp1Aldh1l1_scRNAseq_reviewers"
author: "Kristine Zengeler"
date: "2024-06-27"
output: pdf_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Load libraries
```{r}
library(Seurat)
library(tidyverse)
library(Matrix)
library(scales)
library(cowplot)
library(RCurl)
library(g... |
3ee0378fc487ee899c9a43dab5a77ccb912cb025b8672a49e135b228799dc6b7 | R | 27,347 | 800 | ---
title: "Clustered heatmap of Cryptococcus Wakeup RNAseq timecourse"
author: "Edward Wallace"
date: "2022-11-22"
output:
html_document:
toc: true
---
# Summary
Clustered heatmap of Cryptococcus Wakeup RNAseq timecourse
This analysis does:
- EDIT
It concludes that... EDIT
## Load count data from shared ... |
2618541f0d84051747181e7b1f7ab607a0d6fbae7460ab1648e09a4de9f2a86f | R | 27,364 | 410 | ---
title: "Introduction to fastman"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Introduction to fastman}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
## Description... |
506212f7e73779fd5bf62b35a061ba0f8b519b7fff749c410dcf81066ffb740f | R | 27,453 | 810 | ---
title: "Anders MelBrM: CIBERSORTx analysis"
output:
html_document:
toc: true
toc_depth: 2
toc_float: true
code_folding: hide
number_sections: true
editor_options:
chunk_output_type: console
---
```{r setup, include=F}
knitr::opts_chunk$set(echo = T, message = F, warning = F, error = F, c... |
db30ab2d59c0517984b8ba39ad2220dffa740f6ab080ae8bbc70ab950301ada5 | R | 27,528 | 422 | ### Loads the data and creates data frames for the analysis ###
fpath <- paste(getwd(),"/Parkinson-UPDRS-TMS-cohort-main/data_UDPRS_TMS/",sep = "")
TMStable <- read.table(file = paste(fpath,"TMS.csv",sep = ""), sep = ",", header = TRUE)
TMStable$Period <- factor(TMStable$Period)
TMStable$ID <- factor(TMStable$ID , leve... |
96e47adbbf8c5ed54c19d83ed7a09ddf076c423f7634e2e0ab1316f85b39c74f | R | 27,554 | 710 | ---
title: "Harris October 2024 scRNA-seq Huwe1 NSCs"
subtitle: "Pseudobulk differential expression analysis"
author: "Rebecca Johnston and Lachlan Harris"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r original-data-directory}
#... |
90e932aef737a8d04fff1c48a87b6bee55c4c409eb840dd1e8df3bf76a473a3e | R | 27,572 | 784 |
get_communities_from_graph <- function(
graph,
method = 'spin_glass_no_weight',
communities_number = NULL,
checkCommunitiesConnectivity = TRUE,
seed = 1234){
set.seed(seed)
if(is.null(graph))
stop('Cell state graph must be generated first !')
... |
9b2af7e2dd1fa8db47c8060e63e5c5f18b1b89d1a120d49db2d100e7aacdecf4 | R | 27,592 | 1,023 | ---
title: "Anders MelBrM: Somatic variants"
author: "Layne Rogers, DCI Bioinformatics"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document:
highlight: pygments
code_folding: hide
toc: true
toc_float:
collapsed: true
toc_depth: 4
number_sections: true
---
```{css, echo=FAL... |
eb577371dd2ab8185bf6b7a2008dc58a5c916a9113aa3b2ea5b8d6b209790e26 | R | 27,668 | 779 | ---
title: "Cell-to-cell variation analysis: cells not detected as expressed"
author: "Joyce Hsiao"
date: 2016-07-08
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$se... |
36a9a550bb54bb55d3ffd806b8d0e061a1201836793e12861d82aa73db91a8ba | R | 27,679 | 800 | library(cowplot)
library(patchwork)
# Meta highligh plot ----
# added order to list of params
#changed DimPlot_scCustom_man to DimPlot_scCustom_man_man, and cahnged order from true to order
Meta_Highlight_Plot_man <- function(
seurat_object,
meta_data_column,
meta_data_highlight,
highlight_color = NULL,
backg... |
1221876a3ecb1906e6e9b38a6f6e0c41834e64adb07b16b3e50f65fa29072479 | R | 27,929 | 741 | #' heatmap3.LW.R
#'
#' This function runs differential gene analysis (linear modeling on normalized counts)
#'
#' @keywords heatmap
#' @export
#' @import gplots
#' @import dynamicTreeCut
#' @import WGCNA
#' @examples
#'
# AUTHOR: Freddie (Edited by Leanne Whitmore)
# DESCRIPTION: This was updated so that... |
bf5feff6d6743b8f488e175bd8f664d679d80d9b3f2267401b99ad70d2267af2 | R | 28,112 | 565 | #!/usr/bin/env R
# Author: Sean Maden
#
# Build env for rmse TABLE S4.
#
# Run from top level (`deconvo_lute-paper/`).
#
#
#
source("software_manuscript/src/rmse.R")
# Parse proportions outputs
# Cohort 1 pseudobulk, K2 and K3
# proportions cohort 1
# k2 results
load(file.path("huuki-meyers-et-al-2023_dlpfc-cohor... |
e4a7a599ad57fed829881f4ff7a0b680b055e6e12643a88072d34f39b4e820e9 | R | 28,283 | 834 |
# ------------------------------------------------------------------------------
# --- maths functions ----------------------------------------------------------
# ------------------------------------------------------------------------------
# -- angle_diff_deg() -----------------------------------------------------... |
a8671eec89a947444e2c2337858a6952b724b77eb17e4b201936c41673a27a2c | R | 28,521 | 475 | ---
title: "Proportion of diads and triads"
author: "Filipa Torrão & Eugenia Chiappe"
date: "`r Sys.Date()`"
output:
html_document: default
editor_options:
chunk_output_type: console
---
## Setup and Libraries
```{r}
library(tibble)
library(fafbseg)
#if (!require("devtools")) install.packages("devtools")
#devtool... |
c7052b255391a29d6240b8d32e25ad79fec20b34a15f21096f034b3395f5c4c5 | R | 28,522 | 899 | #' @export
#' @import methods
#' @import GGally
#' @import reshape2
#'@title GetDiffExprsData
#'@description a function that retrieves DifferentialExpression data from
#'a BundledExperiment
#'@param be an object of class bundled experiment
#'@return a list with the differential expression files annotated.
#'
GetDiffE... |
730ccd091792734f413b3911a3571e8a91295a3d3778d7ca616062d655d4a504 | R | 28,572 | 653 | ---
title: "MDACC PCM and xenograft data for Anders lab MelBrM"
author: "Marissa Lee, DCI Bioinformatics"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document:
toc: true
toc_depth: 2
toc_float: true
code_folding: hide
number_sections: true
editor_options:
chunk_output_type: consol... |
d0168275f508cc4171b82812342020415495121fd378c91b2a487b7faa4247b5 | R | 28,588 | 763 | ---
title: "Fig violin"
author: "SRomano"
output: html_document
editor_options:
chunk_output_type: console
---
# Load packages
```{r}
library(ggplot2)
library(dplyr)
```
# metaG
## Load dfs and format
```{r}
df_comb<-readRDS("/metaG/R_analyses/Taxonomy/RDS/df.comb.cv.scv.rds")
df_comb<-subset(df_comb, ML == "ridge... |
748d955b53ba94dff1529524dee1620daa6c0e467d952a917a4fd68d3628bb4c | R | 28,725 | 884 | rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
library(magrittr)
library(harmony)
library(R... |
8a41bd369f7f7941b2d28a12064e3937a9a3bff09af24194ac8bf39fe3a244ae | R | 29,083 | 945 | # Created on Sun Jun 27 21:50:13 2021
# Name: labula.R
# Purpose: Evaluates distribution of connections of the two post in the lobula
# Author: Andrea Vaccari (avaccari@middlebury.edu)
#
# Generates:
# - A 3d plot showing all the selected endpoints considered in the lobula, the
# selection plane, the centroid of ... |
7736bf3f028bc570de899b082453e8998a70c3b4101f042bef8e0cc90c6df800 | R | 29,192 | 468 | #### Code for Manuscript Becker, Sommer & Cabeza 2023
#### Neural Mechanisms of Creative Problem Solving: From Representational Change to Memory Formation
#### Control analysis Subsequent Memory
#### (c) almaxi@gmail.com
#### last update: 22/Jan/2024
rm(list = ls())
## load libraries ######################... |
25f6b6e6eb3bbf0fc8fc508af1444da44be68cb101fb1ea71eb4bf9ef201a426 | R | 29,271 | 699 | source('human global.R', local = TRUE)
options(future.globals.maxSize= 891289600)
## setting header & sidebar
header <- function(){
dashboardHeader(title = "Welcome to GD-CAT!")
}
sidebar <- function(){
dashboardSidebar(
sidebarMenu(
id = "tabs",
class= "hide",
menuItem("Instructi... |
458e9356b391f030a97eecf637a089b59b0cc895e6584035cb2b923152c02dec | R | 29,331 | 834 | ---
title: "Figs"
author: "SRomano"
output: html_document
editor_options:
chunk_output_type: console
---
# Load packages
```{r}
library(ggplot2)
library(tidyverse)
library(emmeans)
library(nlme)
```
# Seq depth
```{r}
all<-readRDS("/16S/R_analyses/RDS/all_g_counts.rds") %>% t() %>% as.data.frame()
meta<-readRDS("... |
9e49738159fcebc7ab71c1390864ce46c434e1c96dd1606db4be4445c142b0c8 | R | 29,433 | 440 | ---
title: "Carving cell trajectories"
# author: "Julien Delile"
# date: "`r Sys.Date()`"
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{Carving-cell-trajectories}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, echo = FALSE}
embed_png ... |
d154060c8732834f83a1d1ab485565ce8d5288e038b67e5096b3ff78bd52738c | R | 29,572 | 708 | ### code for the linear mixed-effects analysis
library(lmerTest) # version 3.1-3
file_path <- "/_path_to_csv_file_/data_for_lmerTest.csv"
data <- read.csv(file_path, header = TRUE)
head(data)
### Normalize data
data_exsubj <- data[, !(names(data) %in% c("subject"))]
z_data <- as.data.frame(lapply(data_exsubj, scale))... |
7957135cac1559b605fdabeca3662855eb2b00dfc4b384826400bfb2ed234f38 | R | 29,618 | 798 |
# Allow igraph S3 class to be used as field of Carver
setOldClass("igraph")
Carver <- setRefClass(
Class = "Carver",
fields = list(
antler_env = "environment",
W_optim = "numeric",
optim_res_all_batches = "list",
plot_folder_path = "character",
runVariables ... |
bcad706c1fe8e23e757044c8f645a6c154875c745ed30b5f987b78293ade3a54 | R | 29,741 | 754 | ---
title: "Harris scRNA-seq Ascl1 qNSCs tradeSeq results"
subtitle: "tradeSeq fitGAM nknots = 6"
author: "Rebecca Johnston"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r hpc-memory-requirement}
# This script uses max 8 GB mem, ... |
f5a7793f0348ce8e8c9c280b0e40bd1891131e284ab74ed3f5cc4b158e0d336d | R | 29,753 | 566 | ###Running EVE experiment using only adults in analysis
###purpose is to look for evolutionary shift in expression in shrew lineage
###Using a regrowth adult brain regions (Stage4 spring adult)
### STEP1: Start by loading libraries you will need
library(stringr)
library(readr)
library(assertr)
library(tximport)
librar... |
32ea4a2d2f96445105920ce01d837bd57ed3932f76f100dd121bdc29f380bee7 | R | 29,967 | 762 | ---
title: "Harris scRNA-seq Mycn qNSCs tradeSeq results"
subtitle: "tradeSeq fitGAM nknots = 6"
author: "Rebecca Johnston"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r hpc-memory-requirement}
# This script uses max 9 GB mem, t... |
88a3ac943b91489bbe590f294c463b41d1b9731af428127ae3e52d88bd24e8f0 | R | 29,972 | 494 | #####################################################################################################################
### Goal: Read alignment files into methylKit and filter to create tabix files of filtered cytosine methylation, call DMS and DMRs without overdispersion correction
### Author: Janay Fox
### R script
##... |
1004aa24dad3056d8ade33ad01e9a68fef0be972c07878092b5062437f6d958c | R | 30,170 | 494 | #####################################################################################################################
### Goal: Read alignment files into methylKit and filter to create tabix files of filtered cytosine methylation, call DMS and DMRs with overdispersion correction
### Author: Janay Fox
### R script
#####... |
6aee939a18d59eed8dd0a2ab9f5f985d6e330b510ba1ddfbfcc65ef0d4c7aaa1 | R | 30,414 | 757 | ---
title: "CNN evaluation"
output:
html_notebook:
df_print: paged
html_document:
df_print: paged
code_folding: show
---
```{r}
#rm(list = ls())
library(tidyverse)
library(future)
library(ggthemes)
set.seed(1245264)
```
In this notebook we will test the performance of varKode to distinguish species of ... |
0c1dfd08c05d7856fc096bccb28e2d2e290267c73e7292a261a1389cd6ce123c | R | 30,489 | 490 | #### Code for Manuscript Becker, Sommer & Cabeza 2025
#### Neural Mechanisms of Creative Problem Solving: From Representational Change to Memory Formation
#### Control analysis Subsequent Memory
#### (c) almaxi@gmail.com
#### last update: 18/Feb/2025
rm(list = ls())
## load libraries #######################... |
89f6d5fab247af770885652d8309202d8de29b51b1c292a187a38f65a8f90251 | R | 30,539 | 896 | #' @export
#' @import methods
#' @import reshape2
#'
setClass("MultiExperiment",
representation(name='character',
organism="character",
keys = 'character',
exprs_data = "matrix",
diff_exprs = "list",
... |
938f6f01c7f40de02d5d45c89636ac2e37deeddaae3b0e36dfc6f9b449be8154 | R | 30,680 | 690 | library(ggplot2)
library(ggseg)
library(dplyr)
library(colorspace)
library(ggsegSchaefer)
library(ggpubr)
# load in libraries and set up colours
cbbPalette= c("#F0792C", "#f5ec6c",'#4d3d87',"#76D7C4","#268236", '#4d3d87','#593d80', '#3b49e3')
########################## Schaefer atlas heritability ###################... |
b596702d81390e802ca27d9f320ac8a93100a3ea71c0d137b94195a71fed3f83 | R | 30,793 | 892 | #' Split a path name into into its components
#'
#' @param path A path name
#'
#' @return a vector of path components (starting with the last component)
#' @export
#'
#' @examples
split_path <- function(path) {
if (dirname(path) %in% c(".", "/", "//", "\\" , "\\\\", path))
return(basename(path))
return(c(basena... |
d8d9a17b698f6a95774acf14ebb71d46e988de8da84ac144e4c7d0953bc2ec12 | R | 30,814 | 883 | # Siwei 30 May 2023
# Siwei 07 Jul 2023
# read in Jeff's raw dataset and make baseline correction
# use the 2nd batch data
# write out baseline-corrected data matrix
# Yan edited 10 April 2024
# init #####
require(zoo)
library(ggplot2)
library(gridExtra)
library(gplots)
library(RColorBrewer)
library(colorRamps)
libra... |
18bdbacc9cf7493f6296da0b661c7e2572b3043f0444ae8ce1f60e84a8fb77af | R | 30,921 | 531 | #Code for processing the differential expression results that we can automatically pipe in from Gemma in preparation for running the meta-analysis
#Goals:
#1. For each of the datasets that have survived our inclusion/exclusion criteria, we will need to identify the relevant result sets and statistical contrasts that a... |
9cc44d4372e355bebaf8ccb33ef2ec859038ee408df0958ab5d44909bc5b2b9d | R | 30,985 | 877 |
rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
library(magrittr)
library(harmony)
library(... |
fddd0177106cb0165eed48889a9817abaab4604c257585da2da83ba2d441b92c | R | 31,173 | 587 | ---
title: "5. Importing External Datasets"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Importing External Datasets}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, eval = FALSE, warning=FALSE... |
aeed2bd1819ee204e0683e3f37e10d8c05a1dd342c83bb2c3650a32307b63c4c | R | 31,620 | 648 | library(Seurat)
library(tidyverse)
library(scCustomize)
library(patchwork)
library(ComplexHeatmap)
library(circlize)
set.seed(1234)
polychrome_pal <- DiscretePalette_scCustomize(num_colors = 36, palette = "polychrome")
polychrome_pal <- polychrome_pal[c(1, 3, 6:36)]
stepped <- DiscretePalette_scCustomize(num_colors = ... |
5c26c2f8d9145730fbaf37311d7892d43d93065a0a7fa393fbbd9f8559ba361e | R | 31,744 | 627 | ---
title: "4. Example analysis notebook"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Example LH Analysis}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, eval = FALSE, warnings = FALSE)
```
... |
722c6b4cb571cb96e513c766403a7a431e801e7742af87c4cca2ada2ef5127d0 | R | 31,777 | 962 | ---
title: 'TCP data-release-behaviour figures'
output: html_notebook
---
```{r}
library(reticulate)
np <- import("numpy")
library(svglite)
library(pbapply)
library(parallel)
library(patchwork)
library(superheat)
library(pals)
library(magick)
library(ggplot2)
library(ggeasy)
library(ggpubr)
library(patchwork)
library... |
751c683379e0e348d011b803fe3590cdb2e4f015f66c7839abd190711f37a7b8 | R | 32,060 | 837 | ---
title: "Harris October 2024 scRNA-seq Mycn qNSCs"
subtitle: "Pseudobulk differential expression analysis"
author: "Rebecca Johnston and Lachlan Harris"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r original-data-directory}
#... |
05eb70eb5c769a83aa8afa3078c2071e0dc4648ae3d2de134a69cf17086e5e92 | R | 32,140 | 875 | ---
title: "Cell-to-cell variation analysis: paper figures"
author: "Joyce Hsiao"
date: 2016-10-28
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = FALSE,... |
5234610f1615112d2af311196e543fcdea76c4025e8177c3f51c0cda3f20214c | R | 32,158 | 544 | ---
title: "Transcriptomic Summary"
# author: "Julien Delile"
# date: "`r Sys.Date()`"
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{Transcriptomic-summary}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, echo = FALSE}
embed_png <- fun... |
1f209a5c05c6969fef69920a4394343db52a9acbbe121edba2ccedcd40e3c62f | R | 32,233 | 985 | ---
title: "Anders MelBrM: survival analysis"
subtitle: "Duke and MDACC"
author: "Layne Rogers, DCI Bioinformatics"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document:
highlight: pygments
code_folding: hide
toc: true
toc_float: true
toc_depth: 4
number_sections: true
---
```{c... |
ed4746022fbe82de92a90dd4ebf7dd2244064dc8dbd0288e66e1b1c4596d2bdf | R | 32,374 | 819 | library(stats)
library(ggplot2)
library(ggpubr)
library(heplots)
# Set working directory. Change this according to where your folder is.
setwd("PATH_TO_WD")
# Data for all 1831* subjects (Note that one subject withdrew from the study since
# the writing of associated publication, and the data had to be dropped)
maste... |
7d2ea990a7000619afc575dbc0203fda4f04b05b51082e6441440a4b2f71723d | R | 32,418 | 952 | newClusterWeightedDistance <- function(Wcc, compact_data){
res <- fastEuclideanDist(t(sqrt(Wcc) * compact_data))
# Normalized distance matrix
res <- res / sum(res)
# add a minimal distance between cells
res <- res + 1e-10
diag(res) <- 0
return(res)
}
newScoreFunctionWeightedDistance <- function(
... |
96834a5e4949ba1993be59fe8cf7a49d41c6425c03c2008385be81c87d310dbd | R | 32,646 | 707 | ---
title: "Extended Data Figure 3"
author: "Sang LIU"
date: "`r Sys.Date()`"
output:
html_document:
code_download: TRUE
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## Load packages
```{r}
library(nat)
library(ggplot2)
library(ggpmisc)
li... |
47673f1f56bf001ea9447f9ca07d941dde77322a086998298a03823343fb2d31 | R | 32,671 | 634 | ### Tripsacum greenhouse experiment
### Root section analysis
### Code by Joel Swift 04-2024
library(tidyverse)
library(readxl)
library(emmeans)
library(ggpubr)
library(lmerTest)
library(viridis)
library(scales)
# Set theme
theme_set(theme_bw())
treatment_palette <- c("Waterlogged 24" = "#26008E",
... |
bb4ea077cd296a101a97801a6a3232641e5a4aa544f9652f7c76c72205991559 | R | 32,871 | 761 | #######################################################
### Goal: Plot and analyze overdispersion results
### Author: Janay Fox
### R script
#######################################################
## Set up ##
#install packages
#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages("ggpubr")
#instal... |
938d92ca85928efdcdc7c58de0bb1fc7413b7c812e2ccceb2a3fa5c439c85646 | R | 32,879 | 610 | ---
title: "2. Mapping Tutorial"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Mapping Tutorial}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE, eval=TRUE}
options(width = 300, rmarkdown.html_vignette.check_title = FALSE)
knitr::opts_... |
cd37dbb2b2c6ac4665b262580a0640da4ce52d4f7de96d5030114e810b9081bf | R | 33,065 | 1,293 | ---
title: "Anders MelBrM: WES QC"
subtitle: "Duke and MDACC"
author: "Layne Rogers, DCI Bioinformatics"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document:
highlight: pygments
code_folding: hide
toc: true
toc_float: true
toc_depth: 4
number_sections: true
---
```{css, echo=FA... |
7bd72526ec6d491d1fc0c22d30e673201860cc086175e990f37379d5cbff4666 | R | 33,234 | 618 | #######################################################
### Goal: Plot and analyze annotation stats, run go seq
### Author: Janay Fox
### R script
#######################################################
## Set up ##
#install packages
#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages(genomation... |
80bb06e4b62e921a0fa80fec0289421bb9de0ff67d957eb0b7356fd9eae21a91 | R | 33,396 | 1,050 | rm(list = ls())
library(Seurat)
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Rmagic)
library(readr)
#library(phateR)
library(viridis)
library(magrittr)
library(harmony)
library(... |
22308aab68d449bb0e3ab3689e65ba40718662c7be3d41cde90179c8c4916058 | R | 33,435 | 708 | library(Seurat)
library(tidyverse)
library(nichenetr)
library(dplyr)
library(circlize)
library(ComplexHeatmap)
library(ggplot2)
#packageurl <- "https://cran.r-project.org/src/contrib/Archive/pbkrtest/pbkrtest_0.5.1.tar.gz"
#install.packages(packageurl, repos=NULL, type="source")
##Set some parameters
Log2FC_var <-... |
8c6868a70b9e1806c04f3222909365a75a9db64de568a4bb09a3e62b4d1b428a | R | 33,488 | 711 | library(Seurat)
library(tidyverse)
library(nichenetr)
library(dplyr)
library(circlize)
library(ComplexHeatmap)
library(ggplot2)
#packageurl <- "https://cran.r-project.org/src/contrib/Archive/pbkrtest/pbkrtest_0.5.1.tar.gz"
#install.packages(packageurl, repos=NULL, type="source")
##Set some parameters
Log2FC_var <-... |
082063695a8d6f25df257ab15ee1102ed2ba005675c81a6ac7bebf82bd18dc02 | R | 33,635 | 712 | library(Seurat)
library(tidyverse)
library(nichenetr)
library(dplyr)
library(circlize)
library(ComplexHeatmap)
library(ggplot2)
#packageurl <- "https://cran.r-project.org/src/contrib/Archive/pbkrtest/pbkrtest_0.5.1.tar.gz"
#install.packages(packageurl, repos=NULL, type="source")
##Set some parameters
Log2FC_var <-... |
e12ee9d795b48ba9248656e1e4a42dc9b23d51bb21dcec0b01fc3aa682758cf5 | R | 33,650 | 1,220 |
local({
# the requested version of renv
version <- "1.0.7"
attr(version, "sha") <- NULL
# the project directory
project <- Sys.getenv("RENV_PROJECT")
if (!nzchar(project))
project <- getwd()
# use start-up diagnostics if enabled
diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FALS... |
e578c214b2f1e7e901e41d60cf7ae0096b51f4dbf20cc1ba60e0071fc99863ef | R | 33,707 | 774 | #######################################################
### Goal: Plot venn diagram and heatmaps and do cluster analysis
### Author: Janay Fox
### R script
#######################################################
## Set up ##
#install packages
#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages("g... |
29f4d1a8bbb5453999ddf7606458c8586bf8c61110f19410916dd2b56a261a77 | R | 33,883 | 875 | ---
title: "Harris October 2024 scRNA-seq Ascl1 qNSCs"
subtitle: "Pseudobulk differential expression analysis"
author: "Rebecca Johnston and Lachlan Harris"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
editor_options:
markdown:
wrap: 72
---
```{r original-data-directory}
... |
147f762aff918ea5f4c6066f1196ae5db089857806ac2204f6dcd229b4263932 | R | 33,976 | 716 | library(Seurat)
library(tidyverse)
library(nichenetr)
library(dplyr)
library(circlize)
library(ComplexHeatmap)
library(ggplot2)
#packageurl <- "https://cran.r-project.org/src/contrib/Archive/pbkrtest/pbkrtest_0.5.1.tar.gz"
#install.packages(packageurl, repos=NULL, type="source")
##Set some parameters
Log2FC_var <-... |
754c6b77f179800bab2bd9179977359857742d095b540777121757b5ce87d6dd | R | 34,534 | 871 | library("tidyverse")
library("RColorBrewer")
library(reshape2, ggplot2)
# process raw outputs from SeaMoon, which are individual losses between each pair of ground-truth
# and predicted motions, and identify the best-matching pairs, with the constraint that
# a prediction cannot be matched to several ground-truth mo... |
27ebab2a9b2fbe07a4cccbeaec5044a76d66077d58a001920b84bbf0cc939533 | R | 34,586 | 554 | fastman <- function(m, chr = "CHR", bp = "BP", p = "P", snp, chrlabs, speedup=TRUE, logp = TRUE, scattermore = FALSE, col="matlab", maxP=14, sortchr=TRUE, bybp=FALSE, chrsubset, bprange,
highlight, annotateHighlight=FALSE, annotatePval, colAbovePval=FALSE, col2="greys", annotateTop=TRUE, ann... |
80ed5813bee21f8976af523e900aecf70e2d9f4631d1a9197c95399e2b460de9 | R | 34,769 | 735 | asym_model_gen <- function(meas, hem, trk, trk_sz, dir_in, other_dat, covariates, regions,
beh_names, rating, dV, ctr_str, use_inf, use3, vqc_enigma, rating_vqc){
if (meas == 'wm'){
mri <- read.csv( paste0( dir_in, '/reorg/volume_wm_output.csv' ))
colnames(mri)[colnames(mri) == '... |
b09bcee879c8b5dd83fea40c1ac8b5576f1f7eed9403f3233f4d650c2778cb3e | R | 34,809 | 903 |
# Mi1 equator, use PR num -------------------------------------------
ind_up_Mi1 <- c(599, 39, 207, 606, 388, 10, 12, 157, 361, 287, 503, 105)
ind_down_Mi1 <- c(401, 334, 209, 210, 720, 667, 590, 628, 489, 289, 393)
# ME layer ----------------------------------------------------------------
# - coord transform vi... |
7332eaf761ae2963e8a496e866a48840e2603b21218d2ce7f04a9bcb578cce80 | R | 35,157 | 712 | library(tidyverse)
library(plyr)
library(ukbb)
library(arrow)
library(lubridate)
data_root <- "/home/mica/storage/healthspan/v6.2"
instances <- c(0, 1, 2, 3)
scan_instances <- c(2, 3)
# ----------------------------------------------------------------------------------------------------------------------
# Helper func... |
554b8a31d24d2402200173842860214b33c54020192319806be74764f72f9192 | R | 35,208 | 649 | ### SETTING UP ENVIRONMENT
Sys.setenv(KMP_DUPLICATE_LIB_OK=TRUE)
library('reticulate')
library('beeswarm')
library('nloptr')
library('car')
library('zoo')
library('plotrix')
library('lme4')
library('RColorBrewer')
library('lsr')
library('prettyGraphs')
library('scales')
library('matrixStats')
library('BFpack')
np = imp... |
cfc28e0f125c5eeed3ba1c30fc2bcb0a8fd5862da6ec4eb0cf70cd2ffe006428 | R | 35,886 | 882 | library(shiny)
library(shinydashboard)
library(shinyalert)
library(dplyr)
library(purrr)
library(ggplot2)
library(echarts4r)
library(MetBrewer)
library(forcats)
library(DT)
library(zip)
library(reticulate)
library(Rcpp)
library(reshape2)
library(colormap)
library(patchwork)
library(qgraph)
library(devt... |
466af08c4d780125b5581b07aca8a91f942220b782ff6cc5153bc32bac921b2d | R | 36,131 | 756 | library(clusterProfiler)
library(org.Rn.eg.db)
library(DOSE)
library(ggplot2)
library(openxlsx)
library(stringr)
library(readxl)
# Function to perform GO analysis and return results as a data frame
perform_go_analysis <- function(gene_list, group_name) {
# Convert gene symbols to Entrez IDs
gene_df <- b... |
e5cd272330601d3b0c2b31dd2fa34401694d6971e841e6f82ae2afe65f7a5561 | R | 36,443 | 1,125 | ---
title: "Results"
author: "DCI Bioinformatics"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document:
highlight: pygments
code_folding: hide
toc: true
toc_float:
collapsed: true
toc_depth: 4
number_sections: true
---
```{css, echo=FALSE}
.watch-out {
background-color: l... |
99500f62354c4f0008fa676119fc7483ad90c5760e8f8811f6536af6cb8bd46b | R | 36,548 | 1,305 |
local({
# the requested version of renv
version <- "1.0.11"
attr(version, "sha") <- NULL
# the project directory
project <- Sys.getenv("RENV_PROJECT")
if (!nzchar(project))
project <- getwd()
# use start-up diagnostics if enabled
diagnostics <- Sys.getenv("RENV_STARTUP_DIAGNOSTICS", unset = "FAL... |
b571997a4c4c782959bfb0a4a8c36c26edbe094e7d9c720990ad1ce3f3dfb7e4 | R | 36,754 | 1,172 | ---
title: "flawless_code_public_part2"
author: "Owen Forbes"
date: "06/10/2023"
output: html_document
---
# Part 2 - Code accompanying paper "Functional analysis within latent states: A novel framework for analysing functional time series data"
#---
Relating FHMM dominants states, (and eventually FPCs within sta... |
e9e5b4b9227b57036ad5e9cd11a2228f1dadd6598a52a8010b6fc9213ed956e9 | R | 37,299 | 812 | get_absence_or_presence = function(x, DosageCutoff_for_UltraRarePresence){
a=sum(x < (1+DosageCutoff_for_UltraRarePresence) & x>= DosageCutoff_for_UltraRarePresence)
b=sum(x >= (1+DosageCutoff_for_UltraRarePresence))
if(b > 0){
g = 2
}else if(a > 0){
g = ... |
f561a7ad272cd8e752515182706255c3d7a0954595a0110604edf1c94136b3ed | R | 38,057 | 1,038 | ##______________ Package imports ________________
#' @importFrom ggplot2 ggplot aes theme element_text element_line element_rect element_blank unit labs ggsave guide_legend xlab ylab xlim ylim labs
#' @importFrom ggplot2 geom_col geom_tile geom_text geom_jitter geom_hline geom_vline geom_errorbar geom_point
#' @importF... |
b77aed14a389fb043de64b79a85677944032e773a3e8aa8090bf3375983f7200 | R | 38,222 | 1,011 | ---
title: "Revision Optic Tectum"
output: html_document
date: "2024-05-27"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(multiomics)
dna_repair <- getGenesFromGO("GO:0006281")
#Ribo Large
ribo_large <- getGenesFromGO('GO:0022625')
ribo_small <- getGenesFromGO('GO:0022627')
#Calculate de... |
6e523a652c1ab9de375636c2f741e5163b4a5792f7bddfd1e7dacd7b8622accb | R | 38,385 | 976 | #'@export
#'@title MSstatsCorrectPTMs
#'@description Important !!! Use MSstat Report v3.7.3 Input
#'format from Spectronaut for protein quantification .
#'A quite "complicated" function. It takes input from
#'both proteome and ptms data. And run the PTMs quantification correcting
#'the values from the protein abundan... |
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