sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
032e792d55d02ff87573485e25d2dd33adaad6d3726df63db52ddb1665dc011a | R | 17,760 | 418 | ####################################################################################################
###
### File: 00_source.R
### Purpose: Load required packages and functions used to
### create interactive maps.
### Authors: Gabriel Rodrigues Palma
### Date: 05/04/23
###
##############################... |
712142b4551880bcd6701f0db2f7b2884cca01ea53aa21564502fe1416bd87ed | R | 17,761 | 362 | #' This function submits a single script to a high-performance cluster using a scheduler (Slurm or TORQUE).
#' It accepts a vector of arguments to be passed to the scheduler and
#' a vector of environment variables that should be passed to the compute node at job execution.
#'
#' The function returns the jobid of t... |
abcbe3c9f9ce6e5a5b7173582113b8e80c5db587539756dd11170cff48ed3ad4 | R | 17,769 | 531 | #!/usr/bin/R
# ---------------------------------------
# Differential expression for astrocytes:
# Updated: 05/25/21
# ---------------------------------------
# Aggregate number of sign. genes:
library(cbrbase)
set_proj('DEVTRAJ')
source(paste0(bindir, 'multiRegion/load_metadata.R'))
library(tidyr)
library(Matrix)
lib... |
fc4ee801edd2b80f03242b28851d88d77a4ed078b35346f161d0da816f874db9 | R | 17,803 | 440 | library(knitr)
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ALDEx2")
library(ALDEx2)
install.packages("devtools")
library(devtools)
install_github("ggloor/CoDaSeq/CoDaSeq")
library(CoDaSeq)
library(zCompositions)
library(igraph)
library(car)
... |
8533a967ec93d2a942c7773d73325c58a70f6944848b6727cb2f45d1e7c75d88 | R | 17,819 | 531 | # Behavioral tests for the FLAME outlier auto-retry mechanism.
#
# These tests exercise the actual bash and R logic rather than grepping source
# code for string patterns.
if (identical(.Platform$OS.type, "windows")) {
test_that("outlier retry behavioral tests require POSIX shell semantics", {
skip("requires exe... |
d23b813e90fe3f8b2e7907e928c2e56b65876db574a6f76b653d5fea35b19d68 | R | 17,851 | 402 | # SCRIPT INFORMATION:
# SCRIPT: DETECT NEURAL SEQUENCES IN TASK BY MODELLING
# PROJECT: FMRIREPLAY
# WRITTEN BY LENNART WITTKUHN, 2018 - 2019
# REVISED BY QI HUANG 2022
# CONTACT: STATE KEY LABORATORY OF COGNITIVE NEUROSCIENCE AND LEARNING, BEIJING NORMAL UNIVERSITY
## Decoding on slow trials
### Initialization
We ... |
894ce44e40c5f7302291f81109a4884afd61c0a4fce948aff3ec6afb3136e901 | R | 17,856 | 532 | library(corrplot)
library(dplyr)
library(RColorBrewer)
setwd("F:/Brain_region_project/Module_scores_DEGs/Module_scores_PFC427DEGs/Results")
data=read.csv("Ast_metadata.csv")
colnames(data)
library(ggplot2)
######################################################################
###########################... |
cfa8132ce9ceacbbbaffd67e1692e72e65538425bc9b7b6fa7ce2d765b5f14ab | R | 17,857 | 486 | # Familywise-error correction specifications
fwe_spec_schema_version <- function() 1L
fwe_target_fields <- function(level = 3L) {
if (!identical(as.integer(level), 3L)) {
stop("FWE specifications currently support level = 3 only.", call. = FALSE)
}
c(
"session",
"l1_model", "l1_cope_number", "l1_co... |
7d9741f3cec0610ac380733e5d7768914cd687b9c4b4d21612551cfeab0e77c3 | R | 17,876 | 602 | # Function -------------------------------------------------------------------
#' @title Collapse/bind several `hyperSpec` objects into one object
#' @description
#' The spectra from all objects will be put into one object.
#' The resulting object has all wavelengths that occur in any of the input
#' objects, `wl.tole... |
93743efc1c6bad813793e7d56c06aa45b12a3151ce0f2530da619f4d368a136a | R | 17,953 | 610 |
#### Model-based testing of sample means ####
## -------------------------------------------
setMethod("meansTest", "ANY",
function(x, data, fixed, random, samples,
response = "y", reduced = ~ 1, byrow = FALSE,
use_lmer = FALSE, na.rm = TRUE,
verbose = getCardinalVerbose(), chunkopts = list(),
BPPARAM = getC... |
f2fe03f55aa2501cfa8386afcc67dd0fa4e2fb55f326a81c3e6e72482e532e9e | R | 17,967 | 472 | ---
title: "Reproduciblity technical replicates"
output: html_notebook
---
```{r}
library(SingleCellExperiment);library(tidyverse);library(reticulate);library(tidyverse)
library(ggplot2);library(scmap);library(fmsb);library(ggsci);library(scibet)
library(Seurat);library(M3Drop);library(ROCR);library(cluster);library(p... |
69b5b52e1f6effe030b43679aaf800c6747006cb3e1d957441d120af9147efa4 | R | 18,012 | 525 | #make heatmaps for luminex data
#1/30/2020 Annie Ciernia
library(tidyverse)
library(xlsx)
library(ComplexHeatmap)
library(dendsort)
library(cowplot)
theme_set(theme_cowplot())
library(ggpubr)
library(rstatix)
library(car)
library(broom)
#################################################################################... |
ab32996ad9da3d3b95572022cbae20cd0504b75e01b6ad26664517a8982cbc61 | R | 18,015 | 522 | #' @importFrom readr write_file
fit_model = function(
data_for_model, model_name, censoring_iteration = 1, cores = detectCores(), quantile = 0.95,
warmup_samples = 300, approximate_posterior_inference = NULL, inference_method, verbose = TRUE,
seed , pars = c("beta", "alpha", "prec_sd", "prec_intercept_1", "... |
90df4bdad858f244c3b66b4d4333c0adf4fec015d9f231c647c7ba5a79601fe8 | R | 18,026 | 393 | ## ---------- Script -----------------
##
## Script name:
##
## Purpose of script:
##
## Author: Szi Kay Leung
##
## Email: S.K.Leung@exeter.ac.uk
##
## ---------- Notes -----------------
##
##
##
##
##
## ---------- Packages -----------------
suppressMessages(library(readxl))
suppressMessages(library(dplyr))
... |
4f52a2716c4060fc411fb695b887d691df6fcce9b5df67bcf2fb137b95c4eef3 | R | 18,028 | 442 | vanilla_encoder <- nn_module(
"Encoder",
initialize = function(vae_dim, n_batch, n_covariate) {
self$n_layers = length(vae_dim)
self$layers <- nn_module_list()
self$layers[[1]] <- nn_linear(vae_dim[1] + n_batch + n_covariate, vae_dim[2])
if (self$n_layers > 3) {
for (i in 2:(self$n_layers... |
2174e099593ada8e5b59cef18bbbf2fac33ef3952d38dbde023cd8bd2dd28801 | R | 18,100 | 509 | #!/usr/bin/R
# -----------------------------------------------------------
# Aggregate and plot chunked runs of MAST + RE for DGE
# Plot the comparison between regressions on different pathologies.
# Updated: 02/11/2021
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
s... |
1f62f27bffa54ef9b897e42f76a91d57fc53ca624a8fa6f3b1bec984e526b578 | R | 18,146 | 414 | #' R6 class for pTFCE specification for one or more z-statistic images
#'
#' @importFrom R6 R6Class
#' @importFrom checkmate assert_directory_exists assert_subset assert_string
#' @export
ptfce_spec <- R6::R6Class("ptfce_spec",
private = list(
gfeat_info = NULL,
z_files = NULL,
mask_files = NULL,
resi... |
6eca622a6ef69097fc2170eef56fe41d82dbfe197dad6e82f9dfb7567c004571 | R | 18,154 | 398 | #' Plots all doublets in space
#'
#' saves as 'all_doublets.pdf'
#'
#' @param puck an object of type \linkS4class{SpatialRNA}
#' @param doublets a dataframe of RCTD results restricted to doublets
#' @param resultsdir output directory
#' @param cell_type_names list of cell type names
#' @return returns \code{\link{ggplo... |
e4716174700ec79e83da7171c66345dbf40267fec6189f10f1fad82435d9738b | R | 18,279 | 456 | vanilla_encoder <- nn_module(
"Encoder",
initialize = function(vae_dim, n_batch, n_covariate) {
self$n_layers = length(vae_dim)
self$layers <- nn_module_list()
self$layers[[1]] <- nn_linear(vae_dim[1] + n_batch + n_covariate, vae_dim[2])
if (self$n_layers > 3) {
for (i in 2:(self$n_layers... |
ca235c8168669d8cc3fb37b6c5c44837867d91167d00494020a5874e94f84816 | R | 18,326 | 527 | ---
title: "Analysis of genes with bootstrap and permutation (RD) Net [Sh, UBI] with mean"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_typ... |
ac0dd8550a2c89cefb742b865e3ecf07abea92bef1544a9c28b8a48d6dd5ddea | R | 18,329 | 526 | ---
title: "Analysis of genes with bootstrap and permutation (RD) Net [Sh, UBI] median"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: ... |
c8e699bc9346f17c4c1cc1b87079840c3f4350bc58193d53a8c2ad83fc736698 | R | 18,334 | 459 |
# Get functions
library(monocle3)
source("/net/trapnell/vol1/home/readdf/trapLabDir/sharedProjectCode/utility/singleCellUtilFuncs.R")
# modStatus <- loadMonoclePackages()
library(tidyr)
library(ggplot2)
# Note: Need bedtools loaded for this! bedtools/2.29.2
library(cicero)
# Add this to stop R from formatting into sc... |
026500208afdb99d3544e3dfdb5290713e82871b77289b322e8576cb4d6a6309 | R | 18,351 | 527 | ---
title: "Analysis of genes with bootstrap and permutation (RD) Net Sh with median"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: in... |
125f8ecc8c188bba3bd96ab4ec382aa09769e8ba2cd70085bf138dc73327a3e2 | R | 18,377 | 432 | #' Main function for plotting ASE fits from spase fit
#'
#' Takes in the result from spase and plots raw data and smoothed allele
#' probability surface
#'
#' @description This function plots stuff for spase results.
#'
#' @param matrix1 a matrix of counts where the rows are genes and the columns
#' are cells for alle... |
695fb887218d8e282cdc5efffc74b592b0ed66e544116e385eaea9410b3bd44c | R | 18,392 | 536 | #!/usr/bin/R
# -----------------------------------------------------------
# Plot/predict ligand interactions with string given
# the top DE genes in each CT
# Updated: 03/23/2021
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
source(paste0(bindir, 'multiRegion/load_... |
6a5c056fc003336a57fc8eb770d04e5c602933200eb1dc6e4d2b88fdfae07330 | R | 18,437 | 534 | #!/usr/bin/R
# -------------------------------------------------------
# Plot energy metabolism for glia and excitatory neurons:
# Updated: 11/07/23
# ------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ', 'multiRegion')
source(paste0(bindir, 'multiRegion/load_metadata.R'))
library... |
f0c1ea4751b41819efe89060e8125978972bc2fd4cd38f2ac11b66cac6c73e69 | R | 18,444 | 471 |
library(tidyr)
library(ggplot2)
library(glmnet)
library(ROCR)
library(data.table)
library(monocle3)
library(gridExtra)
library(RColorBrewer)
# Get shared functions between this and runRegressionModel.R
source("./utilityFunctions.R")
source("/net/trapnell/vol1/home/readdf/trapLabDir/sharedProjectCode/utility/singleCe... |
4be5d56831e5661313141c877ef2f9a153424891b9acdcf265a276ab7105182d | R | 18,498 | 434 | #!/usr/bin/R
# -----------------------------------------------------------
# Calculate the fraction differences, by binomial regression:
# As in:
# https://github.com/vals/Blog/tree/master/201127-cell-count-glm
# Updated 01/19/2021
# Updated 03/15/2021
# Final version is composition_02_binom_emmeans.R
# -------------... |
6223ad37eb87de216cb22da49ac1f1344ab88dd95c7948fc01917fe497b07cc0 | R | 18,514 | 421 | #' function to submit a set of jobs on a cluster to estimate many Feat level 1 models
#'
#' @param gpa a \code{glm_pipeline_arguments} object containing model specification
#' @param level GLM level to run.
#' @param model_names an optional level 1 model name used to subset the runs to submit to feat.
#' If not provi... |
b670cdb11af130e53affd8d9035eb60895692a41afca586ca7406bd4b2eb00e6 | R | 18,533 | 478 | # Functions for CovBat simulations
# by Andrew Chen
#### Data-Generating Function: Additive Covariance Effect ####
# modified in this code to allow for binary covariates
# df_gen_add <- function(mu, # p-dimension intercept vector
# Sigma, # p x p covariance matrix for error terms
# ... |
b7970ded4a898daf67b7e47afac0550a87aacb029104cc651efd4a11e82abc0c | R | 18,573 | 455 |
basepath = "/net/trapnell/vol1/home/readdf/trapLabDir/hubmap/results/2021_07_15_Greg_ATAC_Code_nobackup/"
dir.create(paste0(basepath, "archr/results/finalPlots/"))
out_dir = paste0(basepath, "archr/results/finalPlots/")
setwd(out_dir)
set.seed(7)
# load requirements
suppressPackageStartupMessages({
# libra... |
bc237a2a8b630741080f87ccc78bd69d9135b47728f297db5e729c359e968518 | R | 18,648 | 459 | #' Extract headings of (R) Markdown-syntax text as an outline
#' @inheritParams mm
#' @return Character, showing the outline.
#' @export
#' @examples
#' input <- system.file('examples/mindr-md.Rmd', package = 'mindr')
#' input_txt <- readLines(input, encoding = 'UTF-8')
#' outline(input_txt)
#' outline(input_txt, md_li... |
4e7323bc8414a4d15429074965374257482b89522e4b54dd5e682db37e25c74c | R | 18,776 | 570 | # Unit tests for collinearity_diagnostics.R functions
# Uses mock factories from helpers-mock_factories.R
# Note: create_mock_collinearity_summary() and create_empty_collinearity_summary()
# are defined in helpers-mock_factories.R and loaded automatically by testthat
# ================================================... |
2f4b336975f4adf264becded5c6a00acd79150adb91de10d819ee8519e8817b6 | R | 18,851 | 471 |
library(here)
#==============================================================================
# function that grabs gene meta data from biomaRt
getGeneMetaData <- function(){
library(biomaRt)
# load tidy expression data
reads_file = here("data","tidy_reads.csv")
reads_data = read.csv(reads_file)
# ... |
6b8ca2bf20ec579c19fc145b6a48d642ed87629857c851821212e536221a9a8d | R | 18,879 | 517 | rm(list = ls())
library(fmsb)
library(ggplot2)
library(ggpubr)
library(scales)
library(stringr)
library(asbio)
library(tidyverse)
library(car)
library(broom)
scriptsdir="/softwares/pyCAP_PLOS_Biol2024/"
source(paste0(scriptsdir, "/clean_impute.R"))
#source(paste0(scriptsdir, "/behavioral_pca.R")) #if not works due to... |
5c6a2bb3818cc2bdfa36817b212da6edbcb404608f0e0c147b873d4e60045795 | R | 18,890 | 569 | #!/usr/bin/R
# -----------------------------------------------------------
# Use the pathology to run some tests on linear mixed models:
# Last updated mid-2020 (exploratory analysis)
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
source(paste0(bindir, 'multiRegion/lo... |
586d7ca9531af89b37e708b39aab7530d0987b41e090253899eddd32bbee6907 | R | 19,245 | 494 | library(broom)
library(diptest)
library(knitr)
library(PRROC)
library(randomForest)
library(tidyverse)
library(yardstick)
metrics_data = read_tsv("eLife_Metrics.tsv") %>%
filter(!is_duplicate)
num_images = nrow(metrics_data) %>%
print() # 66253
###############################################
# Identify images wi... |
85172282ce552ac8f5ab5868c7e4be4377d7df7cddef9458ddaaa5a7f75a2c87 | R | 19,348 | 411 | suppressPackageStartupMessages({
require(argparse)
library(stringr)
})
#--------------------------------------------------------------------------------------------------------------------------
# Author: Javier de la Fuente
# Date: 05-11-2020
#
# Filename: paLDSC_JFC.R
#
# Purpose: Defining a function to perf... |
71f985c45da3ce5f05353a3ee770fbdd802fc307a8b0f709410a69b13ef7f5b2 | R | 19,368 | 367 | #Packages needed
library(car)
library(dplyr)
library(rstatix)
library(ggpubr)
library(emmeans)
library(FSA)#Dunn's test
library(performance)#r2
library(SIBER)#SIA
#Setting up main dataset
trt.data <- read.csv("Lamarre_Wilson_2024_main_data.csv")# Main dataset
#Long chain omega-3s (lcn3) in red blood cells (RBC) and c... |
9bcd12a0359aee57812048eafb2d6830e8874ae949e193eecb1a864ed7fc0821 | R | 19,400 | 371 |
library(tidyr)
library(ggplot2)
library(glmnet)
library(ROCR)
library(data.table)
# library(monocle3)
# Get shared functions between this and runRegressionModel.R
source("./utilityFunctions.R")
library("optparse")
# Get the passed parameters
option_list = list(
make_option(c("-p", "--pValFIMOcutoff")... |
4388d2dd5c94100dd8921e2b1e862df996d51f41c196b4c6bc278bace416d01f | R | 19,567 | 462 | library(phytools)
library(geiger)
library(caper)
library(ape)
library(nlme)
library(mvMORPH)
library(ggplot2)
library(dplyr)
library(hrbrthemes)
library(nortest)
library(multcomp)
library(RColorBrewer)
#Load tree file
tree = read.nexus("TreeTE.tre")
tree = ladderize(tree)
plot(tree)
#Load data
data... |
6f03f778d9b295ff13d609cea452d29d5e513199b8efde028178ebaa3375b8e5 | R | 19,587 | 442 |
library(stringr)
library(reshape2)
library(ggplot2)
print("Starting Now")
plotCurveFromRDSdataframes <- function(dfAsRDSfiles,groupTitle,
colToPlot = c("posResultMM")){
# read in the rds objects
splitNames = str_split(dfAsRDSfiles, "_folds_")
# Loop through. For each result make a separate plot
for (eachRe... |
b2a3bc2497e88c683c1f2c6bb572c81ba47b2929524e13a75c5280b979d9f711 | R | 19,598 | 508 | #' Functions for extracting and summarizing collinearity diagnostics across the GLM pipeline
#'
#' These functions provide structured summaries of regressor correlations and variance
#' inflation factors (VIF) for all subjects and runs following model setup.
#'
#' @name collinearity_diagnostics
NULL
#' Extract colline... |
2a844bf1715a499a8ed2276e79a1a95ad5674d3c5bf6711e51a644b5e9998341 | R | 19,666 | 450 |
###########################################################################################
# Load relevant packages
source("../../../sharedProjectCode/utility/singleCellUtilFuncs.R")
modStatus <- loadMonoclePackages()
print(modStatus)
source("../../../sharedProjectCode/scRNA_Seq_Background_Code/backgroundMethod... |
a1d029fb4fe7e044f4f57f067c5a9f7e679d91c2fc39f546eefbb90dca3cb118 | R | 19,813 | 444 | lassosum.pipeline <- function(cor, chr=NULL, pos=NULL, snp=NULL,
A1=NULL, A2=NULL,
ref.bfile=NULL, test.bfile=NULL,
LDblocks=NULL,
lambda=exp(seq(log(0.001), log(0.1), length.out=20)),
... |
379112a051ec95e268f9e933fbfb979fccb57d725c0d17fe4926c66937352163 | R | 19,922 | 567 | ```{r}
library(reticulate)
library(dplyr)
library(tidyr)
library(ggpubr)
library(arrow)
library(ggplot2)
library(cowplot)
library(gridExtra)
```
The gene file timing_genes.parquet comprises 1000 randomly chosen genes.
For the timing experiments, the number of regression chunks was set to 1 in all snakefiles.
The t... |
d1cee061bce1d96f05289cecb4f100958be94444e086b7f9035d43671e6ac5bb | R | 19,950 | 554 | library(corrplot)
library(dplyr)
library(RColorBrewer)
setwd("F:/Brain_region_project/Module_scores_DEGs/Module_scores_PFC427DEGs/Results")
data=read.csv("Ast_metadata.csv")
colnames(data)
library(ggplot2)
######################################################################
#########################... |
fa247b8e0f15a806068f0ad2fb8298235fe25930fe7fd3fe2c3babffd06b1f60 | R | 19,967 | 369 |
#' archstabms__optimal_library_design_src
#'
#' Library design for Src optimising WT-like abundance and activity.
#'
#' @param mochi_outpath path to ddPCA data (required)
#' @param position_offset residue position offset (default:0)
#' @param max_num_mutants maximum number of mutations (required)
#' @param explore_mut... |
5beadaf7631a84294365355056702af4d27f583d39cd55d137c5f2c4e501c79d | R | 20,110 | 778 | ---
title: "Pa for SO, UBI (L, R; Hand, Machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "10/22/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FALSE}
source("../BayesianPValue.R"... |
ed3cae0420ba2cfd1b15d8fc98c579db7bd63694407152d09d2b16f15ef8b037 | R | 20,244 | 550 | rm(list = ls())
library(fmsb)
library(ggplot2)
library(ggpubr)
library(scales)
library(stringr)
library(asbio)
library(tidyverse)
library(car)
library(broom)
scriptsdir="/softwares/pyCAP_PLOS_Biol2024/"
source(paste0(scriptsdir, "/clean_impute.R"))
# -- Set ggplot basic theme
theme1 <- theme(
panel.border = eleme... |
000d5aa13dc8adb7dc83276402094b75f6bd2c116c50a86147507283eb88c71a | R | 20,343 | 495 | library(knitr)
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ALDEx2")
library(ALDEx2)
install.packages("devtools")
library(devtools)
install_github("ggloor/CoDaSeq/CoDaSeq")
library(CoDaSeq)
library(zCompositions)
library(igraph)
library(car)
... |
71730bba92bcd2bb6be0ff893b181a25164739ae64f7bd1abcf14803a86915b4 | R | 20,421 | 600 | ---
title: "Analysis of C>T variants in scs data"
output:
html_document:
self_contained: false
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
In this document we provide an analysis of the C>T variants found in the SCS dart-seq data. The criteria for finding a C>T variant has been the fo... |
a39e03a2be8909a064389fd17fbfdae27925ca7a68febddfe1d3be3b45774168 | R | 20,445 | 546 | #' Assigns a y-label for a plot based on the target type and metric to plot
.y_label <- function(target, metric) {
# default: no label
ylab <- ""
# for specific targets (indicated by position in the plot):
# assign a label based on the metric to plot
if (target %in% c("blood_pressure_systolic",
... |
19e64b750dc3315729843944f58971c727f25fb0ec148d5b994eb01234a8b81d | R | 20,492 | 358 | # This script saves the significant clusters for each map in a SCEPTIC group analysis
#used for testing: group fixed entropy
#Sys.setenv(fsl_pipeline_file="/gpfs/group/mnh5174/default/clock_analysis/fmri/fsl_pipeline/configuration_files/MMClock_aroma_preconvolve_fse_groupfixed.RData")
#Sys.setenv(run_model_index=2)
#... |
1231e841d64659d763f1213d4678f740990312146345ebaf487cca7371dbf9c9 | R | 20,512 | 506 |
getInputDF <- function(opt, specifyFeatures=FALSE, specifiedFeatures="NULL"){
# Get the path
dirName = paste0("../2021_07_26_setup_ATAC_to_expr_data_nobackup/fileOutputs/",
"Gene_Prom_Plus_Distal_WithSequence_Sites_Max", opt$maxNdistalSites, "_Upstream", opt$promoterUpstream,
"_Do... |
5624468a9b570c03e731006a7dcf054601ddfa2557ebd442ef04702b947c151b | R | 20,539 | 856 | ---
title: "10x snRNAseq pipeline"
author: "Shahzad Khan"
date: "2023-11-01"
output: html_document
---
Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
```{r}
library(dplyr)
library(Seurat)
library(patchwork)
library(ggplot2)
install.package... |
45168fe1224e9a3183bff0eb81078fe3c2b354bdba1061eb53ad078cf8846a22 | R | 20,577 | 602 | library(tidyverse)
library(broom)
library(quickpsy)
###########################################################################
# Load and preprocess data ------------------------------------------------
###########################################################################
data <- read_csv("../../data/data_exp1... |
544207dda99345fabf3d51e8edc9ec7a4c6bcf59b33f2d4fb1994bf2659be285 | R | 20,651 | 629 | ---
title: "Melanoma single-cell DT data - Data preprocessing"
author: "Yingxin Lin"
date: "Created on 11 July 2022, last compiled on `r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
code_folding: hide
number_sections: yes
toc: yes
fig_height: 12
fig_width: 12
toc_float:
colla... |
f38f4c91633529b125d5400623428082e3aa8aa5907bf90beac4f09eafb992a8 | R | 20,673 | 664 | ---
title: "ROI analysis"
author: "Michael Lombardo"
date: "13/10/2023"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# ROI analysis
```{r, warning=FALSE, message=FALSE}
library(easypackages)
libraries("here","tidyverse","readxl","reshape2","patchwork","ggpackets","emme... |
1da6a5192fb11a9030dc0f97ecfb6b6b0e45ac26f0fd9299f894777395c425fc | R | 20,799 | 528 | coord_flipper <- function(coord_list, flip_vec) {
flipped_coord_list <- vector("list", length(coord_list))
for (i in 1:length(coord_list)) {
tmp_coord <- coord_list[[i]]
# No flip
if (flip_vec[i] == 0)
flipped_coord_list[[i]] <- tmp_coord
# Flip X
if (flip_vec[i] == 1) {
tmp_... |
571566134899e971ffc798e8f91824d97b60410fb95c90ed5e601c280370f8cc | R | 20,805 | 588 | # Build a complete backend spec by merging test-specific overrides onto defaults
make_test_backend_specs <- function(...) {
defaults <- fmri.pipeline:::default_glm_backend_specs()
overrides <- list(...)
for (nm in names(overrides)) {
if (nm %in% names(defaults)) {
defaults[[nm]] <- modifyList(defaults[[... |
a75c2ee503ad843f55ab39f6f14d6fb5a4fe98bb9ed90b66881ae550cdce95b1 | R | 20,835 | 715 | ---
title: 'SF: Read and preprocess raw stretch force measurements'
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "11/26/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FALSE}
source(".... |
9ed36a22263da3b1d87797e66f332884b9dbe3c3d851d309ab7acd5fdc72b694 | R | 20,859 | 727 |
#### SpectralImagingData ####
## --------------------------
# VIRTUAL class for containing spectra arrays
# with imaging position/pixel information
.valid_SpectralImagingData <- function(object)
{
errors <- NULL
if ( length(object@processing) > 0L )
{
is_ps <- vapply(object@processing, is, logical(1L), "Process... |
05bffb9d47a7ba6c0334b0cf52fc51acf21d46f276f7a27059809e954f0a04b0 | R | 20,869 | 390 |
library(tidyr)
library(ggplot2)
library(glmnet)
library(ROCR)
library(data.table)
library(RColorBrewer)
# library(monocle3)
# Get shared functions between this and runRegressionModel.R
source("./utilityFunctions.R")
library("optparse")
# Get the passed parameters
option_list = list(
make_option(c("-... |
4c2a636642044838184f61620aaaa5f622bcee62afdf8299e2da774c94dc76d0 | R | 20,885 | 435 | library(ggplot2)
library(Seurat)
setwd("D:/Mouse_data_integration")
pbmc=readRDS(file="GABAergic_neurons_integrated_all_class.rds")
write.csv(pbmc@meta.data,file="GABAergic_neurons_integrated_all_class_metadata.csv")
data=read.csv("GABAergic_neurons_integrated_all_class_metadata_addition.csv",row.names=1)
p... |
a508ff3ab1430d31912f9014aa7bffdcf8dcfcff024a8b421a3af379d33ddaf9 | R | 20,942 | 591 | # NEPC DNA Variant Analysis
# David Moline
# University of Minnesota
# Hwang Lab
# Last updated: 8/13/24
# Libraries ---------------------------------------------------------------
library(ggplot2)
library(dplyr)
library(tidyr)
library(reshape2)
library(pivottabler)
library(corrplot)
library(gridExtra)
library(patc... |
1eda2fa010c920a8ddbbac3614de5588f41830c61ef25d296f64c1afb8b386fb | R | 20,999 | 775 | # GRAPHIC FUNCTIONS
create_heatmap <- function(plot_data,
factorgroups,
groups2plot,
Colv = TRUE,
ColSideColors = FALSE,
RowSideColors = NULL,
clusteralg = "a... |
8e2c76ddbe2435305221d47645a4206126984c2c38eddd734c5a7ba5a113b37c | R | 21,008 | 352 | # devtools::install_github("kushnerlab/scRNAseqR")
library(EMC.SKlab.scRNAseq)
##### USER INITIALIZATION -----
### USER CONFIG ###
# general
run_name <- "sakshi_pipeV8"
project_dir <- "C:/SynologyDrive/Projects/scRNAseqR"
samples_dir <- file.path(project_dir, "data/samples/")
# sample analysis
sample_names <- c("N... |
afe8176e6a81948d7312a57dffcbc65345623bad3f07b3393148f043285a8641 | R | 21,088 | 680 |
###########################################################################################
# Load relevant packages
source("/net/trapnell/vol1/home/readdf/trapLabDir/sharedProjectCode/utility/singleCellUtilFuncs.R")
# modStatus <- loadMonoclePackages()
# print(modStatus)
library(monocle3)
source("/net/trapne... |
d04b49194bebc68cec70ea57083647c1b73130be98f26f3a9f76058f77427a62 | R | 21,281 | 353 | #' Analyse individual samples
#'
#' Performs Seurat SCTv2 analysis workflow on individual samples.
#'
#' @param samples_dir Root directory of samples.
#' @param sample_name Current sample name, used to match in samples_dir.
#' @param output_dir Package home directory, used to create output directory for results.
#' @pa... |
8db854496e26ee8fc719c174f8ed968bfb3d0f5c255abc0c06707b132f93cba7 | R | 21,406 | 549 |
# 4-7-22 add
.libPaths('1')
# Get functions
library(monocle3)
source("/net/trapnell/vol1/home/readdf/trapLabDir/sharedProjectCode/utility/singleCellUtilFuncs.R")
# modStatus <- loadMonoclePackages()
library(tidyr)
library(ggplot2)
# Note: Need bedtools loaded for this! bedtools/2.29.2
library(cicero)
# Add this to... |
9632ceb30086f5fbdbe10f9821218d9ae65e27b84965ace68ad862ac42649190 | R | 21,467 | 719 | ---
title: "Morphometric_Quantification_RAgas"
output: html_document
date: "2024-01-02"
---
```{r}
library(tidyverse)
library(readxl)
library(cowplot)
library(tidyr)
library(reshape2)
library(viridis)
library(scico)
library(RColorBrewer)
# Theme setting
my_theme <- theme_bw(base_size = 12, base_family = "") +
th... |
1ba92a3d401ae18f06baa4df9b4af510b024fb69074644e3abb52a47168ddd8d | R | 21,619 | 629 | #' Produces forecasts from fitted forecast objects
#' @param forecast_obj A fitted forecast object from the forecast package
#' @param lambda The applied box-cox transformation parameter
#' @param bias_correction Whether or not to use bias correction when doing
#' box-cox re-transformation
#' @param forecast_produced_... |
e45162860797f7adeeea2a20339b6d3a91811b208e2b0b9ba9cfc8e5bfa22045 | R | 21,791 | 373 | #!/usr/bin/env Rscript
## ----------Script-----------------
##
## Author: Szi Kay Leung (S.K.Leung@exeter.ac.uk)
## Mapt 4R vs 3R
## Trem2 proteogenomics characterisation
## --------------------------------
suppressMessages(library("cowplot"))
suppressMessages(library("ggh4x"))
## ---------- config file -------------... |
230a61579bbcf26394873a07d3c9361181a87415054ae452e51f3462b81e5962 | R | 22,204 | 543 | coord_flipper <- function(coord_list, flip_vec) {
flipped_coord_list <- vector("list", length(coord_list))
for (i in 1:length(coord_list)) {
tmp_coord <- coord_list[[i]]
# No flip
if (flip_vec[i] == 0)
flipped_coord_list[[i]] <- tmp_coord
# Flip X
if (flip_vec[i] == 1) {
tmp_... |
5d5ff1c149ab339d312c3182959a1ec44d8e2e030b32ff862962a8493c856e95 | R | 22,304 | 438 | #' Convert R code into FreeMind mind map code
#' @inheritParams mm
#' @export
#' @return Character, FreeMind mind map code.
#' @examples
#' input <- system.file('examples/mindr-r.R', package = 'mindr')
#' input_txt <- readLines(input, encoding = 'UTF-8')
#' output_txt <- r2mm(from = input_txt)
#' output <- tempfile(pat... |
1d38b9ef0e95409a761a7314535f67cfefc38b6357662dcbc8e939bf3ae19c2d | R | 22,369 | 670 |
#### Simulate mass spectra ####
## ----------------------------
simulateSpectra <- function(n = 1L, npeaks = 50L,
mz = rlnorm(npeaks, 7, 0.3), intensity = rlnorm(npeaks, 1, 0.9),
from = 0.9 * min(mz), to = 1.1 * max(mz), by = 400,
sdpeaks = sdpeakmult * log1p(intensity), sdpeakmult = 0.2,
sdnoise = 0.1, sdmz = 10... |
b30de6cf77e45dd13ad146f023ef2fa1a8b36f0ab660a40ba267f69bdec47157 | R | 22,437 | 546 |
basepath = "/net/trapnell/vol1/home/readdf/trapLabDir/hubmap/results/2022_04_03_redoATAC_proc_nobackup/"
dir.create(paste0(basepath, "archr/results/NB11/"))
out_dir = paste0(basepath, "archr/results/NB11/")
setwd(out_dir)
set.seed(7)
# load requirements
suppressPackageStartupMessages({
# library(ArchR)
library(mo... |
ef46122d035cb7dc715ccb2713874c127dd0c8b1c2aca00d051def60583360ac | R | 22,445 | 713 | ---
title: "Vertical Analysis Pa: Ctrl, BNI, FNA (hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
... |
8559eaf428e27525f7a2709709ff7d717aefa55b41cc2da9fa1ebecbc187a6ff | R | 22,506 | 513 | suppressPackageStartupMessages({
library(ggplot2)
library(GGally)
#library(GSEABase)
library(limma)
library(reshape2)
library(data.table)
library(knitr)
#library(TxDb.Hsapiens.UCSC.hg19.knownGene)
library(stringr)
library(NMF)
library(rsvd)
library(RColorBrewer)
library(MAST)
})
... |
2a805a33c84e2788a709397c50a38f629c82e24fc325a81ac3ddd7e0d95b7e52 | R | 22,548 | 637 | ## Tests for brms-style smooth terms (s(), t2()) in sccomp formulas.
##
## The unit tests at the top do not need cmdstan: they only exercise the
## R-side machinery in `R/smooths.R` and the patched `parse_formula()`.
## The end-to-end smoke test does need cmdstan and is gated by
## `skip_cmdstan()`.
library(dplyr)
# ... |
3deff3c628cde8f7287e20da6af63869cc3e1d8c15782525bed3db087ab51826 | R | 22,672 | 618 | #!/usr/bin/R
# -----------------------------------------------------------
# Aggregate and plot chunked runs of MAST + RE for DGE
# Updated: 01/21/2021
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
source(paste0(bindir, 'multiRegion/load_metadata.R'))
library(tidyr)... |
6480f8f3dc0e064eac3f5a568860c1324d099013ba39122a435388bd079202fb | R | 22,755 | 454 |
#' ---
#' title: "Pairwise sample analysis output"
#' author: "Tomas Bjorklund"
#' output:
#' pdf_document:
#' highlight: tango
#' geometry: margin=0.6in
#' fontsize: 9.5pt
#' ---
#' This script presents overview ploits and top candidates.
suppressPackageStartupMessages(library(knitr))
#+ setup, include=FALSE
... |
6fa0165f161e01f40c5eac22f3b5f174956a99ffc100bf08a6817e75fd885ec1 | R | 22,769 | 682 | #' Load in citations for deduplication
#'
#' This function loads in a citation file within the shiny app
#' @import RefManageR
#' @importFrom glue glue
#' @import bibliometrix
#' @import XML
#' @importFrom utils read.csv read.table
#' @param paths Relative paths to the citations file or files
#' @param method Import m... |
1ac427ea35e2bebae87a1d29d74d31c048e2747b175aabe379ca51252ac214f8 | R | 22,882 | 353 | # Szi Kay Leung: sl693@exeter.ac.uk
suppressMessages(library("data.table"))
LOGEN <- "/lustre/projects/Research_Project-MRC148213/lsl693/scripts/LOGen/"
source(paste0(LOGEN,"/transcriptome_stats/read_sq_classification.R"))
source(paste0(LOGEN,"/target_gene_annotation/summarise_gene_stats.R"))
source(paste0(LOGEN,"/com... |
6ea196fe56744c20f664b44004d2d16daa7ef702d733ea96a732fdd3f9dc714c | R | 22,960 | 530 | #' sccomp_remove_outliers main
#'
#' @description
#' The `sccomp_remove_outliers` function takes as input a table of cell counts with columns for cell-group identifier, sample identifier, integer count, and factors (continuous or discrete). The user can define a linear model using an input R formula, where the first f... |
098126cfdef73c3302846493590340624410102d6a6e30c643a44acdc62f5211 | R | 23,040 | 552 | ---
title: "code_for_figures"
author: "Yuvarani Masarapu"
date: "`r Sys.Date()`"
output: html_document
---
```{r}
library(SeuratObject)
library(Seurat)
library(harmony)
library(sctransform)
library(Matrix)
library(RColorBrewer)
library(ggplot2)
```
# Load the seurat object containing the analysed spatial barcodes and... |
8d2a2580701aec10e6b27e5febdf1d9785dc0c1cd4006287217abe8694d205f3 | R | 23,079 | 645 | library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
library(Seurat)
#######################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Oli_integrated_batch3000_leiden_res02_final.rds")
#Add official ... |
a0f6829231bf5d0f28c13907d04bdfbf07a11cddd971c48c322340953ec5f2ed | R | 23,107 | 578 | library(knitr)
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ALDEx2")
library(ALDEx2)
install.packages("devtools")
library(devtools)
install_github("ggloor/CoDaSeq/CoDaSeq")
library(CoDaSeq)
library(zCompositions)
library(igraph)
library(car)
... |
c45b91fd087b10b42d0b3c81bf209a3d041bbdda9efaa357fbc97c7630549830 | R | 23,121 | 423 |
#' ---
#' title: "Heatmaps generated from HMM peptide clustering"
#' author: "Tomas Bjorklund"
#' header-includes: \usepackage{longtable}
#' output:
#' pdf_document:
#' highlight: tango
#' geometry: margin=0.6in
#' fontsize: 9.5pt
#' ---
#' This script clusters Polypeptide motifs using the Hammock hidden Markov ... |
9fc3b906d229c9ad5f1f83df5213c4849a44c0753944ffa99d40b3e845d02359 | R | 23,126 | 500 | if (!require("dplyr")){
install.packages('dplyr')
library(dplyr)
}
if (!require("lme4")){
install.packages('lme4')
library(lme4)
}
if (!require("nlme")){
install.packages('nlme')
library(nlme)
}
if (!require("splines")){
install.packages('splines')
library(splines)
}
if (!requi... |
cf034bfaa08bc395ebcec39c6a19288aac9acb7694b16318d53995320c9b3708 | R | 23,171 | 493 | ####################################################################################################
###
### File: 06_trial_coordinates_differences.r
### Purpose: Computing the differences in trials
### Authors: Gabriel Rodrigues Palma, Rafael Moral
### Date: 03/08/23
###
#########################################... |
5cd9b863a27987ed298c890d945f8cb49055ccc299f90468e30c2b200ca3c64d | R | 23,191 | 623 | #!/usr/bin/R
# --------------------------------------------------------------
# Plot the two correlation scores + directionality
# Use this to partition neuronal DEGs
# Perform gene set enrichment on specific partitions
# Updated: 06/22/2023
# --------------------------------------------------------------
library(cbrba... |
4b7c33e8e003b330e36a2eaa169e2ad452d16d0024c126db58aada65b63a14bf | R | 23,280 | 571 | #!/usr/bin/R
# -----------------------------------------------------------
# Use the pathology to run some tests on linear mixed models:
# Using Liang's Nebula package to run the fast NBLMM
# Basic overall + per-region interactions, for relevant subtypes
# Updated: 10/28/2020
#
# Compare multiple models (in a per-regi... |
7bf702c3ec0a04528f4e2f36843d5b815bf2d8a826a8a4b10fe4ce55aea25f63 | R | 23,390 | 569 |
rm(list = ls())
# the code we are using is an amended version of radarchart function from fmsb library:
# install
# install.packages("fmsb")
# Library
library(fmsb)
library(ggplot2)
library(ggpubr)
library(scales)
library(stringr)
library(data.table)
# -- Set ggplot basic theme
theme1<- theme(panel.border = element... |
612af3bc2498d18a0b36b2733afa67f787671b2fd1a754744a7fd1050ed5f0fb | R | 23,395 | 298 | #' Creates an \code{\linkS4class{RCTD.replicates}} object across multiple \code{\linkS4class{SpatialRNA}} replicates
#'
#' Applies the \code{\link{create.RCTD}} function for each \code{\linkS4class{SpatialRNA}} replicate inputted using a
#' scRNA-seq reference \code{Reference} object.
#'
#' @param spatialRNA.replicates... |
2bc8da406f77794967851c73ccc5ca3a494e47c66d850f910a9bc9958ceb0140 | R | 23,524 | 419 |
#' ---
#' title: "Heatmaps generated from HMM peptide clustering"
#' author: "Tomas Bjorklund"
#' header-includes: \usepackage{longtable}
#' output:
#' pdf_document:
#' highlight: tango
#' geometry: margin=0.6in
#' fontsize: 9.5pt
#' ---
#' This script clusters Polypeptide motifs using the Hammock hidden Markov ... |
d657cf9e9fd38176dc0079ee5faac88a4197f18cc776278e83b6d055f0edda00 | R | 23,588 | 454 | filter_genes <- function(puck, threshold = 5e-5, batch_size = 1000, remove_genes = NULL) {
message(c('filter_genes: filtering genes based on threshold = ', threshold))
gene_means <- numeric(length(rownames(puck@counts))); names(gene_means) <- rownames(puck@counts)
n_batches <- ceiling(length(gene_means) / batch_s... |
f9ef18107dc064b2736d03b6ff18dd03db0da9edf4056bac41a884b749ffe264 | R | 23,797 | 814 | ---
title: "PAS UBI vs SO (L, R; hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "9/23/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FALSE}
source("../Bayesian... |
e4540ffbebc8a1e9350e3816bc313063f6669a227c2afd8a1bb1f975b8fb1c01 | R | 23,818 | 414 | ```{r init}
library(Matrix)
library(tidyverse)
library(biomaRt)
library(monocle3)
library(rgl)
library(tricycle)
library(SignacX)
library(princurve)
library(ggplot2)
library(Hmisc)
library(pheatmap)
library("ComplexHeatmap")
library(circlize)
library(dplyr)
library(ggrepel)
library(latex2exp)
library(scales)
```
```{r... |
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