sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
27a1cff5c6d7f1e90ba294fac4118f2a042712c1192cf18dc8d260d61efe626c | R | 163 | 6 | #' Update the mfishtools library
#'
#' @export
update_mfishtools <- function() {
devtools::install_github("AllenInstitute/mfishtools", build_vignettes = TRUE)
}
|
2f214cec783b1596283f4249585dcc67d5bf3b0b9184fe586e0d1c30d4ae692e | R | 191 | 7 | distance_from_2d_line <- function(a,b,c) {
#a = point, b and c are two points on your line of interest.
v1 <- b - c
v2 <- a - b
m <- cbind(v1,v2)
d <- abs(det(m))/sqrt(sum(v1*v1))
} |
f4bba63c0ea5a1721e51e3946736d7dc105ba14b43567e3dc4ad2e361cc6738e | R | 198 | 7 | # http://dirk.eddelbuettel.com/blog/2017/08/10/
Rd_files <- vignettes <- R_files <- description <-
list(
encoding = "UTF-8",
language = "en",
dictionaries = c("en_stats", "iTReX")
)
|
32b37726c0de6c217e4887bb1d60b1aaf4eebdb161cda04fc6da61166626e10d | R | 201 | 7 | library(MOFA2)
test_that("a pre-trained model can be loaded from disk", {
filepath <- system.file("extdata", "model.hdf5", package = "MOFA2")
expect_s4_class(load_model(filepath), "MOFA")
})
|
06b11f513b8babd1dafa541be9f550bcd4d5c4c5d4823d97749b6df3d8d9cd41 | R | 202 | 5 | withCallingHandlers({
install.packages("lhs", repos="https://cloud.r-project.org/")
install.packages("rBayesianOptimization", repos="https://cloud.r-project.org/")
},
warning = function(w) stop(w))
|
a3f909a682945491c66e74778f48bb18358b464cb095e40e4996beec9f5e77f4 | R | 205 | 11 | #---> Libraries <----
require(dplyr)
require(ggplot2)
require(caTools)
require(glmnet)
library(survival)
library(kernelshap)
library(shapviz)
require(caret)
library(survex)
library(survminer)
|
c7d29bbbdb5dedea53a458bba3ddb309f5436e0cc5528cb006a15792b784d601 | R | 206 | 6 | # Test funcs. in misc.R
test_that("simulateDataset gives expected output", {
expect_equal(nrow(simulateDataset(n_genes = 30)), 30)
expect_equal(nlevels(simulateDataset(n_rings = 4)$cluster), 4)
})
|
8ef0bb7f97135dcc729984c5dd70a98d5f5a90150af28e01adb42005b0555691 | R | 208 | 3 | ################################# Fig.1i
reduced_all <- readRDS("Customized directory/Manuscript.Wei.et.al/Rds/reduced_all.rds")
DimPlot(reduced_all, reduction = 'umap', group.by = "orig.ident", shuffle = T)
|
aacc8aad9a12e314f258d14fd53b200650440c4a022cc54d022a58270621c84e | R | 210 | 9 | library(testthat)
library(lightgbm) # nolint: unused_import.
test_check(
package = "lightgbm"
, stop_on_failure = TRUE
, stop_on_warning = FALSE
, reporter = testthat::SummaryReporter$new()
)
|
ef9963d5f2bc36ac0ef4cf849c6e5f8215562b9ca48efb96718f358c023e9ef7 | R | 217 | 8 | ggplot_theme <- function() {
theme(
plot.title = element_markdown(size = 14),
legend.title = element_text(size = 14),
legend.text = element_text(size = 14),
axis.text = element_text(size = 14)
)
}
|
c834903f94bfc725b0654bc77e135bfa947874b6c64763ed6f3afbe20e888188 | R | 219 | 9 | args <- commandArgs(TRUE)
file_name <- args[1]
index <- args[2]
data_name <- load(file_name)
eveGNN::export_to_gnn(eval(parse(text = data_name)), index)
eveGNN::write_pars_to_gnn(eval(parse(text = data_name)), index) |
6e16abce698ee820acff72817a665ded90e14c5fc426b9b658de900813db1e8c | R | 220 | 10 | #!/usr/bin/Rscript
# default repo
local({r <- getOption("repos")
r["CRAN"] <- "https://cloud.r-project.org"
options(repos=r)
})
pkgs = c('optparse')
install.packages(pkgs, repos='http://cran.us.r-project.org')
|
95a194ae1c7fb5fe4a3ea641ed90e28b254aa7234cd145360ec96b385b6e99a5 | R | 228 | 11 | #' @keywords internal
pdis = function(x, atlas){
vars = rownames(atlas)
pat = apply(x, 1, sum)
atlas = apply(atlas, 1, sum)
parc.discon = matrix(pat / atlas,nrow=1)
colnames(parc.discon)=vars
return(parc.discon)
}
|
56a4c3b9198fee3d94de8bcb7b81b023f478e7e6f1728a72a6cef37aa77fbe01 | R | 232 | 12 | #' Pipe operator
#'
#' See \code{magrittr::\link[magrittr:pipe]{\%>\%}} for details.
#'
#' @name %>%
#' @rdname pipe
#' @keywords internal
#' @return Function load
#' @export
#' @importFrom magrittr %>%
#' @usage lhs \%>\% rhs
NULL
|
66717f9da984c3fc558617260a8b2bb2d0647fb3c4853aca0e7aaffa4316a69a | R | 232 | 10 | #' @importFrom utils packageVersion
.onAttach <- function(libname, pkgname) {
if (!interactive()) {
return()
}
packageStartupMessage(
sprintf("Banksy version %s", packageVersion(pkg = "Banksy"))
)
}
|
e6587df120511c90db64ed00fe3a375dc382d8b3294b4a310bbf2fc4cff081b8 | R | 234 | 6 | ## helper functions for constructing python calls used by targets ----
run_python_target <- function (command_args, out_path, conda_path) {
with_path(conda_path, code = system2("python", args = command_args))
return (out_path)
}
|
78e6de1b4ba8a3d09c694b39081b78b503a25c5aabf56c47b6926fc6412593cc | R | 237 | 9 | ############################
## iTReX ShinyApp file ##
## Author: Yannick Berker ##
############################
# nolint start: undesirable_operator.
iTReX:::set_env()
shinyApp(iTReX:::itrex_ui(), iTReX:::itrex_server)
# nolint end
|
25ca2dd25e865769c2ed3ea8c4888f4667dc7724026765c39b81605bf5218894 | R | 240 | 14 |
set.seed(6879)
props <- rbeta(1000, shape1=2, shape2=10)
res = estimateBetaParam(props)
test_that("estimateBetaParam works", {
expect_equal(length(res), 2)
expect_equal(round(res$a,2), 2.03)
expect_equal(round(res$b,2),9.68)
})
|
c1cfeb296fb610e8556cf7ce2fb1f8774f28769b5e163b0bae7c88e54b0f789d | R | 240 | 9 | library(Seurat)
seurat_obj <- readRDS('multiome.rds')
DefaultAssay(seurat_obj) <- 'SCT'
seurat_obj <- CellCycleScoring(seurat_obj, g2m.features = cc.genes$g2m.genes, s.features = cc.genes$s.genes)
saveRDS(seurat_obj, 'multiome.cc.rds')
|
4a3246202d12b56f05dc6cab4b3f469a948a9bdf73a22a817f4010aed0cf7564 | R | 244 | 9 | grow <- function(x, ...) UseMethod("grow")
grow.default <- function(x, ...)
stop("grow has not been implemented for this class of object")
grow.randomForest <- function(x, how.many, ...) {
y <- update(x, ntree=how.many)
combine(x, y)
}
|
c43751faa6aaf26e05d7f3f10df695432fb3b5dc5b309f4a19a4c691c38e8ce7 | R | 246 | 6 | ##
## Set up variables across 2xx-scripts
##
set.seed( seed = 12345 ) ## Ensure reproducible code blocks
warning("Have set a fixed random seed, all runs will be identical unless this is changed (may be good or bad, depending on what you want)")
|
577f59dcf326e0ad72707a0218ae34c073804cf52d0bf27c2e2e623cba4cd574 | R | 251 | 4 | # Declare variables used via non-standard evaluation (data.table / aggregate
# formulas) so R CMD check does not raise "no visible binding for global
# variable" notes.
utils::globalVariables(c(".SD", "rows", "genes", "col1", "col2", "Homo_sapiens"))
|
04c913819c17929f67a01226c396fdb8a02b134625c22c58224f3cf62e5a4ddb | R | 253 | 13 | library("UMI4Cats")
library(BSgenome.mm10.ensembl.local)
bcpath = snakemake@params[['odir']]
mm10 <- digestGenome(
res_enz = "GATC",
cut_pos = 0,
name_RE = "dpnII",
ref_gen = BSgenome.mm10.ensembl.local,
out_path = bcpath,
sel_chr = NULL
) |
4971ae8818519f6c41e6aacc45eaf24d89362690361260dbdcc0aa2a0caa4da7 | R | 264 | 5 | options(timeout=1000)
install.packages("BiocManager", repos = "http://cran.us.r-project.org")
BiocManager::install("ShortRead")
BiocManager::install("BSgenome")
devtools::install_github("https://github.com/wardDeb/UMI4cats", dependencies = TRUE, upgrade = "never") |
119383e079ed9ebbf6da480dfb80c4bc6936d88376d5560b9f54060bd4c33ca2 | R | 272 | 4 | .onAttach <- function(libname, pkgname) {
packageStartupMessage("MuSiC v1.0.0 support SingleCellExperiment! See Tutorial: https://xuranw.github.io/MuSiC/articles/MuSiC.html")
packageStartupMessage("MuSiC2 for multi-condition bulk RNA-seq data is also available!")
} |
56fc2be856d841ef9c14413a3c27bdc6600a912e9c93944bbaee93adf9558363 | R | 273 | 9 | test_that("`ggplotColors()` returns as expected", {
expect_equal( ggplotColors(6),
c("#F8766D","#B79F00","#00BA38","#00BFC4","#619CFF","#F564E3")
)
})
test_that("`ggplotColors()` returns expected number of colors", {
expect_equal(length(ggplotColors(10)),10)
})
|
f1ac0d6dc59fe60d2b672c2c05f2089b70f15329f2b0c7ab1a9ca90e0591592b | R | 275 | 11 | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
RcppVersion <- function() {
.Call(`_pROC_RcppVersion`)
}
delongPlacementsCpp <- function(roc) {
.Call(`_pROC_delongPlacementsCpp`, roc)
}
|
1b9bece668bbba938e27e206c40f2d2c36e342824a69451df83f1b48294b4f93 | R | 277 | 12 |
res<- speckle_example_data()
test_that("`speckle_example_data` returns as expected", {
r_to_json <- function(x) {
path <- tempfile(fileext = ".json")
jsonlite::write_json(x, path)
path
}
expect_snapshot_file(r_to_json(res), "speckle_example_data.json")
})
|
e45da1adf6e25b2fcaa8177d53cbcaade9f452da38accf5853e1ae65c829ab7b | R | 278 | 17 |
##-------------------------------------##
## METADATA TAB ##
##-------------------------------------##
replace_label <- function(var, old_label, new_label){
var <- gsub(paste0("^", old_label,"$"), new_label, as.character(var))
return(var)
}
|
004bd52380723647e5cdffa58b822710895019e321ed62296047fde2425c4dbd | R | 284 | 16 | library(Seurat)
seurat_obj <- readRDS('multiome.rds')
geneset <- readLines('zr_fus.gene')
seurat_obj <- AddModuleScore(
object = seurat_obj,
assay = 'SCT',
slot = 'data',
features = list(geneset),
name = 'zr_score'
)
saveRDS(seurat_obj, 'multiome.zrfus.rds')
|
25ad46fcc18bd8f61793ab51cda2327a0666bba2d45abbe983ac6e71f23540c1 | R | 287 | 6 | withCallingHandlers({
install.packages("devtools", repos="https://cloud.r-project.org/")
install.packages("Seurat", repos="https://cloud.r-project.org/")
devtools::install_github("dviraran/SingleR", ref="db4823b380ba2c3142c857c8c0695200dd1736f6")
},
warning = function(w) stop(w))
|
7fe9f17a94defeef259c5f74665950c049ddc41142e5e221b368502c7838fcbb | R | 287 | 6 | .onAttach <- function(libname, pkgname) {
RFver <- read.dcf(file=system.file("DESCRIPTION", package=pkgname),
fields="Version")
packageStartupMessage(paste(pkgname, RFver))
packageStartupMessage("Type rfNews() to see new features/changes/bug fixes.")
}
|
406ac892c24f627d2c55434c069065f378f435e7df6352895f05af6595c8946b | R | 296 | 10 | # Skip slow tests
skip_slow <- function(message = "Slow test skipped") {
if (exists("run_slow_tests", envir = .GlobalEnv)) {
if (!get("run_slow_tests", envir = .GlobalEnv)) {
skip(message)
}
} else if (!identical(Sys.getenv("RUN_SLOW_TESTS"), "true")) {
skip(message)
}
}
|
7d857458e62fd5207e3e4d178b62a6e9bccf0ee3f594fcb81aad4c33c3edaf21 | R | 306 | 18 | ---
title: "Omics_Report"
output: html_document
---
```{r, width=700, height=700}
cat("DSS_asym")
plot_igraph(network_l)
```
```{r, width=700, height=700}
if (is.null(s_network_l)) {
cat("sDSS_asym values are not available for this sample")
} else {
cat("sDSS_asym")
plot_igraph(s_network_l)
}
```
|
ff3dd4e522f09ad0bd538eda97d7b2cae3c82b197d5ffb31137fa135e510ccc9 | R | 306 | 10 | #' @keywords internal
p2pnet = function(x, suffix){
pd.file = list.files(file.path(x, "Parcel_Disconnection"))
pd.file = pd.file[grepl(paste0(suffix,"_disconnectivity.RData"),pd.file)]
pd.path = file.path(x, "Parcel_Disconnection", pd.file)
load(pd.path)
dmat = disconnectivity
return(dmat)
}
|
784f40ea1c9edf8b4a44bed92fe92dc9964b83323b5f0295e82e844e5c471d8d | R | 307 | 18 | ---
title: "HitNet_Report"
output: html_document
---
```{r, width=700, height=700}
cat("DSS_asym")
plot_igraph(network_l)
```
```{r, width=700, height=700}
if (is.null(s_network_l)) {
cat("sDSS_asym values are not available for this sample")
} else {
cat("sDSS_asym")
plot_igraph(s_network_l)
}
```
|
ceccc94f7ca8b64470cdfb3716e93df2aca38e51446bf353428d6d415742444f | R | 308 | 6 | treesize <- function(x, terminal=TRUE) {
if(!inherits(x, "randomForest"))
stop("This function only works for objects of class `randomForest'")
if(is.null(x$forest)) stop("The object must contain the forest component")
if(terminal) return((x$forest$ndbigtree+1)/2) else return(x$forest$ndbigtree)
}
|
d34fedea62f7ceb553ef80d031e6f23d154479696e4eaaea9eb637a72578ef27 | R | 309 | 13 | library(data.table)
library(devtools)
require(GenomicSEM)
munge(c("/path/to/MDD.txt",
"/path/to/ADHD.txt",
"/path/to/BPD.txt"),
hm3 = "/path/to/w_hm3.snplist",
trait.names = c("MDD", "ADHD", "BPD"),
info.filter = 0.9,
maf.filter = 0.01)
#Returns munged summary statistics for multivariable LDSC
|
cfbab83476092545626543f54b6758da76c7fe6ead15c74fffbf092eaee9b41c | R | 312 | 15 | #' @keywords internal
ndis = function(x, atlas, groups){
vars = rownames(atlas)
pat = apply(x, 1, sum)
atlas = apply(atlas, 1, sum)
pat=rowsum(pat, group=groups)
atlas=rowsum(atlas, group=groups)
net.discon = matrix(pat / atlas,nrow=1)
colnames(net.discon)=rownames(pat)
return(net.discon)
}
|
405bd697f3426495c2070c9281ae828db14b30af8db16e6099b725eca1f92360 | R | 322 | 5 | ################################# ED.Fig.1d
library(pheatmap)
Combined_avg <- read.csv('Customized directory/Manuscript.Wei.et.al/Raw_Txt/Tumor_Bulk_Combined_gene_list_avg.csv', header = TRUE, row.names = 1)
pheatmap(log2(as.matrix(Combined_avg)+1), scale = "row", cluster_cols = F, cluster_rows = F, treeheight_row = 0... |
872d0e2fbb9df8d74d62f285e62d5d9c3dc7a7cc26f27767de6d9c0192b9b86e | R | 324 | 4 | # Shared publication typography. PDF text stays embedded and searchable.
figure_style <- list(font='Liberation Sans', base_pt=8.5, small_pt=8,
width_mm=178, control_label='Ctrl', effect_labels=c('D1/Ctrl','D3/Ctrl','D3/D1'),
negative='#3b6fb6', neutral='white', positive='#d55e0... |
9207acfcf95ca0bd8371c61c2cfe197b2eb084df2209808ad2b5df9eb9d03545 | R | 324 | 15 | ---
title: "iHeatmap"
output: html_document
---
## `r PID`
```{r}
t <- readxl::read_xlsx(file.path(output_dir, paste0(PID, "_mono.xlsx")))
t$DSS_asym <- as.numeric(t$DSS_asym)
t <- data.table::as.data.table(t)
ordered <- t[order(DSS_asym, -Drug.Name, na.last = TRUE), ]
waterfall_with_hover_drcs(output_dir, ordered)
... |
c096fad4f0c19e0136fa6321c98741b930d18aed3a3fad2a11e287f62e39535d | R | 328 | 8 | withCallingHandlers({
install.packages("BiocManager", repos="https://cloud.r-project.org/")
BiocManager::install(ask = FALSE)
BiocManager::install("SingleCellExperiment")
install.packages("devtools", repos="https://cloud.r-project.org/")
devtools::install_github("hemberg-lab/scmap")
},
warning = function(w) s... |
9c6d4a9171a11c18a0fbc51ea0a45a5fc5cc91a5afad523ef1f6bc6866fb7508 | R | 332 | 19 | loadNamespace("pkgdown")
loadNamespace("roxygen2")
roxygen2::roxygenize(
"R-package/"
, load = "installed"
)
pkgdown::build_site(
"R-package/"
, lazy = FALSE
, install = FALSE
, devel = FALSE
, examples = TRUE
, run_dont_run = TRUE
, seed = 42L
, preview = FALSE
, new_proce... |
b2a5a0648d00b056790c841975f84d015c99a6f6a96fe7c3534f7ada1f2d648a | R | 333 | 10 | # function to create density plot
suppressPackageStartupMessages(library(ggplot2))
density_plot <- function(mat, color_var, title, xlab){
p <- ggplot(mat, aes_string(x = 'log2(value + 1)', fill = color_var)) +
geom_density(alpha = .3) +
theme_bw() + theme_Publication2() +
ggtitle(title) +
xlab(xlab)
... |
8f8acfc23a866fd8b6b40499adf82d6bec766f543e2a8e4b8e85326385a4a141 | R | 335 | 21 |
library(glmnet)
get_lm_results=function(fitted.model, test.x){
test.pred = predict(fitted.model, newdata = test.x)
return(test.pred)
}
get_enet_results=function(fitted.model, test.x){
test.pred=predict(fitted.model, as.matrix(test.x),
type="response", s = "lambda.min")
return(test.p... |
31d4668378b703188d04d45f195a31818bfa510305d082ffef16181afc923ac0 | R | 339 | 5 | install.packages(c("yaml","ape","furrr","future.apply","purrr"), repos = "https://cloud.r-project.org")
remotes::install_github("YuLab-SMU/ggtree", force = TRUE)
remotes::install_github("thijsjanzen/treestats", force = TRUE)
remotes::install_github("EvoLandEco/eve", force = TRUE)
remotes::install_github("EvoLandEco/eve... |
7a09f3e6568a90de873ccff80921b0eccc31e1b7c43602cf23e742a304a510b4 | R | 345 | 12 | #' Re-exporting the pipe operator
#' See \code{magrittr::\link[magrittr]{\%>\%}} for details.
#'
#' @name %>%
#' @rdname pipe
#' @param lhs see \code{magrittr::\link[magrittr]{\%>\%}}
#' @param rhs see \code{magrittr::\link[magrittr]{\%>\%}}
#' @export
#' @importFrom magrittr %>%
#' @usage lhs \%>\% rhs
#' @return depe... |
28cfe5364e50e380973a21f46924b38945e455dbbd7262c3476174607c85a4d7 | R | 348 | 15 | library(neurobase)
library(oro.nifti)
writeLines('*** Reading Files ***')
arg <- commandArgs(trailingOnly = TRUE)
wmh <- readnii(arg[1])
wmh_mask = wmh[wmh != 0]
writeLines('*** Generating Stats Table ***')
out <- table(wmh_mask)
out <- as.matrix(out)
name <- arg[2]
out = cbind(out, rep(name, nrow(out)))
write.table... |
8a3bb40babc9d011084d4da0c31cbe690fd5daf5f218421ac6afcffbf6041cc9 | R | 348 | 11 | .libPaths("/home/xavier/R/library-pROC_revdeps")
.libPaths("/home/xavier/R/library")
pak::pkg_install("r-lib/revdepcheck")
library(revdepcheck)
# Don't make in parallel. Avoids running out of memory on some build tasks
Sys.setenv("MAKEFLAGS"="")
revdep_reset()
revdepcheck::revdep_check(num_workers=2, timeout = as.dif... |
b4ce24b2ce8d2b828cee48eae1ecc9a6f5114b7fabb96ed37cf42e043d8dfac0 | R | 354 | 14 |
set.seed(3485)
y <- matrix(rnbinom(6000, mu = 100, size = 1), ncol = 6)
lnorm.y2 <- normCounts(y, log=TRUE, prior.count=2)
test_that("`normCounts` returns as expected", {
r_to_json <- function(x) {
path <- tempfile(fileext = ".json")
jsonlite::write_json(x, path)
path
}
expect_snapshot_file(r_to_js... |
ba41eab3b66de3efdc669c21aac96a2d28d469b2a924ec0302d82090818cea25 | R | 358 | 21 | ---
title: Installation
output:
pkgdown:
toc: FALSE
---
`MuSiC` is implemented as an
R package, `r BiocStyle::Githubpkg('xuranw', 'MuSiC')`, which can be
installed from GitHub by:
```{r, eval = FALSE}
# install devtools if necessary
install.packages('devtools')
# install bseqsc
devtools::install_github('xura... |
a546154cdd90bde90c5a44e903dcd2700feca6820566c4f00d6a64a440e278f3 | R | 359 | 11 | #' @keywords internal
tdis = function(x){
td.file = list.files(file.path(x, "Tract_Disconnection"))
td.file = td.file[grepl(".csv",td.file)]
td.path = file.path(x, "Tract_Disconnection", td.file)
tract_discon = read.csv(td.path)
tract.discon = matrix(tract_discon$Discon,nrow=1)
colnames(tract.discon)=tract... |
a2f6e47e49d5c895032123031bc13318d61d8c8a02e5254ee58237cfd72b3531 | R | 363 | 14 | #' Pipe operator
#'
#' See \code{magrittr::\link[magrittr:pipe]{\%>\%}} for details.
#'
#' @name %>%
#' @rdname pipe
#' @keywords internal
#' @export
#' @importFrom magrittr %>%
#' @usage lhs \%>\% rhs
#' @param lhs A value or the magrittr placeholder.
#' @param rhs A function call using the magrittr semantics.
#' @ret... |
7c4e5d1609d6aba6c4510851cae3d8b10c1aa16a8e8aed9311c6d5e49e7888d4 | R | 370 | 9 | withCallingHandlers({
install.packages("BiocManager", repos="https://cloud.r-project.org/")
BiocManager::install(ask = FALSE);
BiocManager::install(c("scater", "MAST"))
install.packages("devtools", repos="https://cloud.r-project.org/")
devtools::install_github("satijalab/seurat")
devtools::install_github("B... |
275789f5aced5dc5ebc8edb807dccd3be2f62d53d9dbac6dd6dfb3853cd604a6 | R | 372 | 9 | # plot data sources for ciliopathy genes
library(ggplot2)
variantsCiliopathy = read.csv('data/variantsCiliopathies.csv') #curated list of ciliopathy genes
freqtable = as.data.frame(table(unique(variantsCiliopathy[,c("datasourceId", "diseaseId", "targetId")])[,1]))
ggplot(freqtable, aes(x=reorder(Var1, -Freq), y=Fre... |
813c8b69641e0da0ccc0f6c5b69fe166e7f6b0247479e99d8b785f236bbccf41 | R | 372 | 12 | # This file is part of the standard setup for testthat.
# It is recommended that you do not modify it.
#
# Where should you do additional test configuration?
# Learn more about the roles of various files in:
# * https://r-pkgs.org/tests.html
# * https://testthat.r-lib.org/reference/test_package.html#special-files
libr... |
31f123dba39e1b56b3a06c0f24951bdefa5a34f15117ce988959ed06edc1174b | R | 373 | 14 | #!/usr/bin/env RScript
args=commandArgs(trailingOnly=TRUE)
org=args[1]
corresFile=args[2]
libpath=args[3]
corresIDorg=read.table(corresFile,header=T,row.names=1)
orgGO=as.character(corresIDorg[org,1])
if((!require(orgGO,character.only=TRUE, lib.loc=libpath))){
requireNamespace("BiocManager", quietly = TRUE)
BiocMa... |
97a20d417c008467f730ac1d1b7fb5285806202cf6a03d1b91a196192a9f5126 | R | 374 | 12 | # This file is part of the standard setup for testthat.
# It is recommended that you do not modify it.
#
# Where should you do additional test configuration?
# Learn more about the roles of various files in:
# * https://r-pkgs.org/tests.html
# * https://testthat.r-lib.org/reference/test_package.html#special-files
libr... |
ce2f843ea25ba9b9bb5c6f824e066ee379b096e18038a613f9a394343bb67f15 | R | 374 | 11 | # Skip expect_doppelganger if vdiffr is not installed
expect_doppelganger <- function(title, fig, ...) {
testthat::skip_if_not_installed("vdiffr")
vdiffr::expect_doppelganger(title, fig, ...)
}
# expect_doppelganger for ggroc
expect_ggroc_doppelganger <- function(title, fig, ...) {
testthat::skip_if_not_installe... |
5379b2baa0d2faa89ed29a2dbfd6e3f23a6352e38fd4859bc179dd25cffa6d1b | R | 380 | 9 | library(LAVA)
input = process.input(input.info.file="/path/to/input.info.txt",
sample.overlap.file="/path/to/sample.overlap.file", #Optional; NULL
ref.prefix="/path/to/g1000_EUR/g1000_eur",
phenos= c('F1'))
loci = read.loci("/path/to/locus.txt")
locus =... |
96b28762cfe26c94fb66467a3e47e88bbd80c0a9ef43d3a3476c1578ec70cbbb | R | 389 | 10 | test_that(".METRICS_HIGHER_BETTER() should be well formed", {
metrics <- .METRICS_HIGHER_BETTER()
metric_names <- names(.METRICS_HIGHER_BETTER())
# should be a logical vector
expect_true(is.logical(metrics))
# no metrics should be repeated
expect_true(length(unique(metric_names)) == length(metri... |
f5bef65af8f96766b345febd3179de80306127c296669dc36ff29ccdfd78a7ac | R | 398 | 12 | # This file is part of the standard setup for testthat.
# It is recommended that you do not modify it.
#
# Where should you do additional test configuration?
# Learn more about the roles of various files in:
# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
# * https://testthat.r-lib.org/articles/spec... |
15efd594ff01ac60d6efec144bf9bb6c6d5b7e39a78e010a6fd26597c5e3f810 | R | 401 | 11 | #' @keywords internal
pdam = function(x, suffix){
pd.file = list.files(file.path(x, "Parcel_Damage"))
pd.file = pd.file[grepl(paste0(suffix,"_percent_damage\\.csv"),pd.file)]
pd.path = file.path(x, "Parcel_Damage", pd.file)
parcel_damage = read.csv(pd.path)
parcel.damage = matrix(parcel_damage$PercentDamage,... |
2ce4e8fd168e410c439b39990bc574300fdaff943ba4fcb6538081f79f0d8cff | R | 404 | 12 | # This file is part of the standard setup for testthat.
# It is recommended that you do not modify it.
#
# Where should you do additional test configuration?
# Learn more about the roles of various files in:
# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
# * https://testthat.r-lib.org/articles/spec... |
39c6482ac89a94eb7d2b5df1dd1d341d1591e3e8c6c087a337ecf070ae56db8c | R | 404 | 12 | # This file is part of the standard setup for testthat.
# It is recommended that you do not modify it.
#
# Where should you do additional test configuration?
# Learn more about the roles of various files in:
# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
# * https://testthat.r-lib.org/articles/spec... |
e9f7ac1be96f962b6d51bbab4cac20e176974507d22419a25c8dd8fd1c75b653 | R | 404 | 11 | source("../shinytest_helpers.R")
set_window()
app$setInputs(number_of_samples = "cohort")
app$uploadFile(layout_table_file = demo_path("MRA_Layout.xlsx"))
app$uploadFile(readout_matrices_file = demo_path("MRA_2ReadoutsXlsx.zip"))
app$setInputs(start_oca = "click", timeout_ = 1500e3)
app$setInputs(iTReX = "MRA-mod/Coho... |
517e9e1263b5274082867c78e05b3ca0862b444583aa258be12ab41a740d2ed7 | R | 405 | 24 | # ---> Libraries <----
require(dplyr)
require(ggplot2)
require(caTools)
require(glmnet)
library(randomForestSRC)
library(pec)
library(survex)
# if (!require("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
#
# BiocManager::install("survcomp", force = TRUE)
require(survcomp)
# l... |
e8389bcc8d4a2f3089d32d33cbeba65f4083bda25c291b7b12c28c3764107624 | R | 406 | 11 | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
col_max <- function(quantities, m, n) {
.Call('_diann_col_max', PACKAGE = 'diann', quantities, m, n)
}
maxlfq_solve <- function(quantities, peptides, samples, margin = -10.0001) {
.Cal... |
43f37581f2d52a5bee3702352ddeaff0a34ffe1f8d936c867595fd0e79387840 | R | 411 | 12 | library(tidyverse)
library(dplyr)
v39_eh_df <- read_tsv('results/ensembl_gene_symbol_gtf_gencode_v39.tsv')
open_ped_can_eh_df <- read_tsv('input/OpenPedCan-v12-ensg-hugo-pmtl-mapping.tsv') %>%
dplyr::select(gene_symbol, ensg_id) %>%
dplyr::rename(ensembl = ensg_id)
merged_eh_df <- distinct(bind_rows(v39_eh_df, o... |
76e027abbb5c1dd3478db79c487424d3d397f4c6a429b70e45e6218bbeb0f6f4 | R | 413 | 19 | library(Seurat)
seurat_obj <- readRDS('multiome.rds')
DefaultAssay(seurat_obj) <- 'SCT'
seurat_obj <- PrepSCTFindMarkers(seurat_obj)
diff_exp <- FindAllMarkers(
object = seurat_obj,
only.pos = TRUE,
logfc.threshold = 0.25,
min.pct = 0.05,
recorrect_umi = FALSE
)
write.ta... |
b82752f2c46d91202b4b11389cfc8790d9fb99ab1e676b44f1df8141d9cff3d0 | R | 413 | 11 | library(rgl)
library(wholebrain)
path.bin <- 'F:/1.课题/1.神经环路/20230713/Figure/bin'
path.matrices <-'F:/1.课题/1.神经环路/20230713/Figure/data/3D_data'
allen.annot.path <- paste(path.matrices , 'allen-mesh', sep = '/')
load(paste(path.matrices ,'atlasspots.RData',sep='/'))
load(paste(path.matrices , 'vivid-colors.RData', sep... |
862f38e1a06072e52c7bf37a18a9aee794a81534b7648003043911cabcbff371 | R | 414 | 11 | source("../shinytest_helpers.R")
set_window()
app$setInputs(number_of_samples = "cohort")
app$uploadFile(layout_table_file = demo_path("MRA_Layout.xlsx"))
app$uploadFile(readout_matrices_file = demo_path("MRA_2ReadoutsXlsx_Identical.zip"))
app$setInputs(start_oca = "click", timeout_ = 1500e3)
app$setInputs(iTReX = "MR... |
7cf5bf7651503cd4fa5871fa80520ea24f88195f4d5f19504dbe4412326b2b19 | R | 424 | 17 | #' @keywords internal
p2pdis = function(x, atlas){
pat = x
pat[upper.tri(pat)]=NA
pat = melt(pat, na.rm=T)
pat$Var = paste0(pat$Var2, "_to_",pat$Var1)
atlas[upper.tri(atlas)]=NA
atlas = melt(atlas, na.rm=T)
atlas$Var = paste0(atlas$Var2, "_to_",atlas$Var1)
pat$value = pat$value / atlas$value
parc2p... |
b195a1800319029b1fa22c88392963520ee4443b24e81da2a8b3daf596b819d6 | R | 425 | 13 | # ------ Function to find the last row where relevant columns contains "+" and the next column has data
find_last_valid_row <- function(col) {
# Find rows with "+"
rows <- grep("\\+", file_temp[[col]])
# Keep rows where next col has data
rows <- rows[file_temp[[col + 1]][rows] != "" & !is.na(file_temp[[... |
47e506099709147a306faf9c6958e2c0256ab3d5d7d60851c9d29f2438a5fa0b | R | 427 | 8 | withCallingHandlers({
install.packages("devtools", repos="https://cloud.r-project.org/")
install.packages("BiocManager", repos="https://cloud.r-project.org/")
BiocManager::install("fgsea")
devtools::install_github("thomasp85/patchwork", ref="fd7958bae3e7a1e30237c751952e412a0a1d1242")
devtools::install_github(... |
b835a29b3b4c8c2afa7d4b14206923dc060ccd43608aff014f58008280a42715 | R | 427 | 7 | ### Saving Dataset for OSF Storage:
library(Seurat)
sctv2fileloc='path/to/datasets/'
MayZhang10x<-readRDS(file = paste0(sctv2fileloc,'2024-06-18_May-Zhang2021_10x_6wks_MouseColDuodIle_SCTv2Integrated_HarmonyBC.RDS'))
MayZhang10x@assays$SCT<-NULL
MayZhang10x@assays$integrated<-NULL
saveRDS(MayZhang10x,file = paste... |
8beb673d8e98e698dae34e3d5854435e0448503801252e8efc78f6d8cbdd1641 | R | 431 | 8 | withCallingHandlers({
install.packages("BiocManager", repos="https://cloud.r-project.org/")
BiocManager::install(c("monocle", "DelayedArray", "DelayedMatrixStats",
"org.Hs.eg.db", "org.Mm.eg.db"))
install.packages("devtools", repos="https://cloud.r-project.org/")
devtools::install_github(... |
314c96e81b07256bb421c63c91b9678d58502acac917fac2069b74534244d0cd | R | 434 | 11 | ---
title: Data download
output:
pkgdown:
toc: FALSE
---
* [Processed RNA-seq data from bulk pancreatic islets in healthy and
hyperglycemic individuals (GSE50244)](https://github.com/xuranw/MuSiC/tree/master/vignettes/data/GSE50244bulkeset.rds)
* [Single cell RNA-seq data of pancreatic islets from health... |
f69b81b13cb3e2699f110159b46fb8e01828f89c29a8cd5d317a0dd2175257c3 | R | 434 | 8 | withCallingHandlers({
install.packages("devtools", repos="https://cloud.r-project.org/")
install.packages("BiocManager", repos="https://cloud.r-project.org/")
BiocManager::install(c("bioDist", "ggplot2", "gplots", "cowplot",
"dendextend", "corrplot", "reshape2", "plotly"))
devtools::ins... |
7f19cd6c6caa0dae95f5fd41b5f9bd58fa3e1e12b52eb1531a9497402df9b21c | R | 435 | 11 | # Function to read all the sheets of an Excel file
read_excel_allsheets <- function(filename, tibble = FALSE) {
# I prefer straight data.frames
# but if you like tidyverse tibbles (the default with read_excel)
# then just pass tibble = TRUE
sheets <- readxl::excel_sheets(filename)
x <- lapply(sheets, function... |
a60ccf53f108d009b263b46df352d8c5cff9356964ef5c8a342bbdc0c46f7fcc | R | 435 | 7 | # vector of bridge recommendations assigned to each datapoint from the
# cross-product normalization method and when setting the format 'format'
# argument to TRUE.
bridge_recommendations <- c("median_centering" = "MedianCentering",
"quantile_smoothing" = "QuantileSmoothing",
... |
190f395643fad0e055f051300bf9dd968310e0c56846f0f264e5ed50a69440fe | R | 443 | 14 | source("../shinytest_helpers.R")
set_window()
app$uploadFile(layout_table_file = demo_path("MRA_LayoutAndReadouts_BT-40_ST04.xlsx"))
app$setInputs(upload_reference_samples = TRUE)
app$uploadFile(reference_samples_file = demo_path("Controls_DKFZ_ST10-min.xlsx"))
app$setInputs(start_oca = "click", timeout_ = 1500e3)
ap... |
a0e398c14178702a2724931f4a6d00ca3b49e6aa96ca023f6209ad3393609b84 | R | 443 | 12 | source("../shinytest_helpers.R")
set_window()
app$setInputs(number_of_samples = "cohort")
app$uploadFile(layout_table_file = demo_path("MRA_Layout.xlsx"))
app$uploadFile(readout_matrices_file = demo_path("MRA_2ReadoutsXlsx.zip"))
app$setInputs(Amin_select = "0")
app$setInputs(start_oca = "click", timeout_ = 1500e3)
ap... |
6ad968f54fcfea0fdfd77e2fe6382022dc4ca7a50fdefbc45cd7ee97f7c508e0 | R | 445 | 12 | source("../shinytest_helpers.R")
set_window()
app$setInputs(number_of_samples = "cohort")
app$uploadFile(layout_table_file = demo_path("MRA_Layout.xlsx"))
app$uploadFile(readout_matrices_file = demo_path("MRA_2ReadoutsXlsx.zip"))
app$setInputs(Amin_select = "10")
app$setInputs(start_oca = "click", timeout_ = 1500e3)
a... |
09ddaa8dfff31ee06c25f075d30cf0e48ef30e7a324df7e9d609d630560731bb | R | 449 | 16 | folder<-"/home/jbrenton/Regina_file_deposit"
files<-list.files(folder)
files<-files[grep("fastq.gz", files)]
# filenames<-sub("(^.*)/.*", "\\1", files)
sample_names<-c()
for (i in 1:length(files)) {
index<-which(!is.na(str_match(files[i], meta$CaseNo)))
sample_names[i]<-unique(meta$CaseNo[index])
}
new_files<-fil... |
24bfa82906f37567c02467ddd0fbbfc6141c48b64d476c349b356fb329750104 | R | 451 | 18 |
data <- speckle_example_data()
x <- table(data$clusters, data$samples)
res = estimateBetaParamsFromCounts(x)
test_that("estimateBetaParamsFromCounts works", {
expect_equal(length(res), 6)
expect_equal(res$n, 1100)
expect_equal(length(res$alpha),ncol(data))
expect_equal(length(res$beta),ncol(data))
expect... |
36fe7be6f6de7c60598960d1c914bf14ae75cfdd534ef031466a37f99bd67612 | R | 457 | 18 | args <- commandArgs(TRUE)
name <- args[1]
if (!dir.exists(name)) {
dir.create(name)
}
setwd(name)
dir.create("BD_TES")
setwd("BD_TES")
bd_tes <- replicate(500, ape::rphylo(n = 200, birth = 0.6, death = 0.1, T0 = 10, fossils = FALSE), simplify = FALSE)
bd_tes_list <- list(tes = bd_tes)
eveGNN::export_to_gnn(bd_te... |
1152ffdbf5b22ba646de1e7cced825ace4ad4e21223c9971d5d26343cf9cc7f2 | R | 460 | 14 | # =======================================================
# Some global variables that can be used in all functions
# =======================================================
#' @import utils
NULL
## Set global variables to avoid NSE notes in R CMD check
utils::globalVariables(c(
"q.name", "q.len", "q.start", "q.e... |
8b16ca4d2ed734a92780b0bc74a0ec62d240383fc42a0e14afcda9d2adf15d5d | R | 467 | 7 | # Requires R 4.6.1 plus a C/C++ toolchain and standard R build dependencies.
if(as.character(getRversion())!='4.6.1') stop('The frozen environment requires R 4.6.1')
dir.create('.Rlib',showWarnings=FALSE)
.libPaths(c(normalizePath('.Rlib'),.libPaths()))
options(repos=c(CRAN='https://cloud.r-project.org'))
if(!requireNa... |
dc1161abcc21f658f9e795475f7f80a956acdcaaf9781b0230057bffee073608 | R | 468 | 14 | # File: /scripts/analysis/lme_RMS.R
# Purpose: Linear mixed‑effects model for RMS post EEG biofeedback
# Input: ../../data/processed/EMG_EEG_strength.csv
# Output: model summary printed to console
# Dependencies: lme4, emmeans (see docs/parameters.md)
library(lme4)
library(emmeans)
data <- read.csv("../../data/proces... |
ef74b055b6d1bfa3e66c5a300b765027fbf5740258adfc0099b69773db09e0fc | R | 470 | 16 | test_that("getLGBMthreads() and setLGBMthreads() work as expected", {
# works with integer input
ret <- setLGBMthreads(2L)
expect_null(ret)
expect_equal(getLGBMthreads(), 2L)
# works with float input
ret <- setLGBMthreads(1.0)
expect_null(ret)
expect_equal(getLGBMthreads(), 1L)
# s... |
6f005bfb92667faf18050a1d0f28ff55ba37b3a77e49f8a82fd9c2d7bfdbdb73 | R | 476 | 16 | setwd('~/Documents/work/PTSD_2023/round3_medi/interaction_withMiRNA_NOV/code_for_share/Base_model/FACTORwave2_PTSSwave3/Life_Factor/')
df <- readRDS('df.rds')
fomular <- as.formula(sprintf("%s ~ %s", colnames(df)[1],
paste(paste(colnames(df)[-c(1)],
... |
8eb89b99f99e762dbb48cd3aa22a3a6422daecdac82441a63b6c8f9fb758144d | R | 476 | 8 | utils::globalVariables(c(
".", ".data", "Adjusted", "CFI.dif", "CIlower", "CIupper", "Crude", "Edge",
"Edge weight bootstrapped (95% CI)", "Edge weight sample", "M(sd)",
"RMSEA (90% CI)", "RMSEA.dif", "Significance", "VIF", "Var", "any_of",
"dups", "eff.type", "group_category", "id", "key", "n(%)", "node1", "no... |
64e2ec929ab40865ba868f6e400f9bfc1c8751ed43b8d9752de4296612899562 | R | 477 | 16 | setwd('~/Documents/work/PTSD_2023/round3_medi/interaction_withMiRNA_NOV/code_for_share/Base_model/FACTORwave4_PTSSwave4//Life_Factor/')
df <- readRDS('df.rds')
fomular <- as.formula(sprintf("%s ~ %s", colnames(df)[1],
paste(paste(colnames(df)[-c(1)],
... |
1204e2b9896fb2b36f4c8bd46c8cd2d99100db1b3f864e45da4697e39fd35ed2 | R | 480 | 16 | setwd('~/Documents/work/PTSD_2023/round3_medi/interaction_withMiRNA_NOV/code_for_share/Base_model/FACTORwave2and3_PTSSwave3/Life_Factor/')
df <- readRDS('df.rds')
fomular <- as.formula(sprintf("%s ~ %s", colnames(df)[1],
paste(paste(colnames(df)[-c(1)],
... |
6e4068c84cdcd71f4aa8460b1406d4590cdcc5c9af4eb22da6c0cfb3986890e2 | R | 480 | 13 | source("../shinytest_helpers.R")
set_window()
app$setInputs(number_of_samples = "cohort")
app$uploadFile(layout_table_file = demo_path("MRA_Layout.xlsx"))
app$uploadFile(readout_matrices_file = demo_path("MRA_2ReadoutsXlsx.zip"))
app$setInputs(Amin_select = "other")
app$setInputs(Amin_slider = 25)
app$setInputs(start_... |
575f64f4523055173bbfb79d69790478d2e09bbef647fc33a9ea7de9525e734a | R | 487 | 20 | ###############################################
#
# UI for homepage tab
#
###############################################
tab_HOME <- tabPanel(
title = "",
icon = NULL,
#div(class="fa fa-home", role = "navigation"),
value = "home", # tab ID
htmlTemplate("www/landing-page.html",
latest_upd... |
6d1707f7d6007ca743f2f401962e3e032cfa72ad9544219af7966c71693a8a86 | R | 488 | 23 | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
hyper_bench_vector <- function(xin, yin, N, n) {
.Call(`_richR_hyper_bench_vector`, xin, yin, N, n)
}
name_table <- function(lh) {
.Call(`_richR_name_table`, lh)
}
reverseList <- func... |
465c01c7af4b58a8fd83ca6a8ac7e9e0ba96e86efc1b1a6a5a82e66d784da851 | R | 489 | 16 | setwd('~/Documents/work/PTSD_2023/round3_medi/interaction_withMiRNA_NOV/code_for_share/Base_model/FACTORwave2_PTSSwave3/Life_Current_Factor_PRS//')
df <- readRDS('df.rds')
fomular <- as.formula(sprintf("%s ~ %s", colnames(df)[1],
paste(paste(colnames(df)[-c(1)],
... |
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