sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
351fcad53238df7250ddff3833aff7afa8f584b225833d922f4c14d734d66aa8 | R | 1,762 | 60 | #this code calcuates raw PCC coexpressiox network and write to file
library(Seurat)
library(parallel)
library(doParallel)
setwd('/home3/junhacha/HumanNetv3/Benchmark/rawPCC/')
data <- read.table('/home3/junhacha/HumanNetv3/Benchmark/BC_countdata_EC.tsv', sep = '\t', header = T)
cell.type <- 'EC'
seurat <- CreateAssa... |
b90f78dac48953fb8c6550d2a237a278344fb29932e1ee5977fefc56d721f9b0 | R | 1,783 | 73 | #' Back trace the expressions evaluated when an error was caught
#'
#' @param future A future with a caught error.
#'
#' @param envir the environment where to locate the future.
#'
#' @param \ldots Not used.
#'
#' @return A list with the future's call stack that led up to the error.
#'
#' @examples
#' my_log <- functio... |
fe2357afca1a8d0dc317a8a82c75b3ce8c94b4f34b28bdeb8de7d927ececd164 | R | 1,784 | 64 | #srun --cpus-per-task=1 --mem=50gb --nodes=1 --qos=priority --time=168:00:00 --pty bash -i
#remoter::server(verbose = T, port = 55556, sync = T)
remoter::client("localhost", port = 55501)
setwd("/groups/umcg-fg/tmp01/projects/genenetwork/recount3/")
sraFiles <- list.files(path="rse-sra/SRA_Files/", pattern="sra... |
93b14af21e02ccabfdc13b81e61d5b971cfec62d3511db05782f65e0f47f8e73 | R | 1,785 | 35 | library(SnapATAC)
library(Matrix)
args = commandArgs(trailingOnly=TRUE)
input_dir <- args[1]
output_dir <- args[2]
# Older version
# for (sp in c("2C", "3C", "4B", "5D")) {
# x1.sp <- createSnap(file=paste0(sp, ".snap"), sample=sp)
# x1.sp <- addBmatToSnap(obj=x1.sp, bin.size=1000)
# write.table(data.frame... |
2d0fb57d13d85f05b0b3ae72455f8682e0544046aa6ef6e3e66e934b4a777ddd | R | 1,795 | 70 | #######################################
# R script to read outputs from RACCOON
# J. O. Nash @2022
# F. Comitani @2022
#######################################
open.h5<-function(file){
#This function reads in an hdf5 file
#
# args:
# file (hdf5), path to the hdf5 file to read
# return... |
fddfc2a9e750a7d814b21c2539d159a2856687fd3f85a3b52953e211d330636c | R | 1,799 | 54 | #' Rebuild the index
#'
#' Rebuild the index (or indices), typically after restarting the R session.
#' This is because the indices are held in external memory and are not serialized correctly by R.
#'
#' @param trained List containing the output of \code{\link{trainSingleR}},
#' possibly after some operations that inv... |
137d472295d78151c8b04f3e49f5b2fa5587f577ffbb7c12d9e49e5ad892261d | R | 1,804 | 40 | x <- read.table("~/Desktop/depict2/output/maf_filtered/v51/height_2018_30124842_hg19_genePvalues.txt", header=T, row.names=1)
y <- read.table("~/Desktop/depict2/output/height_paper/height_2018_30124842_hg19_genePvalues.txt", header=T, row.names=1)
x[,1] <- -log10(x[,1])
y[,1] <- -log10(y[,1])
coreg.x <- read.table("~/... |
8ac08b513aa849d597ce1d5b5a1b00578671e2a48acce55291046b838f2c903f | R | 1,820 | 44 | #' calcInt
#'
#' calculates the summarized data over the time points in each interval
#'
#' @param x data frame
#' @param varname character, new name for column
#' @param groupingVar character, variable to group by before summarizing
#' @param intVar character-column name for intervals
#' @param intervals character vec... |
f4fe8a577e4f8ce7933ab80ceae140a7701230c32eeb5f0504ba462b8966984a | R | 1,821 | 77 | #' Function to write a network
#'
#' @param fName: file name
#' @param network: network definition
#' @param rule: "ID" or "MR" (currently only works for ID)
#'
#' @return success
writeNetwork <- function(fName, network, rule= "ID"){
#TODO: writeNetwork currently only works for rule = "ID"
#should be implemente... |
89218537b6fee32b305343d8d977dc61555b3cc5785790e3bcc5e5d0d625257f | R | 1,824 | 70 | library(minet)
library(reticulate)
library(ggplot2)
library(RColorBrewer)
np = import("numpy")
####============================================================================
#### Set directories
####============================================================================
# args = ... |
d975d4f6953d4528c5e616bb52fd620304b2b3ed0acab5d1eb841db91ec97bf8 | R | 1,826 | 63 | #remoter::server(verbose = T, port = 55556, sync = T)
remoter::client("localhost", port = 55001)#55556 55501
setwd("/groups/umcg-fg/tmp01/projects/downstreamer/depict2_bundle/")
library(readxl)
read.depict2 <- function(path, potential_traits=NULL) {
if (is.null(potential_traits)) {
potential_traits <- ex... |
3b5c407e30a571f4b4af320e1fcfc0198dd39fadb33a8903b84e9a1f53e0ce72 | R | 1,832 | 60 | #' @tags utils-internal cluster
library(future)
registerClusterTypes <- future:::registerClusterTypes
makeClusterPSOCK_args <- future:::makeClusterPSOCK_args
message("*** registerClusterTypes() ...")
## The 'FUTURE' cluster type is registered when the package is loaded
stopifnot(identical(future:::FUTURE, "future::... |
24bfafc193347523ecccc4c4f44dc2661476628fd252a3cb4b4212638ac57c04 | R | 1,833 | 67 |
## Marioni, R. E. et al. Translational Pscyh. (2018).
library(MungeSumstats)
library(tibble)
library(tidyr)
library(readr)
library(purrr)
library(plyr)
library(dplyr)
library(stringr)
library(forcats)
library(tabulizer)
library(fuzzyjoin)
## Misc functions
calc_se_from_beta_and_l95 = function(or, l95){
logOR = log... |
9409c50eef0226e853ab912b90ff9a1c6b46bf30cd3d5ea8970f77a6dc0b94d6 | R | 1,837 | 56 | #' @tags globals reserved-keywords
#' @tags sequential
library(future)
options(future.debug = FALSE)
plan(sequential)
message("Overriding reserved keyword functions ...")
## Identify globals used by the expanded future expression
...names <- globals::findGlobals(getExpression(future(NULL)))
...names <- ...names[sapp... |
6a69af942d2ce977dc79e540d915e208da7e75a537127a5add6ba06268406f1c | R | 1,848 | 56 | library(ggplot2)
library(grid)
library(gridExtra)
library(reshape2)
# Figure 2A
plotx <- read.table(plotx, "SourceData/Figure_2A_Source_Data.txt", sep = "\t", header = T)
p1 <- ggplot(plotx[which(plotx$Data == "SAMPLE_NUM"),], aes(Tissue, Number, fill = Tissue))+
geom_bar(stat = "identity")+
coord_flip() +
scal... |
61d744bcf71fdbfa9310f3207d2aad1bb64bff47cf56ed40fccfd04b1df0f885 | R | 1,850 | 53 | # first, compare site model with a fraction of proteins with omega>1 with a null model
setwd("/data/share/htp/TRNP1/paper_data/")
system("bash protein/scripts/summarise_PAML_out.sh")
m8_vs_m7_trnp1<-read.table("protein/PAML/M8_vs_M7.txt", sep="\t") %>%
distinct() %>%
mutate(lnL=word(V3,7,7, sep=" "),
p0=... |
49da8d263a63e7849bc647bab3f74153112a319b6dd53df3a6493bb0d310af7e | R | 1,851 | 52 | # Disclosures of Conflicts of Interest
- Raniere Gaia Costa da Silva: No relevant relationships.
- Ambika Prasad Mishra: No relevant relationships.
- Michael Doube: No relevant relationships.
- Christopher Riggs: No relevant relationships.
# Acknowledge
We thank Dr. Anil Prabhu, Vincent Y. T. Tang, and Voss ... |
04921c6e802b80be06505164b2f38ab25c74b92839204cd3cce3498c06c5e532 | R | 1,859 | 46 | rm(list = ls())
library(igraph)
library(parallel)
load("/work/lulab/Ben/distmat/NEWMAN_SUBSAMPLING/inception/input/combos.list")
load("/work/lulab/Ben/distmat/NEWMAN_SUBSAMPLING/inception/input/ks.dist.mat.all.complete")
get.average.distance <- function(combos){
tmp1 <- names.list[[combos[1]]] #this is id of batch an... |
f60b53cc4c6dc541d26bdf39e6a4003ee6b0818060c20cb9a4770d24268aa6ac | R | 1,879 | 51 | # Note: we can only lookup symbols that are available in the installed version of libcurl
# Therefore you should only update the symbol table using the latest version of libcurl.
# On Mac: 'brew install curl' will install to /usr/local/opt/curl
blacklist <- c("CURL_DID_MEMORY_FUNC_TYPEDEFS", "CURL_STRICTER")
# Functi... |
30cfb550ad50bfd0a124d580a75d50edc18a2646b7f0445194f5c25ec49b4294 | R | 1,880 | 34 | library(ComplexHeatmap)
library(ggplot2)
library(matrixStats)
for (f in list.files("./", "*feature_ranks.csv")) {
print(f)
data <- read.table(f, header=T, sep=",", stringsAsFactors=F, row.names=1)
print(dim(data))
data <- as.matrix(data[rowSums(abs(data) > 0) >= 2,])
print(dim(data))
annotatio... |
b0638ceb658630d24bba9914d758576b8e91da00994abd90b8be969a183238d3 | R | 1,883 | 81 | ```{r}
library(nlme)
custom.gls <- function(x, y, Sigi) {
x <- as.matrix(x, ncol=1)
# Calculated beta on pre-computed inverse matrix
# xtxi = b1
xtxi <- solve(t(x) %*% Sigi %*% x)
# part between brackets is b2
beta <- xtxi %*% (t(x) %*% Sigi %*% y)
# Calculate SE
res <- y - (x %*% beta)
... |
9a1f22ad84da9cac66985c4a59e9968c751f182c1b82ed4cc1a2b2ccd09911b6 | R | 1,890 | 55 | ```{r}
library(qqman)
source("downstreamer_functions.r")
setwd("gwas_simulations")
source("data/source_olivier.r")
files <- list.files(simulated.sumstats.path, pattern="*assoc.txt.gz", full.names = T)
curstats <- fread(paste0("zcat ", files[1]), data.table=F)
rownames(curstats) <- make.names(cur... |
2b5798c31ade7857e8a4ccbdc349463230c14d95a662c2d713ad1a808a235112 | R | 1,901 | 60 | #' @tags interrupt
#' @tags detritus-files
#' @tags sequential multisession multicore
library(future)
options(future.debug = FALSE)
strategies <- supportedStrategies()
## IMPORTANT: Skip when testing with 'covr', because value() cancels the
## still-running futures when one of them fails, which terminates their
## w... |
b768acafba0d76f8e2f7372d7f64b09579470ab9a9f620d663e7f252cda9f1d5 | R | 1,904 | 63 | library(Biostrings)
library(stringr)
library(tidyverse)
library(plyranges)
library(foreach)
library(doParallel)
prot_seqs_sp <- list.files("protein/other_protein_alignments/self_matches_fa", recursive = T, full.names = T)
#for the cases where multiple sequences were matching equally good, count different positions... |
edd084f454fc16a9685a6d9c97538a4e8a73f1cd7fe01bcbb1d37fbba23deab0 | R | 1,907 | 58 | ##
## Generate a heatmap for a matrix of values with specified genes/rows and samples/columns.
##
plot_heatmap = function(mat, row_subset, col_subset, title, file_prefix = "plot.heatmap") {
library(glue)
library(pheatmap)
# confirm that the subsets exist in the full matrix
row_subset = intersect(row_subset... |
bafbd1eb9247f6f6b9623c3fd0bcbadedc103b0db829d80cefda825224568b4e | R | 1,908 | 72 | ```{r}
setwd("evaluating_pathway_predictions")
source("../downstreamer_functions.r")
source("data/source_olivier.r")
# Read excel files
path <- "/home/work/Desktop/depict2/output/final_paper/excels/"
files <- list.files(path, pattern=".*_enrichtments.*.xlsx")
datasets <- list()
for (file in files) {
name <- gsub("... |
cb596f79c69649d56786f32676c37dabc196e0de46682245b9743275f26b8c07 | R | 1,919 | 51 | # This tests that pruneScores works as expected.
# library(testthat); library(SingleR); source("test-prune.R")
test_that("validating per-cell check without finetuning", {
scores <- rbind(
c(0,0,0,0,1),
c(0,0,0,1,1),
c(0,0,1,1,1),
c(0,1,1,1,1),
c(1,1,1,1,1)
)
colnames... |
00d2a08889e437b1bfc2f1d73f0288e2a220c49db60481dd66274bbb38814e26 | R | 1,931 | 97 | # Resources requested:
#$ -l h_data=2G,h_rt=00:30:00
#$ -V
# Email address to notify
#$ -M user@mail
#$ -m a
rm(list=ls());
suppressMessages(library(GOstats,quietly = T))
suppressMessages(library(org.Mm.eg.db,quietly = T))
# options(echo=TRUE)
options(stringsAsFactors = FALSE);
onts<-c("BP","CC","MF")
MMthreshs<-... |
2cd635178151c0c5e40f2d9c3f2aa57167d33ace566a1d5df0c795bab15bc6f0 | R | 1,932 | 58 |
#remoter::server(verbose = T, port = 55556, sync = T)
library(pbdZMQ)
sessionInfo()
remoter::client("localhost", port = 55506)#55501 55556
genes <- read.delim("/groups/umcg-fg/tmp01/projects/genenetwork/recount3/genes_Ensembl94.txt.gz", check.names = F)
str(genes)
#Ensembl Gene ID Chromosome Name ... |
5e2e89463cc54e8f7e4e0053319d444791385f0be4147b7f8b52c6d95d899a29 | R | 1,937 | 77 | # Annotate with Nearest Gene
## Nearest protein-coding gene according to GENCODE release 40
library(dplyr)
library(tidyr)
library(purrr)
library(janitor)
library(tibble)
library(glue)
library(stringr)
library(readr)
library(forcats)
# library(rtracklayer)
# Snakemake
## Input
path_snps <- snakemake@input[["snps"]]
pa... |
994cda0d87cb3c421353c738d0445c450e49c26cfeeec0eb6b0cd973aa52fecc | R | 1,952 | 75 | with_assert <- function(expr, ...) {
invisible(expr)
}
prune_call <- function(expr, name) {
if (!is.call(expr))
return(expr)
expr <- unclass(expr)
fcn <- expr[[1]]
if (!is.symbol(fcn))
return(expr)
if (as.character(fcn) != name)
return(expr)
NULL
}
prune_debug <- function(expr) {
if (!is... |
3770667b480ef32ee866dd17da105af223b57e58a73482f35315e1f291fa8cef | R | 1,955 | 66 | #' @tags interrupt lazy
#' @tags detritus-files
#' @tags multisession multicore
library(future)
options(future.debug = FALSE)
strategies <- supportedStrategies()
strategies <- setdiff(strategies, "sequential")
## IMPORTANT: Skip when testing with 'covr', because value() cancels the
## still-running futures when one ... |
fe5d06fc52c97b0e41da650dcc1edbd4dd8c147898af9d6d526d5be1c6002e70 | R | 1,971 | 63 | #remoter::server(verbose = T, port = 55556, sync = T)
remoter::client("localhost", port = 55556)#55556 55501 55504
setwd("/groups/umcg-fg/tmp02/projects/downstreamer/depict2_bundle/")
library(readxl)
read.depict2 <- function(path, potential_traits=NULL) {
if (is.null(potential_traits)) {
potential_traits... |
dd278e33efde48a78a7a31fd3d339853b141ac23f5fb1ae266b6fbc617fd19e1 | R | 1,972 | 61 | #' Functions Moved to 'parallelly'
#'
#' The following function used to be part of \pkg{future}, but has since
#' been migrated to \pkg{parallelly}. The migration started with
#' \pkg{future} 1.20.0 (November 2020). They were moved because they
#' are also useful outside of the \pkg{future} framework.
#'
#' _If you are... |
6cd9b10482920f3fbc92ad556694fcfbcd1b49c542c2151661a95f11f2754e59 | R | 1,974 | 43 | #' Class "galamm"
#'
#' An S3 class for objects returned by [galamm()].
#' Contains information about the fitted model, random effects, parameters, and
#' smooth terms.
#'
#' @section Components:
#' * `call`: the matched call used when fitting the model.
#' * `random_effects`: a list with:
#' * `b`: random effects in... |
549f32260301a18db5000a8190c0a719c1785406643a2fc01629d0eb4cd5ad50 | R | 1,987 | 40 | library(sRACIPE)
if (!file.exists("/projects/lu-lab/BenStuff/research/projects/oldhome/scripts/networks/clustscore/output/scorelistNUMBER1")){
load("/projects/lu-lab/BenStuff/research/projects/oldhome/scripts/networks/rset/rsetlists/output/rsetlistNUMBER1")
scorelistNUMBER1 <- list()
length(scorelistNUMBER1) <- ... |
5c211f138fb9c6d776077698e22842e504ac98e328534ff34e024c5567cd4a88 | R | 1,991 | 88 | #' @tags futureAssign
#' @tags listenv
#' @tags sequential multisession multicore
library(future)
library(listenv)
message("*** %<-% to listenv ...")
## - - - - - - - - - - - - - - - - - - - - - - - - - - - -
## Future assignment via infix operator
## - - - - - - - - - - - - - - - - - - - - - - - - - - - -
z <- list... |
71fb4e53b257ef24f3b971a113bed19420c52f0ab42ff5c6b1089c545071e89e | R | 2,018 | 81 | ---
title: "--"
author: "rbarreiro"
date: "--"
output:
html_document:
theme: journal
css: rmark.css
---
```{r setup, include=FALSE}
suppressMessages({
library(tidyverse)
library(scales)
library(cowplot)
library(ggbeeswarm)
library(ggsci)
library(viridis)
library(knitr)
library(ggpubr)
lib... |
4b89ae0fb92409b659fc26aab508bb91122cbfc575ca3538ad5f56c03bc9b42e | R | 2,020 | 64 | #' @tags utils-internal import
library(future)
import_from <- future:::import_from
import_parallelly <- future:::import_parallelly
import_parallel <- future:::import_parallel
import_parallel_fcn <- future:::import_parallel_fcn
## NOTE: Only *exported* functions are used below, so that these tests do not
## depend on... |
b7678e39d96bbe55892914917b70c1f015ae4a83d4e9d83437b11f19eba42cd8 | R | 2,022 | 61 | library('circlize')
# Read connectivity data
main_dir <- '/Users/karimia/code/Brain_Network/matlab/figs/chord_modularity'
file_name <- "combined_hemis"
out_name <- "Modules_2_3"
full_csv_name <- file.path(main_dir, paste(file_name, '.csv',sep = ""))
T <- read.csv(full_csv_name)
# set the row names and remove the Row ... |
4850c89e00af075dfd4416201ccf010e372db5e2f48aeaac22f20a5e87e8b568 | R | 2,025 | 85 | ### script to identify high expressed genes (features)
# load libs
source('functions.R')
# load tool locations
tool_path <- load_tool_location()
# get args
get_dir <- commandArgs(trailingOnly = TRUE)
# check input files
in_bam <- get_dir[1]
if(grep('.sort.bam$',in_bam) != 1){
stop(
paste0(in_bam, ' is not a B... |
54e3d2e74370ad1546f2cd6db92d8ed4e64d3b0893f24bd5ab86ea4edd7d17bf | R | 2,033 | 56 | ```{r}
setwd("evaluating_coregulation")
source("../downstreamer_functions.r")
source("data/source_olivier.r")
library(ggsignif)
datasets <- read.downstreamer.batch(main.downstreamer.output.path, USE.CACHE = T)
ced.prio <- as.data.frame(read_excel(aadriaan.ced.prio,
col_types = c(rep("text", 4)... |
09480747667be61a67aa9738a7c6c64aae7928f5dc788846e74216d1f413ae0b | R | 2,043 | 51 | #' Title Get top percent of diffHubs default is 5percent
#'
#' @param diffPR.df output dataframe of diffPR(),
#' @param top.percent top percentage of diffPR hub genes to retrieve, default is 0.05
#'
#' @return dataframe of top percentage diffPR genes for each celltype
#' @export
#'
#' @examples
#' sorted.net.list <- So... |
fa8c9961e448f557f7a3f51b9225fdc0d031755b7a0b93bcb57be7f9c455fdea | R | 2,051 | 59 | # Cell-type marker conversion
library(homologene)
library(readr)
setwd("/Users/philippehabets/Dropbox/Git/fMRI-transcriptomics-cortisol/data/")
# Read markers. Used Neuroexpresso Version: 1.2
dir <- "neuroExpresso/"
filenames <- list.files(dir)
conversion_table <- sapply(filenames, function(f){
m <- unlist(read.tabl... |
2b246cbb1d79c489b3e245af2f50c35e4ed320b6113be02802ffea98980a4ee4 | R | 2,053 | 55 | library(data.table)
input_file <- '../test_less_genes/output/5_covariatesRemoved/1000_genes_test.duplicateSamplesRemoved_extractedColumnsnoVarianceRowsRemoved.DESeqNorm.CovariatesRemoved.txt'
expression <- fread(input_file,
check.names=F)
expression <- data.frame(expression, check.names=F)
rownames... |
1671ed203966d8d438f10a0d2f40306adfd460eaa7fe0bb6fdaf8d06535718da | R | 2,077 | 86 | #' @importFrom utils globalVariables
globalVariables(c(".", ".."))
bquote_compile <- function(expr, substitute = TRUE) {
if (substitute) expr <- substitute(expr)
tmpl <- list()
unquote <- function(e, at = integer(0L)) {
n <- length(e)
if (n == 0L) return()
if (is.pairlist(e)) {
for (kk in... |
25feb18d106ca7551bfd7615adca2c492414766adb25784a081deb55a7d181e7 | R | 2,078 | 72 | #' @tags worker-interrupt
#' @tags detritus-files
#' @tags multisession multicore
library(future)
options(future.debug = FALSE)
strategies <- supportedStrategies()
## Signalling SIGINT to an R future process might end up
## terminating the whole R process. Because of that, we
## might get a FutureError, because we c... |
7106e5fec0fc0c75b2eca5353a91899d7d61782115747608355923dcb58a2704 | R | 2,078 | 45 | ```{r}
setwd("../downstreamer_collaborations/biogen/")
source("../../downstreamer_main/downstreamer_functions.r")
# Read excel files
base <- read.downstreamer.batch("/home/work/Desktop/depict2/collaborations/biogen/hand_grip_strength/2021-04-09/")
```
```{r}
a <- read.table("/home/work/Desktop/depict2/collaboration... |
8345ad28c020ac5e642da211a5223439b8e94b808ff98f579ea0db151b304823 | R | 2,079 | 76 | #!/usr/bin/R
library(micropan)
library(dendextend)
library("optparse")
option_list = list(
make_option(c("-f", "--file"), type="character", default=NULL,
help="dataset file name", metavar="character"),
make_option(c("-o", "--out"), type="character", default="out.txt",
help="output fi... |
62a55b26da06a34fbb640967c8a013b584a9c7840a6f2d2248e18cc8e7ba8056 | R | 2,081 | 84 | #' @tags futureOf
#' @tags environment
#' @tags sequential
library(future)
suppressWarnings(rm(list = c("x", "z")))
message("*** futureOf() with environment ...")
message("*** futureOf() with environment - future assignments ...")
x <- new.env()
x$a %<-% { 1 }
f1 <- futureOf("a", envir = x)
print(f1)
f2 <- future... |
1c77c9ed936d58caedc249ad7adf699c7d6fc281095b48b24c19d001a5ba47a5 | R | 2,092 | 83 | ### script to filter(=keep) reads of a certain length
# load libs
library(foreach)
library(doParallel)
source('functions.R')
# load parameters
conf <- load_mapping_config()
# load tool locations
tool_path <- load_tool_location()
# set max cores
max_cores <- get_max_cores() # from functions.R
# register max 8 cores ... |
3bc1f7906425865ecff02fceb25fa0b5088920a36a00f03dca29dc9d07366f9c | R | 2,096 | 73 | #!/usr/local/R-4.1.2/bin/R
library(RColorBrewer)
library(dendextend)
library("optparse")
#args = commandArgs(trailingOnly=TRUE)
option_list = list(
make_option(c("-f", "--file"), type="character", default=NULL,
help="dataset file name", metavar="character"),
make_option(c("-o", "--out"), type... |
0711b3b82fb5ea7524a59cf6aac0d8570e6ff23f62c9b6180341d03b695509ac | R | 2,098 | 60 | library('circlize')
# Read connectivity data
main_dir <- '/Users/karimia/code/Brain_Network/matlab/figs/chord_modularity'
file_name <- "mod_averaged"
out_name <- "Modules_averaged"
full_csv_name <- file.path(main_dir, paste(file_name, '.csv',sep = ""))
T <- read.csv(full_csv_name)
# set the row names and remove the R... |
33147e5953c2321c6cf6332b9ff3621c092a05c3f56804c6bf3ed82b168c7bcb | R | 2,101 | 68 | extract_optim_parameters <- function(object) {
UseMethod("extract_optim_parameters")
}
#' @title Extract parameters from fitted model for use as initial values
#'
#' @srrstats {G1.4} Function documented with roxygen2.
#' @srrstats {G2.1a} Expected data types provided for all inputs.
#'
#' @description This function ... |
d5da63d166ad2029a1950e8a0df3240218661a153bab54897ab9e0b28e6928e2 | R | 2,109 | 62 | #' @tags utils-internal rng
library(future)
stealth_sample <- future:::stealth_sample
message("*** stealth_sample() ...")
## Nothing to sample
stopifnot(identical(stealth_sample(1:10, size = 0L), integer(0)))
stopifnot(identical(stealth_sample(letters, size = 0L), character(0)))
## Nothing to randomize, because th... |
028285d8a75b4ea5c4306204f5347745597d93e53ba6c6f921471bcdf6121997 | R | 2,121 | 84 | library(tidyverse)
library(mgcv)
library(mvtnorm)
set.seed(123)
tps <- 8
tests <- c(3, 2, 4)
family <- c("gaussian", "binomial", "gaussian")
trials <- c(1, 1, 1)
n <- 200
lambda <- list(
c(1, 1.4, .3),
c(1, 2),
c(1, 1, 1, 2)
)
# Residual standard deviation for Gaussian model
sdeps1 <- .1
f0 <- function(x) 2 * s... |
6e1f4d31a023978865e63888060e99b321d86b0d730d1ee80f93b503de2669f1 | R | 2,121 | 48 | #' getsitedc
#'
#' This function takes a RefCDS object and a bigwig file with duplex coverage as input and adds to the RefCDS two fields required to use site-level duplex coverage in dndscv. Usage: RefCDS = getsitedc(RefCDS)
#'
#' @author Inigo Martincorena (Wellcome Sanger Institute)
#' @details Martincorena I, et al.... |
66a573471e9ea13d40f8ab149ee2c645fffbb34f9203577f45f0d6195f4c48f7 | R | 2,132 | 58 | #' Load, parse and check BEDPE.
#'
#' This function loads a BEDPE file. Columns 2 and 4 and 5 and 6 will be sorted numerically.
#' If only a BED-file is present, duplicate BED-columns 1,2,3 as: 1,2,2,1,3,3.
#'
#' @param loop.bed Path to bedpe file.
#' @param header Does the file come with a header?
#' @export
#' @retur... |
a128387e0012fa38aeab27d9a35600ae2eb23ef0ce1de16a9bd784b28f9ac3a8 | R | 2,132 | 76 | #' @tags utils-internal whichIndex
message("*** whichIndex() ...")
dims <- list(
c(1),
c(1, 1),
c(2),
c(2, 1),
c(3, 4, 3)
)
for (dim in dims) {
printf("Dimensions: (%s)\n", paste(dim, collapse = ", "))
dimnames <- lapply(dim, FUN = function(n) letters[seq_len(n)])
X <- array(seq_len(prod(dim)), dim =... |
f1bbdec937e3d6f7394e0cd5f32fb5477e2d53ef422a2daafbd3281a0c44649c | R | 2,139 | 64 | ```{r}
if (basename(getwd()) == "downstreamer_main") {setwd("evaluating_coregulation")} else {setwd("../evaluating_coregulation")}
source("../downstreamer_functions.r")
source("data/source_olivier.r")
eqtlgen.cis <- read.table("data/cisQtlEnrichment.txt")
metabrain.cis <- read.table("data/cisQtlEnrichmentBrain.txt")
... |
756cb7e21ad1726ced68c7e02dfcd3aad06b19bff1b28f8dc36d3cec92b55e76 | R | 2,140 | 37 | library(data.table)
gn.expression <- fread("zcat /groups/umcg-wijmenga/tmp04/projects/depict2/depict2_bundle/reference_datasets/human_b37/expression_databases/31.07.pc1.illumina.wantedgenes.DESeqNorm_log2.duplicatesRemoved.ProbesWithZeroVarianceRemoved.CovariatesRemoved.txt.gz", data.table=F)
rownames(gn.exp... |
3b4e89f8794309abf489b7dcd1a609ccdd3f689a9daedf59ced80758d8e66b7a | R | 2,142 | 61 | ```{r}
setwd("evaluating_coregulation")
source("../downstreamer_functions.r")
source("data/source_olivier.r")
files <- list.files("~/Desktop/depict2/collaborations/harm_jan/", pattern="*.xlsx", full.names=T)
datasets <- list()
for (file in files) {
name <- gsub("\\_hg19\\_enrichtments\\_exHla\\.xlsx", "", basename(f... |
d79e37633800289e8049d4f933ce9097ed0195b7d4ad4c5427d0df242095ea48 | R | 2,146 | 81 | #' @tags result sequential
library(future)
plan(sequential)
message("*** result() ...")
## A resolved future gives a FutureResult
f <- future(42L)
v <- value(f)
res <- result(f)
stopifnot(inherits(res, "FutureResult"))
stopifnot(identical(res[["value"]], 42L))
## Asking again returns the already collected result
r... |
414ef9ea90175cb366a4ebdfa281f32d1607c182359ce5cad7164a9362bbd8e2 | R | 2,151 | 69 | ##########################################################################################
## Create gene x gene co-expression matrix containing proportionality metric (rho)
## using human cortex gene expression matrix from Velmeshev 2019 (scRNA-seq)
##
## Author: Yu-Han Hsu
############################################... |
d4dfebc7a6f42516faec0e1bd3854a1e41e373d4d99cb5c8f2875f17f069d25b | R | 2,168 | 68 | ##########################################################################################
## Generate MAGMA common variant enrichment plots for ASD PPI networks
##
## Author: Yu-Han Hsu
##########################################################################################
rm(list=ls())
library(ggplot2)
# read ... |
123744dd0ad3a5bb98220471c58edf00ac22d57ce7c2e5a965f7cdfdb8d44215 | R | 2,171 | 60 | library(data.table)
library(rtracklayer)
dir <- "~/crg2/utils/wgs_gene_coverage/"
print("Reading GTF file...")
gtf <- readGFF("/hpf/largeprojects/ccm_dccforge/dccdipg/Common/genomes/hg19.ncbiRefSeq.gtf")
## Filter out additional chromosomes
chr_names <- paste("chr", c(seq(1:22), "X", "Y"), sep="")
gtf <- gtf[which... |
36df7249584ce027e428e8becdc1cd276ec37cf5bbb2addadd82324a9d1423a1 | R | 2,174 | 54 | library(tidyverse)
TDPortal <- read.csv("All_Hits_Rat_Brain.csv", header = TRUE,check.names = FALSE)
load("x53m.RData")
### Change headers to match TDPortal
### Remove redundant or extra columns
w_cluster <- w_cluster %>%
mutate(`Scan#` = `Scan(s)`) %>%
select(-`Scan(s)`) %>%
select(-NormRecal... |
2a308aab160d32e4988c99e9b60332eb501a3da9253f6f8653a99e5777df9efe | R | 2,181 | 60 | load(file = "hpoEnrichmentSession4b.RData")
str(recount3Zscores)
pascalxZscores2 <- pascalxZscores
colnames(pascalxZscores2) <- gwas$Name[match(colnames(pascalxZscores2), gwas$machine_friendly_id)]
pascalDist <- as.dist(1 - cor(pascalxZscores2, use = "pa"))
pascalDist[is.nan(pascalDist)] <- 1
pascalDist[is.na(pasc... |
e58fe87ce9762c36cf414860427cf265c6c8e2b5050550010dc057009ffc60d6 | R | 2,184 | 61 | load("allnetworks.RData", verbose = FALSE)
done <- "models removed"
doner <- "models remaining"
trash <- list()
trashcount <- 0
pb <- txtProgressBar(min = 0, max = length(bensface), style = 3)
for (i in (1:length(bensface))){
if (colSums(bensface[[i]])[1] == 0){
trashcount <- trashcount+1
trash[trashcount] <-... |
8fd3776e4d9b22d25a4a0c0fcfa3bfa527f50138589a5e182a49e385eb9664be | R | 2,196 | 66 | ```{r}
source("downstreamer_functions.r")
setwd("gwas_simulations")
source("data/source_olivier.r")
files <- list.files(gwas.simulation.path, pattern=".*normalizedGenePvalues.txt", full.names = T)
genep <- read.enrichments(files)
# Read reference datasets
ensembl <- read.table(ensembl.file, sep="\t", header=T, row.na... |
e6ac9e43ef592e23c52858990ec669e5a878524e12d54db3148a15c34d9d4d54 | R | 2,197 | 89 | #' @tags journal sequential
library(future)
journal <- future:::journal
oopts <- options(future.journal = TRUE)
plan(sequential)
mkfuture <- function(x) {
f <- future(x)
value(f)
f
}
f1 <- mkfuture(1L)
f2 <- mkfuture(2L)
message("*** journal() - Future ...")
j <- journal(f1)
print(class(j))
stopifnot(inher... |
3277ea440cd4afd69518f55f51d3c53486c9ada0c1a28fb08b69033314e4e076 | R | 2,200 | 81 | ##' @importFrom nlme ranef
##' @export ranef
NULL
#' @title Extract random effects from galamm object.
#'
#' @srrstats {G1.4} Function documented with roxygen2.
#' @srrstats {G2.1a} Expected data types provided for all inputs.
#'
#' @param object An object of class \code{galamm}, returned from
#' \code{\link{galamm}... |
71d1f6dd2375458eabb6e1ba1d323b1e7e4b6e05a088ca3888d5ad81d85987f1 | R | 2,200 | 84 | #' @tags debug listenv
#' @tags sequential multisession
library(future)
message("*** backtrace( ) - explicit future ...")
f <- future({ 42L; stop("Woops") })
v <- value(f, signal = FALSE)
print(v)
calls <- backtrace(f)
print(calls)
message("*** backtrace( ) - explicit future ... DONE")
message("*** backtrace( ) -... |
75a0bf7665be41209b312eb6ec310f1b5aa15629ba9fca83d3e24e230a8d7c3b | R | 2,213 | 70 | library(R.matlab)
library(dplyr)
Sys.setenv(JAVA_HOME= "/usr/bin/java") #set java environment
library(RDAVIDWebService)
david<-DAVIDWebService$new(email="p.c.habets@lumc.nl", url="https://david.ncifcrf.gov/webservice/services/DAVIDWebService.DAVIDWebServiceHttpSoap12Endpoint/")
david
path_DEG <- file.choose() #choose... |
c11d5ed98bbbb26a89c7ca3f0bacc27246562bf12ec64834e8863aa5e4c097e8 | R | 2,215 | 59 | #
# tstat.postprocessing.R
#
# Copyright (c) 2013-2013 GBIC: Danny Arends, Harm-Jan Westra, Lude Franke and Ritsert C. Jansen
# last modified Jul, 2013
# first written Jun, 2013
#
setwd("~/Github/systemsgenetics/eqtl-mapping-pipeline/src/main/scripts")
source("helper.functions.R")
setwd("~/Github/Juha/")
ProbeAnnotati... |
5da5e29badbca9802abbba3d41f1a34a7ff52673c6172505b8841aab1fe9d06f | R | 2,224 | 70 | ####################################################################################
#' RISC data
####################################################################################
#'
#' The RISC object contains all the basic information used in single cell RNA-seq
#' analysis, including raw counts/UMIs, normalized... |
1a2fadf649c354053b2085732e51b26a04005558c4b331fd4b090efdbf469b13 | R | 2,228 | 59 | #' GenesetHnv3
#'
#' @param geneset geneset of interest. provided multipe genelist as a named list or as a character vector
#' @param reference.network default HumanNetv3
#'
#' @return a dataframe of genelist with connectivity, detected genes in the HumanNetv3 and the normalized connectivity
#' @export
#'
#' @examples
... |
2c4f2b510521b8836e7c8a3c231f2c96232940b8a8c229d20cf9b45668e2b9fb | R | 2,229 | 93 |
setwd(dirname(rstudioapi::callFun("getActiveDocumentContext")$path))
library(tidyverse)
gi.dc <-
readRDS("../WGCNA/Colon/geneINFOall.rds")
gries<-read.csv("griesprot.csv")
keep=gries$p.li<0.05
gries.li<-gries[keep,]
protnames<-strsplit(gries.li$Protein.Name,";")
uniprot_mapping <- function(ids) {
uri <- 'ht... |
f7828df2dde8df1c26b8bcb95b93d1e7a2bd90ffaa75aba1f3585701aed68db2 | R | 2,232 | 66 | library(Biostrings)
library(tidyverse)
library(nlme)
library(ape)
library(geiger)
# PERMUTATIONS
# SHUFFLE TILES TO TEST FOR INTRON SIGNIFICANCE ####
#plot only the ones with GI and brain weight present +human1 activity --> 45 species btw
pheno_data<-read_rds("pheno_data/pheno_data.rds")
mammaltree<-read.tree("prote... |
a6857850b53bf2f1de8e5662f27f88c1c9c5ff444e74b529494efd86b45027be | R | 2,236 | 65 |
setwd("C:\\UMCG\\Genetica\\Projects\\Depict2Pgs")
trait = "Height_v33/Height"
library(readr)
table_tmp <- read_delim(paste0(trait, "_eigen_Enrichment_betasExHla.txt"), delim = "\t", quote = "")
eigenBeta<- as.matrix(table_tmp[,-1])
rownames(eigenBeta) <- table_tmp[,1][[1]]
rm(table_tmp)
table_tmp <- read_delim(pa... |
b84c69ba330b4b47a0bf3501ceef03c462bec3a54fe7a5977e91645fb811ea31 | R | 2,241 | 71 | #' @tags multisession
#' @tags connections worker-termination
#' @tags detritus-files
library(future)
options(future.debug = FALSE)
message("*** multisession - connections must not leak when futures error ...")
if (.Platform[["OS.type"]] == "windows") {
## This test takes very long to run on MS Windows (e.g. 5-10 ... |
c150f88f9a5c03b7d3d5a5f50c3cd01207997dd78c850ec913abe6328c1da129 | R | 2,243 | 72 | source ("Library.R")
options(mc.cores = parallel::detectCores())
rstan_options(auto_write = TRUE)
#####melanogaster####
d <- read.csv("normmax_imaging_4C_melanogaster.csv")
d$x <- d$IPI
d$y <- d$normmax
observation <- list(N = nrow(d), x = d$x, y = d$y, Ninds = length(unique(d$ID)), id = d$ID)
params = c(a0 = 0.1... |
b4c19e4503c46860f1c82fcba8700f06efcde522fb66fa5075a7295b2b5bb4cc | R | 2,247 | 87 | ---
title: "Statistics for age and sex - HCPEP and Cobre"
author: "Fran Hancock"
affiliation: Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
date: "`r format(Sys.time(), '%B %d, %Y')`"
fontsize: 14pt
output: html_document
---
```{r setup, include=FA... |
cc3c4b2c8079174233a469ad8c2002ea21b28564b3b91e20c5f7322aa49c78e1 | R | 2,256 | 70 | plot_smooth <- function(object, ...) {
UseMethod("plot_smooth")
}
#' @title Plot smooth terms for galamm fits
#'
#' @srrstats {G1.4} Function documented with roxygen2.
#' @srrstats {G2.1a} Expected data types provided for all inputs.
#'
#' @description
#' Plots smooth terms of a fitted \code{galamm} object. This fun... |
583a99d71bb42f5d445d0f433510126280df843d56dd87c376127620bbadd637 | R | 2,260 | 61 | ```{r}
if (basename(getwd()) == "downstreamer_main") {setwd("evaluating_coregulation")} else {setwd("../evaluating_coregulation")}
source("../downstreamer_functions.r")
source("data/source_olivier.r")
library(UpSetR)
# Cached 2021-04-16
#datasets <- read.downstreamer.batch(main.downstreamer.output.path, US... |
4f15d21d01ad32663263e4536c1b5805b34e43918983581514c5aee6c3027634 | R | 2,262 | 56 | require(ggplot2)
require(viridis)
require(UpSetR)
require(ComplexHeatmap)
require(plyr)
df <- read.table("marker_name_list.csv", header=T, sep=",")
df <- df[,-c(1)]
df <- df[1:100,]
print(head(df))
gdf <- read.table("rank_gene_list_celltype.csv", header=T, sep=",")
gdf <- gdf[,-c(1)]
gdf <- gdf[1:1000,]
print(head(gdf)... |
a1aad956beed1e658bcaad3090146cb40b1d0529bdc1d2e69b967e68709e2e9a | R | 2,264 | 78 | setwd("D:\\UMCG\\Genetica\\Projects\\Depict2Pgs\\output\\ds2\\")
library(readxl)
read.depict2 <- function(path, potential_traits=NULL) {
if (is.null(potential_traits)) {
potential_traits <- excel_sheets(path)
potential_traits <- potential_traits[grep("Overview", potential_traits, invert=T)]
}
output... |
5277dbad31c212edd251684f91adc42445fd7f96f6dac96365a2aa0d19ffc67d | R | 2,268 | 50 | #' geneciloc
#'
#' Function to calculate confidence intervals for dN/dS values per gene under the dNdSloc model using a Poisson ratio.
#'
#' @author Inigo Martincorena (Wellcome Sanger Institute)
#' @details Martincorena I, et al. (2017) Universal patterns of selection in cancer and somatic tissues. Cell. 171(5):1029-1... |
fe5f7070b443c53518f42bbd03b9f6d30b6e8a8043da55c71fc4ab45315bbc7a | R | 2,268 | 79 | ##
## Generate a volcano plot from a data frame of genes, fold changes (log-scale), and p-values.
##
plot_volcano = function(stats_df,
gene_col,
fc_col,
p_col,
fc_cutoff = 0,
p_cutoff = 0.05,
... |
ca9ddfcbc4b665d22f8bb270ad0826e12faf278e19f04e497795534af5411f8d | R | 2,271 | 82 | #' @tags cancel
#' @tags detritus-files
#' @tags detritus-connections
#' @tags sequential multisession multicore
library(future)
options(future.debug = FALSE)
strategies <- supportedStrategies()
#strategies <- setdiff(strategies, "sequential")
for (strategy in strategies) {
message(sprintf("plan('%s') ...", strate... |
821a3ec1d428d849c7fcd7cbf4b5f3fd814b4e7ca34e5dea36e735496dc68a49 | R | 2,277 | 47 |
if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools")
devtools::install_github("DKFZ-biostats/explainedVariance", dependencies = TRUE)
library(explainedVariance)
library(lme4)
library(tidyverse)
# load and prepare data
reflectance <- read_csv("reflectance_clamping.csv")
reflectance$stag... |
9271898bb275ee8e9f97e68def5498ca8a6cf6dcdefd0af3dd4069cde9e0c42a | R | 2,281 | 79 |
library(data.table)
library(gridExtra)
library(grid)
library(ggplot2)
library(lattice)
library(viridis)
library(optparse)
option_list = list(
make_option(c("-m", "--matrix"), type='character',
help="Matrix to make pairwise hexbins of"),
make_option(c("-o", "--outfile"), type='character',
... |
ba3a69396c59c79fd07c304fda79c2bd877b8ead3f5b881db34cc05ba0fb4ee7 | R | 2,281 | 91 | #' Outputs details on the current \R session
#'
#' @param env If TRUE, `Sys.getenv()` information is returned.
#'
#' @return Invisibly a list of all details.
#'
#' @importFrom utils sessionInfo
#' @export
#' @keywords internal
sessionDetails <- function(env = FALSE) {
## Gather all details
details <- list(
"Sys... |
68652bd882b71da452254f5c66f49fef6c9d1aa095a980a88fc275c94167bf76 | R | 2,282 | 57 |
# For ensembl readnames
ensembl <- read.table("~/Documents/data/reference/ensembl/ensembl_gene_position_export.txt", sep="\t", header=T, stringsAsFactors = F)
ensembl <- unique(ensembl[,c(1, 5)])
rownames(ensembl) <- ensembl[,1]
# Read coregulation matrix
cur.df <- read.table("~/Desktop/gene_network_niersteen_filtere... |
420a746c2398a8e7b1c46b17e206f2edebb094cc8ae25c3637a2958e958eed0b | R | 2,289 | 92 | library(future)
library(graphics)
plot_what_is_done <- function(counts) {
for (kk in seq_along(counts)) {
f <- counts[[kk]]
## Already plotted?
if (!inherits(f, "Future")) next
## Not resolved?
if (!resolved(f)) next
message(sprintf("Plotting tile #%d of %d ...", kk, n))
counts[[kk]] <... |
6131f346a94f143937e3e8a26394212676d7dd9430814abb123c0e9cb3749f48 | R | 2,302 | 75 | ## Create a universally unique identifier (UUID) for an R object
#' @importFrom tools md5sum
uuid <- local({
## We need to trick 'R CMD check' that 'md5' is a function already,
## because with md5 <- NULL, 'codetools' triggers a check NOTE.
md5 <- function(x) {
## 1. Use the native tools::md5sum(bytes = ...),... |
ddd8e9abc2a8f9cd7b28a3e403219cb27bc9dd2a926bade19e4c4c0a2ed0fdca | R | 2,302 | 86 | #' @tags relaying stdout
#' @tags sequential multisession multicore
library(future)
message("*** Standard output ...")
truth_rows <- utils::capture.output({
print(1:50)
str(1:50)
cat(letters, sep = "-")
cat(1:6, collapse = "\n")
write.table(datasets::iris[1:10,], sep = "\t")
})
truth <- paste0(paste(truth_r... |
c1ea2fa500447454f85c73017dadfbb07ee8c3526bba91083924c10b6aad1bed | R | 2,309 | 80 | #=========================#
# 4.Prep target QC files #
#=========================#
## Set up ----
filepath <- ""
setwd(filepath)
### Load libraries ----
library(dplyr)
library(magrittr)
## Sex checks (checking whether genetic and self-report match) ----
# Genetic QC files performed by Marzia Scelsi
# Two different ... |
207776bb838a2360f85c7c06f6326bad79ad8b48a86e802c54b00bf14acfe9a6 | R | 2,314 | 98 | #' @tags rng rng-utils
message("*** RNG ...")
set_random_seed(seed = NULL)
seed <- get_random_seed()
stopifnot(is.null(seed))
set_random_seed(seed = 42L)
seed <- get_random_seed()
stopifnot(identical(seed, 42L))
res <- tryCatch({
seed <- as_lecyer_cmrg_seed(seed = FALSE)
}, error = identity)
print(res)
stopifnot(... |
55cb4adad7f2ca1acff666ab299eecaf75ba5ff805e596aa443fc516bd0899f5 | R | 2,317 | 52 | ## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.height = 6, fig.align = "center")
## -----------------------------------------------------------------------------
library(motif4node)
library(ggplot2... |
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