sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
a1a550926bbb8031da184b417634f1b4aeb650190f6c2f3ed6936f5d7f958859 | R | 9,726 | 269 | ####<----- Some plotting tools ----->####
#' Overlay density plots of log-transformed counts (for one gene)
#'
#' @param molecules Matrix of log-transformed counts. Sample by cell.
#' @param annotation Annotation matrix labeling each cell according to individual,
#' batch, replicate, well ID, etc.
#' @param ind... |
3e8c274d75a2304f94d4a4ced6af451d75ea70f85fafc04f7aab77963fef36e0 | R | 9,814 | 235 | # R Corbett 2023
#
# Generate survival summary table for PBTA Ancestry project
# Load packages
library(tidyverse)
library(survival)
library(patchwork)
library(colorblindr)
# Establish directory paths
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
analysis_dir <- file.path(root_dir, "analyses", "survival... |
5c1dcc7288b9722fbba0d9c08827b14df745b552a5fcd86cdf62c21c825139cb | R | 9,815 | 254 | ---
title: "Tracking down bug in reads to molecules conversion - Attempt 04"
author: "John Blischak"
date: 2016-03-30
---
**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$set(cache = TRUE)... |
a9650653ead855e6aa5ecad07134b9ecd257228865e417308a7e2c2e6c93af71 | R | 9,817 | 273 | #############################################
############### RIVM Nowcast ################
#############################################
setwd("/Users/silaskoemen/Library/CloudStorage/OneDrive-ImperialCollegeLondon/Imperial/NowcastPNN/")
## Load packages
library(Matrix)
library(tidyverse)
library(scales)
library(RColo... |
f485c7be593e6731ce7532f2f4ba0ff60e86cd2bc6167f0c933ab7b04401873c | R | 9,863 | 235 | #Figure 9:
#(A) CIBERSORTx using mRNA data to estimate abundance of immune cells in MDACC MBM and ECM;
#(B) CIBERSORTx comparing MDACC MBM (n = 88) and Duke MBM (n = 13).
#(C) shows transformed M2: M1 ratios by sample type (MDACC MBM, MDACC LN, MDACC skin, Duke MBM).
# sif=/mnt/data1/public/singularity/dcibioinfor... |
111662e76a892f91c50200f44e7ff45ae185afb3f93cd1a6f47012ae6f5ef4cf | R | 9,877 | 279 |
plotRanking <-function (pvalues, summary, alpha = 0.05, cex = 0.75, decreasing = FALSE)
{
opar <- par(mai = c(0, 0, 0, 0), mgp = c(0, 0, 0))
on.exit(par(opar))
k <- length(summary)
if (decreasing) {
summary <- k - summary + 1
decreasing = FALSE
}
if (is.matrix(summary)) {
... |
c5c00840092b6159964f9fe4891ee74dbb9e64cc8373441de709a650a3099b48 | R | 9,911 | 356 | ---
title: "Plate reader growth curves of GAT201 mutants in RPMI media varying NaHCO3"
author: "Liz Hughes & Edward Wallace"
date: "19/02/2024"
output:
html_document:
toc: yes
toc_depth: 2
---
```{r call_shared_functions_formatting, child = "shared_functions_formatting.Rmd"}
```
# Summary
This experiments ... |
43c93637f5a6c221725259f1d07531af9d448acf6fea17129489ca2bf14f5c42 | R | 9,925 | 249 | ---
title: "Figure 2"
author: "Sang LIU"
date: "`r Sys.Date()`"
output:
html_document:
code_download: TRUE
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## Load packages
```{r}
library(nat)
library(ggplot2)
library(ComplexHeatmap)
library(g... |
8d040d751e027d6e80bc1729a3779c8e1de305ce0c7948b53c57b38f9652043f | R | 9,953 | 274 | ---
title: "Figure 1"
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(dendextend)
library(NbClust)
library(ggplo... |
9e7fc3f3532cecea3746b93f44aca3f04093f406b951c8510c66614a7298d191 | R | 9,954 | 261 | ################################################################################
#################### EMA Microglia RNA-seq GSEA ###############################
################################################################################
setwd("~/Dropbox/2023_EMA_Manuscript/Analyses/June2023")
options(stringsAsFa... |
7dbcc6c9112026c49a2a7e527659049f7527669c083b3ba8fb83147f87611594 | R | 9,958 | 227 | # https://www.geeksforgeeks.org/accessing-rest-api-using-r-programming/
# Installing the packages
#install.packages("httr")
#install.packages("jsonlite")
# Loading packages
library(httr)
library(jsonlite)
# Initializing API Call
numPGS= 3688 # but there are some redundant ones:
# https://www.pgscatalog.org/rest/sco... |
5f06f692c27091db9dbf979792412712bb170dfab8585a4bd246b0ac927c0d8a | R | 10,007 | 195 | #' Compute Jaccard similarity matrix for gene sets.
#'
#' Given a list of gene member vectors, this function computes the pairwise Jaccard similarity matrix.
#'
#' @param members_list A named list where each element is a character vector representing gene members.
#' @return A numeric matrix with row and column names c... |
1b5aa6d1eee5f8fcd7dac8d80ca7d58260e1f0207d74763519d23a2c41318f44 | R | 10,033 | 294 | ---
title: "BASiCS - 40,000 iterations"
date: 2015-08-10
---
**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")
```
We analyzed our single cell data with [BASiCS][] developed by [Vallejos et al., 2015... |
b3d93ea4c03fa90d1398fe96757eefd550d24c6d912d71cfec08944a1660ab26 | R | 10,037 | 177 | ---
title: "Pipeline Troubleshooting"
author: "Layne Rogers"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
output:
html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Purpose
Pipeline errors are a common occurrence when doing any analysis, and it's important to learn (and have re... |
51ac4e8e2ed1fb12b545aa4b9c4f7122144b670d0c92bcbfd0c5a220d0b9a6b1 | R | 10,059 | 397 | ---
title: "EDCS cleaning of the epigraphic text"
author:
- Petra Hermankova^[Aarhus University, petra.hermankova@cas.au.dk, https://orcid.org/0000-0002-6349-0540]
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
theme: united
toc: yes
toc_float: true
number_sections: true
toc_de... |
2bd72ecadb3da5753fd4ae6cb2b83ba1299a584150ba47e2496b6785a2146a24 | R | 10,104 | 232 |
#load useful libraries
library(nlme)
library(multcomp)
library(ggplot2)
library(tidyverse)
library(cowplot)
library(REdaS)
library(patchwork)
#Panel B: remapping index
hb_offset_diff_evo <- read_csv('C:/Users/mbasn/Dropbox/Manuscript-Basnak/Nat Neurosci Aug 2024 revision/zenodo/Figure7_analysis/hb_offset... |
041964bb1874eef5c2554bec421d5a03901fcc21aa497d27be6aac96ba8e13ba | R | 10,127 | 214 |
# helper functions
sn_eset_rescale <- function(sn.eset, s.glial = 3, s.neuron = 10){
mexprs <- m1 <- exprs(sn.eset)
which.glial <- sn.eset[["k2"]]=="glial"
mexprs[,which.glial] <- mexprs[,which.glial] * s.glial
which.neuron <- sn.eset[["k2"]]=="neuron"
mexprs[,which.neuron] <- mexprs[,which.neuron] * s.neuro... |
e5349d860c77e5e03f32ae5e407a25a4ed79e0eec345c105169412a08f58d004 | R | 10,129 | 348 | # sif=/mnt/data1/public/singularity/dcibioinformaticsR-v2.1.sif
# dir1=/mnt/data1/workspace/Anders/MelBrM
# singularity exec \
# --containall \
# --no-home \
# --bind ${dir1}:${dir1}:rw \
# ${sif} \
# R
set.seed(2024)
library(tidyverse)
library(readxl)
library(openxlsx)
library(xtable)
library(glue)
library... |
6dfc1414e2f808f75d75f8786e0ba71961ebf3720915a22eb26bb2b9579e0e5b | R | 10,137 | 269 | ---
title: "Subsample: Cell to cell variance in expression"
date: 2015-07-16
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(warning = FALSE)
```
How does cell to cell variance i... |
c8faa2b638a24bd0e24842f28757be4750366704af19b2707735fc5140f89468 | R | 10,165 | 255 | library(tidyr)
library(dplyr)
library(data.table)
library(parallel)
library(ComplexHeatmap)
library(circlize)
library(viridis)
library(ggplot2)
workingDir <- '../2024_02_29_multiVelo/'
dataDir <- '../2024_02_29_multiVelo/data/'
print("Reading in state files")
stateFile_case <- fread(file.path(dataDir,'Human_vs_Macaqu... |
61222bb14996489d37b1694b4f20f8d88c54baf2e26c225fe4e7457a60e6e869 | R | 10,205 | 314 | sif=/mnt/data1/public/singularity/dcibioinformaticsR-v2.1.sif
wd=/mnt/data1/workspace/Anders/MelBrM
rtmp=/mnt/data1/workspace/Methods/Containers/MissingPackages/v2.1:/rtmp
singularity exec --containall --no-home --bind ${wd}:${wd}:rw --bind ${rtmp} ${sif} R
library(tidyverse)
library(openxlsx)
library(DESeq2)
library(... |
635e3e8dfd0fb45322f9cdf6d18f49b5f697498c74afa5bb8d52f3326038940f | R | 10,268 | 351 | ---
title: "Format and prep data"
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 {
backgro... |
280bd2ab6bcc28604f095ee54ae0fcb0be21c6158729e271237507a02b8e49cf | R | 10,347 | 231 | #Sample code for MetaData extraction for Gemma datasets, part3: Annotating
#Megan Hagenauer, Jun 27 2024
############
#This code has not been cleaned up, fully annotated, functionalized, and made easily generalizable
###############
library(gemma.R)
library(dplyr)
###############
#First - just as a reminder, this... |
919a680cecc3a9529f85a3ef01100c2ee1c9972c73d563c2e391e6837e9c0f23 | R | 10,422 | 328 | #'@export
#'@import methods
#'@import reshape2
#'@title ComplexCoExpr
#'@description Takes in input a MultiExperiment, and run a protein complex
#'co-expression analysis. It must have in input also a ComplexSet coming
#'from the proteomicstools package. The function requires the installation
#'of the proteomicstools p... |
7885b9bcba73a611cb0cbbacef13dcc406e2d753081c37f479d5a6ec23bf9a5b | R | 10,436 | 280 | # Filter and plot pathways enriched in each cluster and module of trajectory analysis
# input data
# - .tsv files with enriched pathways
# - top_match_between_IMC_to_RNA_clusters_original.csv (generated in 9. RNAseq_IMC_clusters_matching.R)
#### 0. Load packages, create folders #####
library(dplyr)
#install.packages... |
9a5a8591f3fb99efc0571db1b8369654ceb9e53a2b09ad575924acbf2ab9b458 | R | 10,478 | 190 |
set.seed(0) # random seed for reproducibility
rm(list = ls()); gc()
load_pkg <- rlang::quos(tidyverse, tibble, readxl, dplyr, miloR, scater, scran,
patchwork, SingleCellExperiment, Seurat, EnhancedVolcano, rstatix, ggpubr,
biomaRt, clusterProfiler, enrichplot, BiocPara... |
b10d3771624ceaedeacc66197d9f186de8582f69c26a016f6d9be2cb5be1d166 | R | 10,559 | 340 | ---
title: "Proportion of genes detected using all cells"
date: 2016-02-16
---
**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 = TRUE, fig.width = 8, fig.height = 8)
```
```{r ... |
ac694daf441fc2fbab68309c3ad06e79f34ed495b2b5357a98890b91915d6336 | R | 10,597 | 340 | ---
title: "Compare transcriptome-wide profile of CVs"
author: "Joyce Hsiao"
date: 2015-10-25
---
**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$set(message = FALSE, warn... |
22af1f6b0827766eaefa95f3b96db4171e36d583510ee6214981373f7df94531 | R | 10,610 | 231 | # general scripts
# Custom Functions
deg_extract_fn <- function(input_res, input_bmlist, symbol_name){
deg_temp <- input_res %>% rownames_to_column(var=symbol_name)
deg_temp <- subset(left_join(deg_temp, input_bmlist, by=symbol_name, multiple = 'all')) %>%
mutate(PValue = ifelse(PValue < 4.672418e-243, 4.67241... |
5cedb9da5b973a46d3505d01fbfd2de9d1f36218358df3e672c067bc91c73b45 | R | 10,623 | 207 | #Example code for making a Heatmap illustrating the Log2FCs from the individual studies for each of the top meta-analysis DEGs
#Megan Hagenauer & Jinglin Xiong
#June 6 2025
#This code is not functionalized and beautiful, but it is well annotated...
################
#Set the working directory to where you are storing... |
ac6fbbe71bb2c5def74e36404f6fd27dfbca25d35e9f23b4367896eb5138603f | R | 10,679 | 260 | # Load necessary libraries
library(Seurat)
library(Signac)
library(EnsDb.Rnorvegicus.v79)
library(dplyr)
library(ggplot2)
library(patchwork)
library(readr)
library(GenomicRanges)
library(SummarizedExperiment)
library(ggrepel)
library(cowplot)
library(openxlsx)
# Set base directory (use relative paths or ... |
179de94eb6730932c1fdc1729338b66712c3169bb63cae02590cd6885fb9f8a7 | R | 10,715 | 291 | #Preparing our limma results for meta-analysis
#Megan Hagenauer
#July 27 2023
###############
#Start with an empty workspace
###############
#Cleaning up the annotation for our results
#Example from Anne's results
setwd("/Users/hagenaue/Documents/drive-download-20230727T135146Z-001")
TempResultsJoined<-read.csv("... |
59da6f72d54fa1de155865e00cf1d8d100014e46cae2d95a42d8d4db9d64598e | R | 10,733 | 364 | ---
title: "Multiple Sequence Alignment of GAT201 homologs"
author: "Edward Wallace"
date: "2023-10-10"
output:
html_document:
toc: true
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(readr)
library(dplyr)
library(tidyr)
library(stringr)
library(magrittr)
library(ggplot2)
library(cow... |
4282c2215c3877e8d0e8925689adc8088ec7882d6cd73413d877ebcf85baa0d7 | R | 10,739 | 279 | ---
title: "Total molecule counts"
author: "Po-Yuan Tung"
date: 2016-04-18
---
**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$set(fig.width = 12)
```
Recreate the [Sequencing depth and ... |
8cbee8321f6cf1755c5be3fb843f170280ad55656026faafc573b1191068897d | R | 10,739 | 303 | ---
title: "R Notebook"
author: Sean Maden
output: html_notebook
---
Notebook to perform A/B testing on Sosina et al bulk expression datasets.
Run this from base path on local: sosina_reproducibility_notes/sm_reproducibility_report/
```{r, messages = F}
libv <- c("here", "SummarizedExperiment", "MuSiC")
sapply(libv,... |
3b737110322ff54169997e45010ccafcb958fd7bea9f495dea3a5dc7982d74ee | R | 10,742 | 207 | #Extracting Experimental Design details from Gemma's database
#Megan Hagenauer, July 8 2024
#The Gemma database includes differential expression results for each of the independent variables included in the transcriptional profiling datasets
#We will need to review the design of these differential expression analyses... |
333e95f29d3e8db02ae30439b9497586b040f1cb2ef588dc6e2082dfbae973ef | R | 10,749 | 352 |
Index_PL_ILA_ORB = which(PFC_projection$BrainRegion %in% c("PL", "ILA", "ORBm", "ORBvl", "ORBl") == TRUE)
Index_PL_ILA_ORB_PT = base::intersect(Index_PL_ILA_ORB, Index_PT)
NumNeuron_PL_ILA_ORB_PT = length(Index_PL_ILA_ORB_PT)
pie(table(Label_Subtype_PFC[Index_PL_ILA_ORB_PT]))
## Enrichment analysis ----
pvalue_su... |
b7436dd6f982ab91bd2381168f5f57b91b0add587c15d21eea296d931223dbb1 | R | 10,753 | 289 | long_model_report_stats <- function(meas, hem, trk_sz, dir_in, regions,
beh_names, covariates, stats_sum){
# reports stats for dev_struct_dwi analysis
# specify brain names as output by FS or py(Baby)AFQ
if (meas == 'dti_fa' | meas == 'dti_md') {
if (trk_sz == 'nodes'){
... |
3834f072d05e010a6fbf6930a620a860000b6d037e3f736ae5e856b5ae127ac3 | R | 10,764 | 233 |
cross.study.validation<-function(list.models,
microbiome,
meta,
names.studies,
label="PD",
case="PD",
auc.plot = F,
... |
c98ba542040b87d1932bf2ce6b75ad7d02c577d1c4181f32178ec590b12ca892 | R | 10,802 | 465 | # Patrick Cahan (C) 2017
# patrick.cahan@gmail.com
#' @export
sc_statTab<-function# make a gene stats table (i.e. alpha, mu, etc)
(expDat, # expression matrix
dThresh=0 # threshold for detection
){
statTab<-data.frame()
muAll<-sc_compMu(expDat, threshold=dThresh);
alphaAll<-sc_compAlpha(expDat,threshold=dT... |
dfbb78e89efb4708b166c02ff8b1f528f3646c475bb94fdd850c526e30f54feb | R | 10,888 | 236 |
#This is the main script for nageotte nodule gene expression analysis
#INSTRUCTIONS:
#1) Save Spaceranger filtered matrix h5 files from each sample in a directory, which should have no other contents
# - give the path to this dir to the variable 'inputFolder' below
#2) Save annotated barcode csv files from each... |
c25f8dcd7ac29f134dd1acbc4989b71b59cbcf527ac9b995e01a071eea3299fb | R | 10,920 | 294 |
```{r}
library (Seurat)
library(dplyr)
library(MetBrewer)
library(presto)
library(gplots)
library(RColorBrewer)
library(ggplot2)
library(simspec)
library(SeuratWrappers)
library(tidyr)
library(patchwork)
```
Day16_Matrigel_Nomatrix
```{r}
setwd("~/polybox/Jain_Gut_et_al_2023/4.Day16_Matrigel_Nomatrix/")
... |
c4dfbcaa64c3d8b1da9a480879f19852e76774226b0c67010f7d19f41ff7c4c9 | R | 10,942 | 319 | ---
title: "Violin_AUCs"
author: "SRomano"
output: html_document
editor_options:
chunk_output_type: console
---
# Load packages
```{r}
library(ggplot2)
library(dplyr)
library(ggnewscale)
```
# Load data and metadata
```{r}
meta<-readRDS("/metaG/R_analyses/Taxonomy/RDS/meta.rds")
```
```{r}
# GMM
gmm<-readRDS("/m... |
c082cbd7db5f6a5ca963003e8aee873095d677612a33f9eef9551d0695c18547 | R | 10,959 | 224 | library(sesame)
library(readxl)
library(umap)
library(ComplexHeatmap)
library(ggplot2)
library(tidyverse)
library(SummarizedExperiment)
library(sesameData)
sesameDataCache()
library(pals)
install.packages("gprofiler2")
library(gprofiler2)
install.packages("data.table")
library(data.table)
getwd()
# get experiment info... |
0b12033cecb160534d3ae858c66b86d576f2273a1797d4dd300b87529918da30 | R | 10,961 | 75 | ```{r, load libraries, warning=FALSE, message=FALSE}
library(tidyverse)
library(data.table)
library(RColorBrewer)
library(MetBrewer)
library(plotly)
```
```{r}
setwd("/Users/lindsey/Desktop/Hodges_Lab/ATAC-me\ NPCdiff/NPCDiff_ATACme/New_timepoints/data")
dyn_modC_8dayA<- read_tsv("6l_seq/dynamic_8day_A_intersect.bed",... |
0152e5182ee9961f32ec7f4625077d05b5b6319625b8ccd22a58830b211db5b4 | R | 11,001 | 291 | test_that("testing plot_normalized_counts", {
skip_on_cran()
skip_on_ci()
e <- make_analyzed_experiment()
expect_error(plot_normalized_counts(e,
by = "group",
values = list("Context", "Shock"),
channels = "eyfp",
... |
61ac61ae2efbceaaa4e642af1a570beb97cac8f1d216b558e762f5c06f927e91 | R | 11,004 | 359 | ---
title: "Quality control and PCA of CryptoWakeup RNAseq"
author: "Edward Wallace"
date: "2022-08-31"
output:
html_document:
toc: true
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(cowplot)
library(GGally)
library(here)
library(DESeq2)
library(biobroom)
theme_s... |
5d1b3b33d072481b9196c108a8061c4bd452da3ced2e23840bbc74ac6be76ca0 | R | 11,091 | 265 | # Assess subpopulation distribution among genetic ancestry superpopulations in PBTA cohort
library(tidyverse)
library(ggplot2)
library(RColorBrewer)
library(ggpubr)
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
# Set file paths
data_dir <- file.path(root_dir, "data")
analysis_dir <- file.path(root_dir... |
abb1b06d0e3a48c287c357524e019b747275cef0f36bc5d24b0af1f500ff64d5 | R | 11,092 | 226 | # Purpose: analyze the CD11B+ cell populations
# RUN PIPSEEKER ALIGNMENT AT COMPUTE CLUSTER, WRITTEN IN LINUX COMMAND LINE
# In the following code, file paths have been replaced with ~
# Be sure to substitute for true file locations before running
# The raw FASTQ files used in this analysis are located at E-MTAB-13964... |
095dcda02415a5230f8d975912b298e26d685719a9d77cee47ca185896bf0d2f | R | 11,105 | 388 | # Created on Mon Sep 13 20:41:47 2021
# Name: glomerulus_ranking_scan_top.R
# Purpose:
# Author: Andrea Vaccari (avaccari@middlebury.edu)
#
# Generates:
# - ...
#
#
# Copyright (c) 2021 Andrea Vaccari
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General P... |
fbb22d26f808b93f7c6f2277bf70603cfa2e47a327863b04ddd4752e2955cd96 | R | 11,138 | 199 | #There are four biological replicates:P0_CD133_RGC_Droplet, P5_CD133_RGC_Droplet, P0_CD133_RGC_Droplet_rep and P5_CD133_RGC_Droplet_rep.Here P0_CD133_RGC_Droplet_rep file was used as an example.
#1 Building the genome index of mm10
STAR --runThreadN 20 --runMode genomeGenerate \
--genomeDir STAR_index/mm10/ \
--genome... |
56ae5de9b0932d158595083ceabcbe33313996fdb5a43e918a6cdf0945952eb1 | R | 11,171 | 368 | ---
title: "Proportion of genes detected"
author: "Joyce Hsiao"
date: 2015-09-01
---
**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")
```
## Setup
```{r}
source("functions.R")
library("limma")
libr... |
2baf2a9547707d42d4ee0a0ce02d212f122b6e0e905e13e88025fa2fe5a96248 | R | 11,178 | 331 | # Created on Tue May 11 18:04:27 2021
# Name: glomerulus.R
# Purpose: Evaluates the spatial separation of synapses within the corresponding
# glomerulus
# Author: Andrea Vaccari (avaccari@middlebury.edu)
#
# Generates three plots:
# - one 3D plot showing the location of the synapses for the two posts, the best
# ... |
cd0bc579b93126bd9702c34fce6b17a5a493df07fe0acbff9dd23a0505950b93 | R | 11,181 | 391 | # rank correlation analysis below adapted from ML's original version found here: https://gitlab.oit.duke.edu/dcibioinformatics-internal/projects/anders-mbm-rnaseq-wxs/-/blob/master/figures/Figure2_rankCor.R?ref_type=heads
sif=/mnt/data1/public/singularity/dcibioinformaticsR-v2.1.sif
dir1=/mnt/data1/workspace/Anders/Me... |
87fab30883fbec8828413f1d6f970b4ec79a1d093038210ae489be143579a570 | R | 11,232 | 328 | ---
title: "Capture efficiency"
date: 2015-08-10
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, message=FALSE}
source("chunk-options.R")
library("edgeR")
library("ggplot2")
theme_set(theme_bw(base_size = 14))
```
Here capture efficie... |
ba96990c55887a5e046323f5ea6e58e676f92de5909c0ef08ba10a4bc9acf65f | R | 11,235 | 388 |
library(tidyverse)
library(clue) # hungarian
# clean everythign up.
rm(list=ls())
source("eyemap_func.R")
# main loop -----------------------------------------------------------
# load position data, match lens to cone/tip to compute directions
# smooth positions and directions (almost redundant)
fn <- c('202407... |
239b157b721b3c5d94728c9632a716e26ab4732b6065418b7921945f5947096e | R | 11,248 | 219 | ##########################
### Response time #####
##########################
### Predicted RT when craving is centered on the mean
predRT <- predict(mod_activity_meancravsed)
predRTsstimInact <- predRT[mod_activity_meancravsed@frame$Stimuli_activityVS == "inactivity"]
predRTsstimAct <- predRT[mod_activity_meancravsed@... |
dc0dc7152d2b015147aa90382fd2f1c218cbae045c485fe7a57665980b8b7c30 | R | 11,259 | 295 | ---
title: "Normalize coefficients of variation"
author: "Joyce Hsiao"
date: 2015-10-15
---
**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, warning = ... |
4d31c2d7796bcb393c7f25ecc39ac28fc536db64c069f0bbf098a07daadacfeb | R | 11,400 | 205 | ### Section Randomization testing
### Code by Joel Swift 06/2025
library(tidyverse)
library(readxl)
library(emmeans)
library(ggpubr)
library(lmerTest)
# Set theme
theme_set(theme_bw())
#### 1) Load data and calculate derived areas and percentages ####
section_data <- read_xlsx("Section_data_plus_metadata.xlsx", shee... |
01238c4e0bdd000d71629d3ff7531a358576cde1c5256df81e12920283adcdea | R | 11,403 | 347 | library(tidyverse)
library(filenamer)
library(tidyverse)
library(plotly)
library(Rtsne)
library(fpc)
library(dplyr)
library(cluster)
library(umap)
################## START OF FUNCTION ###################
#Functions takes name of csv file and returns processed data frame where it can select what type of patient (ASD, A... |
93f9b60cdbd0789e712d2dee45625d1a5d1b4d60cde396eb81594c17b165d8aa | R | 11,403 | 361 | # Created on Wed Jun 29 18:33:41 2022
# Name: clustering_spatial_bias.R
# Purpose: Evaluated the quality of the VPN clusters created in the cluster
# analysis step
# Author: Andrea Vaccari (avaccari@middlebury.edu)
#
# Generates:
# - Dendritic maps showing the locations of the centroids of each of the
# ... |
74d557aa74a2efe6fbe05a7879119d7fc0462ba6d051751245cc6984a0f9304d | R | 11,408 | 378 | # Created on Sat Sep 25 12:30:41 2021
# Name: glomerulus_ranking_multiple_planes.R
# Purpose: Evaluates the distance matrix of the centroid evaluated in
# glomerulus.R. The distance is evaluated for each pair according to
# the optimal separating plane for that pair.
# Author: Andrea Vaccari (ava... |
eabbc4ed3fc61c036e6a980b5756768109580fad2916567a41f180e0a53edd44 | R | 11,429 | 305 | ---
title: 'Assess pLGG survival by BRAF fusion breakpoint fusion type in PBTA ancestry cohort'
output:
html_document:
toc: TRUE
toc_float: TRUE
author: Ryan Corbett
date: "2024"
---
Load libraries and set directories
```{r load libraries and set directories}
library(data.table)
library(tidyverse)
library(su... |
a2d1cf6eb6555f2d12a22636dfb9f1269367c463a72a8f46fee65ac057dab093 | R | 11,527 | 323 | ---
title: "Profile individual adjusted CVs"
author: "Joyce Hsiao"
date: 2015-10-29
---
**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, warning = FALS... |
c9127b0069d01bf282ea110153ec1b41ec9fab395c07ddd759bc59261743e480 | R | 11,540 | 381 | ---
title: "Compare high/low-CV genes between individuals"
author: "Joyce Hsiao"
date: 2015-10-26
---
**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, ... |
8c40e8cbb3eadb53f740acb5ed4b54fc3bc040be0a8d7ef702f57a5d825294f6 | R | 11,581 | 282 | library(tidyverse)
library(plyr)
library(arrow)
library(survival)
library(broom)
library(caret)
library(stringr)
r_pretty <- function(l) {
return(str_replace_all(l, "[^[:alnum:]]", "_"))
}
args <- commandArgs(trailingOnly = TRUE)
print(args)
multimorbid_acmort_input_type_ind = args[1]
print(multimorbid_acmort_input... |
fcf9a06826505ad25cf00da7e2a28f5323d0e240e6da31fafbc97ab05df139bb | R | 11,600 | 322 |
```{r}
library (Seurat)
library(dplyr)
library(MetBrewer)
library(presto)
library(gplots)
library(RColorBrewer)
library(ggplot2)
library(simspec)
library(SeuratWrappers)
library(tidyr)
library(patchwork)
```
```{r}
setwd("~/polybox/Jain_Gut_et_al_2023/5.Control_YAP_Day16_scRNAseq/")
Day16_Control_YAP1 <- readRD... |
68f660d9e163887d46d26679252036f18512a75edcf271d2b8bad6f403b3496a | R | 11,602 | 87 | ```{r, load libraries, warning=FALSE, message=FALSE}
library(tidyverse)
library(data.table)
library(RColorBrewer)
library(MetBrewer)
library(plotly)
```
```{r}
setwd("/Users/lindsey/Desktop/Hodges_Lab/ATAC-me\ NPCdiff/NPCDiff_ATACme/New_timepoints/data")
dyn_modC_8dayA<- read_tsv("6l_seq/dynamic_8day_A_intersect.bed",... |
3b0781dd1706791121655116d4ff652d6bef2345ef4bf63212c8dc0c1dae13bb | R | 11,632 | 414 | #' Calculate angle difference in degrees, respecting angles <0 or >360.
#'
#' @param target_ang Angle
#' @param ref_ang Reference angle
#'
#' @return Difference in angles in degrees
#' @export
#'
#' @examples
angle_diff_deg <- function(target_ang, ref_ang) {
((target_ang - ref_ang) + 180) %% 360 - 180
}
#' Calculat... |
80b8145dc1ee27759eb217ee10c2106414441133fe7794dd0db33fb27637478a | R | 11,638 | 321 | ---
title: "Proportion of gene detected after filter"
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")
```
The purpose is to see if removing the lowly expr... |
586fe3280a32b2846220224e139f92b9f9fe583c7a149868a6798f39a67b828a | R | 11,642 | 191 | #Generate HR, RR z-scores
library(rriskDistributions)
library(tidyverse)
### Do HR, RR correction
#Tables from Fleming
age = c(0.25, 0.5, 0.75, 1, 1.5, 2, 3, 4, 6, 8, 12, 15, 25)
RR_cutoffs <- data.frame(age,
first = c(25, 24, 23, 22, 21, 19, 18, 17, 17, 16, 14, 12, 11),
... |
6f5eff57dac6d22350827e63a6e79f6d17c0a14880c921a6c6fa9c20af9d2d86 | R | 11,674 | 231 | ---
title: "Experiment Output Data Structure"
author: "Jack Brookes, Dominik Bach"
date: "11/01/2021 - 07/12/2022"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Experiment Output Data Structure}
%\VignetteEngine{knitr::rmarkdown}
\usepackage[utf8]{inputenc}
---
```{r setup, include=FALSE}
kni... |
646491834acea9887b11f0882be55e7d219461bc3e11f13656ef746fd7e02f92 | R | 11,675 | 386 | ---
title: "Compare CVs between individuals, remove PCs"
author: "Joyce Hsiao"
date: 2015-10-26
---
**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, wa... |
b41509114750e17cc0a867c6a065f1992289aac92eee219c23d84632d14c1a12 | R | 11,682 | 355 | #' @export
#' @import methods
#' @import GGally
#' @import reshape2
#'@title PlotFeature
#'@description a function that takes in input a BundledExperiment
#'and a feature name. Returns the expression values of that features
#'along the bundled experiment.
#'@param be an object of class BundledExperiment
#'@param f a ... |
f51011b195e0d194fbfc28713804c3a1ae7d2323c9c88cd70d9a66b1f4e175b9 | R | 11,741 | 285 | #Example: Running a fancier meta-analysis - controlling for co-variates/additional predictor variables
#Megan Hagenauer
#2022-08-03
#This code assumes that you have already run the beginning of the code for a basic meta-analysis from the code document:
#Example_MetaAnalysis_GemmaOutput_ComparingDatasets_DebuggedMaybe.... |
09a6556138641ed9059cfe36ac66902c2f0a387eaede6608844b32d11a86eeb4 | R | 11,786 | 271 | ---
title: "Checking on cell-cycle genes"
author: "Joyce Hsiao"
date: 2016-04-226
---
**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")
```
## Objective
Examine the cell-cycle gene set that went i... |
a5444fc03044fff108bc8e8cc39ea7b1991db39c5ac4d5222d1bac29947a63fa | R | 11,796 | 346 | ---
title: "Figures DA"
output: html_document
editor_options:
chunk_output_type: console
---
# Load data
```{r}
library(ggplot2)
library(dplyr)
l_df<-readRDS("/metaG//R_analyses/Taxonomy/RDS/l.df_g_TSS.rds")
meta<-readRDS("/metaG//R_analyses/Taxonomy/RDS/meta.rds")
df.cross<-readRDS("/metaG//R_analyses/Taxonomy/RDS/... |
c42b29b99fcb1b4e56f7a7e95285482626ea5889e1adcc0a9624b8813212b465 | R | 11,842 | 337 | library(BayesFactor)
library(dplyr)
############################# load data
# Load
data <- read.csv('AnalyseSSVEPs/Results/SSVEPsresults.csv')
head(data, 5)
# subselect data to analyse
data <- data[(data$flickertype == 'interpflicker') & (data$freqrange == 'lowerfreqs')& (data$harmonic== 1),]
data$Group <- ... |
169d03a9290fc6377ee5e658e45717896bf5a4b412f11ad0aeb438e31a861e6a | R | 11,868 | 282 | ---
title: "Verify md5 checksums of downloaded fastq files"
author: "John Blischak"
date: 2015-05-20
---
**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")
```
## Missing files
When performing [QC by... |
4f3a376cb8c35226e917a331e38af6b9670d1e798a03fda1449a090e733c7fbb | R | 11,900 | 299 | ---
title: "Total counts"
author: "John Blischak"
date: 2015-04-22
---
**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$set(fig.width = 8, fig.height = 8)
```
During the [processing pipel... |
2b13342693b6d2480db4c6b5f84b55257ea31ae9d2bf9b500e4c96d5645372a1 | R | 11,917 | 436 | # for TSP-RF
# (C) 2018 Patrick Cahan
#' enable cross-species comparison
#'
#' rename and subset query expDat to orthologs in training data
#'
#' @param expQuery expQuery
#' @param expTrain expTrain
#' @param orthTable orthTable
#' @param speciesQuery speciesQuery default human
#' @param speciesTrain speciesTrain de... |
9d3767b1ec69bf13d00ab699ad30444be08db4ba3a11d9cd0758a6a2a94c7384 | R | 11,946 | 401 | ---
title: "Real bulk results"
author: "Sean Maden"
date: "2023-09-21"
output:
pdf_document: default
html_document: default
---
Deconvolution on real bulk samples.
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
libv <- c("dplyr", "ggplot2", "GGally", "gridExtra")
sapply(libv, library, character.on... |
eb5d623734711907d0066ae7592cc1d08ed21ac9e43eebb33312876b34db2b6e | R | 11,972 | 210 | ---
title: Assessment of single cell sequencing rapid run
author: John Blischak
output: html_document
---
Last updated: `r Sys.Date()`
Code version: `r system("git log -1 --format=oneline | cut -d' ' -f1", intern = TRUE)`
## Data processing
```{r setup, include=FALSE}
library("knitr")
opts_chunk$set(tidy = FALSE, f... |
72ec0aca4e9e52347420907bccd79bb3a1fa2fadee181ea7379c08b7ce0e9ee6 | R | 11,988 | 299 | # FindMarkers, calculate All differential expression genes between Inulin_AD and Ctrl_AD in each cell type in interbrain
# run GSEA: GO-BP, REACTOME, KEGG
remove(list = ls())
library(dplyr)
library(Seurat)
library(patchwork)
library(ggplot2)
library(DoubletFinder)
library(sctransform)
if(!require(AnnotationDbi))BiocMa... |
eb302c817dcc70581613912d776c8c878ceef0b10d53bb45fb717abdfaa1fb70 | R | 12,043 | 238 | ---
title: "scisorATAC: standard workflow"
author: "Wen Hu and Careen Foord"
date: "`r Sys.Date()`"
output: pdf_document
vignette: >
%\VignetteIndexEntry{scisorATAC}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment ... |
db4a0dac479c2025c5cc338d947d64b60dd2ef515c41ab54a082a829d74c9642 | R | 12,053 | 406 | # Created on Sat Jul 17 20:11:24 2021
# Name: glomerulus_distances_ranking.R
# Purpose: Selects the top n (number of synapses) post for a given pre and
# evaluates the median of the distances between all possible pairs
# formed between any of the posts synapses.
# This is similar to the av... |
da65d6dbe2f96b42d3ffbf282697c0c32578c29f131d966e9e426d373f129ada | R | 12,073 | 380 | require(goseq)
require(methylKit)
require(ggplot2)
require(genomation)
require(dplyr)
require(ggfortify)
require(gplots)
## FUNCTION NECESSARY TO PREP THE FILES
makeList <- function(vec) {
len <- length(vec)
out <- as.list(rep(1:len), len)
for (i in 1:len){
out[i] <- vec[i]
}
out
}
... |
91310a227895940af54b9eed75f9f3bca55bcb669acb90d92b84be0803e8524c | R | 12,087 | 319 | ####----- Coefficient of variation related functions -----####
#' Subsample molecule count (or read count) data
#'
#' @param counts Count matrix of gene by cell.
#' @param anno Annotation matrix labeling each cell according to individual,
#' batch, replicate, well ID, etc.
#' @param subsample_size Number of cel... |
6b83b3b76288424b3a0073e21c0a8c248e5fca4ec25f697eda0b2b74800e302c | R | 12,088 | 291 | ---
title: "ERCC cpm?"
author: "PoYuan Tung"
date: 2015-09-07
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
We standardize the molecule counts to account for differences in sequencing depth.
This is necessary because the [sequencing depth affects the to... |
c506555c1397bd4803def64007f92035e55e2d09ae5f9a8ab213d4809b7d0cc5 | R | 12,092 | 157 | ---
title: "1. Imaging, segmentation, and preprocessing"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Segmentation}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
options(width = 300, rmarkdown.html_vignette.check_title = FALSE)
kni... |
e5a6d86a25aec199b213e6405844a72fd011fe5ce4bf2d3633c5cee74867b413 | R | 12,094 | 182 | #!/usr/bin/env Rscript
options(stringsAsFactors=F)
## load R libraries
#library(SAIGE, lib.loc="../../install_dir/0.38")
#library(SAIGE, lib.loc="../../install_dir/0.36.6")
#library(SAIGE, lib.loc="/net/hunt/zhowei/project/imbalancedCaseCtrlMixedModel/Rpackage_SPAGMMAT/installSAIGEFolder/0.44.6.3_onlyRunSingleJobsinS... |
aad8ca69d03660f7cab6779fbcc771d84704e631ed4aeca2226bd7fc203e8cd4 | R | 12,102 | 315 | ############################################
### Goal: Plot and analyze behavioural data
### Author: Janay Fox
### R script
############################################
## Set up ##
#install packages
#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages("forcats")
#install.packages("reshape2")
#ins... |
1be8f45df85618cb299345bd7a268fb72f92362568ff024bff00b9c8997c9bf9 | R | 12,136 | 212 | ---
title: "SMARTTR"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{SMARTTR}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
options(width = 300, rmarkdown.html_vignette.check_title = FALSE)
knitr::opts_chunk$set(
collapse = TRUE,
... |
873b99d5923058adbe98259aee7b9776cdc939b0dd2864838bfba3d702d51d6e | R | 12,181 | 406 | #' Generate position list
#'
#' This helper function takes a scenario hierarchy object containing values for
#' `position` and `euler_angles`, and combines these into a standardised
#' position/rotation list usable for other functions.
#'
#' @param scenario_object
#'
#' @returns A list with 6 items, `"pos_x"`, `"po... |
c661952bb7a9a673ecaec9c5b2e523e35fa78f57a9b058496be089726ae68302 | R | 12,192 | 340 | ---
title: "Process sequence data"
author: "John Blischak"
date: 2015-04-11
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
All processing scripts were run from the data directory.
```bash
cd /mnt/gluster/data/internal_supp/singleCellSeq
```
The raw fast... |
d9df8cf1ce05481253a1e1b503e8c5a7ed9f5e3e51f6cf22910d90ec7f44175e | R | 12,200 | 331 | # Libraries
library(Rmisc)
library(broom)
library(jsonlite)
library(psych)
library(report)
library(tidyverse)
library(jmv)
# Set paths
workdir = Sys.getenv("HOME")
basedir = file.path(workdir, 'climate-brain')
bidsdir = file.path(workdir, 'ds005460')
setwd(file.path(basedir))
# Output directory
output_dir = "./ou... |
ca2bdc0990a2b88592100a71d4e21564f1668131c0606450fabd14cedd296289 | R | 12,222 | 305 | # FindMarkers calculate All differential expression genes between Inulin_AD and Ctrl_AD in each cell type in interbrain
# run GSEA: GO-BP, REACTOME, KEGG
remove(list = ls())
library(dplyr)
library(Seurat)
library(patchwork)
library(ggplot2)
library(DoubletFinder)
library(sctransform)
if(!require(AnnotationDbi))BiocMan... |
f488b4e0e89e93c7c2e2d1bb53eeb9e77d9ecf5c0073b6791130773a795e422a | R | 12,237 | 316 | #' Replace Redcap id in questionnaires by VR ppid
#'
#' Replaces the Redcap record id of the questionnaire data by the ppid of the VR data.
#' Removes records of participants that did the questionnaire several times or didn't do the VR study.
#'
#' @param df raw questionnaire data frame
#' @param redcap_ppid_map redcap... |
61c7083812aa011d188e0793478d58b8eea19171516760fafb801212bca0cd53 | R | 12,260 | 366 | # Filter and plot pathways enriched in each cluster (regressed for variables, comparing clusters with each others)
# input data
# - .tsv files with enriched pathways
# - top_match_between_IMC_to_RNA_clusters_original.csv (generated in 9. RNAseq_IMC_clusters_matching.R)
#### 0. Load packages #####
#install.packages("... |
f850b2ba910b5925a73f9da9a0f6c11ce2d501a6ba6608460d1d95ea7d45d914 | R | 12,279 | 347 | ---
title: "BASiCS - 4,000 iterations"
date: 2015-08-10
---
**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")
```
We analyzed our single cell data with [BASiCS][] developed by [Vallejos et al., 2015]... |
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