sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d5d7ee26f807935d101a1ea279c02ea9cc7aa7d891f1ed10fb6ef34ca0619342 | R | 16,119 | 418 | # Load required R libraries
library(SKAT)
library(parallel)
# import
# Define the function to perform the SKAT test
perform_skat_test <- function(gene_name, gene_chromosome, region_start, region_end, gene_snps, genotype_prefix, result_folder, result_file, is_binary = TRUE) {
tryCatch({
genotype_prefix <- paste0(g... |
99d3492ad5be12a497e9a584cfd95b14c50821343061c31180c74a357a088cb7 | R | 16,126 | 529 | #' @importFrom methods is new
#' @importFrom R6 R6Class
#' @importFrom utils read.delim
#' @importClassesFrom Matrix dsparseMatrix dsparseVector dgCMatrix dgRMatrix CsparseMatrix RsparseMatrix
Predictor <- R6::R6Class(
classname = "lgb.Predictor",
cloneable = FALSE,
public = list(
# Initialize will create a... |
f770ac2e30d326923bcb3c1bc14b00abf4c4985a62913abcbfb43007039d6fbb | R | 16,149 | 651 | # Test product_to_platesize ----
test_that(
"product_to_platesize works",
{
expect_equal(
object = product_to_platesize(product = "Target 96"),
expected = 96L
)
expect_equal(
object = product_to_platesize(product = "Target 48"),
expected = 48L
)
}
)
# Test olink_display_p... |
8b2f5e56891d271aad7839e76952cdaa5842186f957adfdbbaff7a3d66d3a2b6 | R | 16,153 | 472 | # ==============================================================================
# Script Name: Correlation_Heatmap.R
# Description: Calculate Pearson correlation coefficients between samples based
# on TPM expression matrix and generate a heatmap.
# Input: gene_tpm.addAnno.xls
# Output: F... |
bc51a19c96e1d58642658dbf834762c9f49b613636bd100e0d9b3aa2f87fc72b | R | 16,169 | 308 | #' Run Iterative Regional Ablation on Discovered Biomarkers
#'
#' Reads a CSV file of discovered biomarkers (typically from `run_experiments`),
#' and for each biomarker, performs an iterative single-region ablation using
#' `region_ablation` to minimize aggregated Sample Size Estimate (SSE).
#' Results of the ablation... |
dad457350702570a412b3c26abc5d6c6eccbb55f5d2cd3e8da519663fa28b145 | R | 16,188 | 326 | # Libraries are loaded from R/_libraries.R
message("[CLUSTER_DATA_UPLOAD] Loading cluster_data_upload module")
# Define a named vector of choices for clustering methods
clusterdata_file <- c("Continue from clustering", "Upload saved R data")
names(clusterdata_file) <- c("memory_data", "uploaded_data")
message("[CLUST... |
0b3399fa4a471bd67438ea13a75176ae9f9fbab96d9be2cf8d8aa021a4a47d1f | R | 16,199 | 589 | #' Get names of all Olink platforms.
#'
#' @author
#' Klev Diamanti
#'
#' @keywords internal
#'
#' @return A character vector with names of all Olink platforms.
#'
get_all_olink_platforms <- function() {
# return all Olink platforms
olk_all_platforms <- accepted_olink_platforms |>
dplyr::pull(
.data[["n... |
3538fc1445dff1b47667727e0522a36ab30253b976b25a62824c2abc14f85f86 | R | 16,230 | 355 | #' Function to add bezier control points for horizontal layout.
#'
#' @param data A \code{data.frame} containing x and y coordinates.
#' @param strength The proportion to move the control point along the y-axis towards the other end of the bezier curve.
#' @return A \code{vector} of rescaled coordinate values.
#' @auth... |
5f6b26599c329f4779b3068505f45cbb79bdbcae36a7bee58d5d1186746d7636 | R | 16,336 | 359 | #' Function to break PAF alignment into matching bases between query and target sequence.
#' In addition, locations of inserted bases in query and target sequence can be reported as well.
#'
#' @param paf.aln A \code{data.frame} or \code{tibble} containing a single PAF record with 12 mandatory columns
#' along with CIG... |
fccf2feeb7dde12de97d9be4658b30dee744576e7c1d773ba3fc4b7d1963ccb2 | R | 16,340 | 412 |
################################
## Functions to do subsetting ##
################################
#' @title Subset groups
#' @name subset_groups
#' @description Method to subset (or sort) groups
#' @param object a \code{\link{MOFA}} object.
#' @param groups character vector with the groups names, numeric vector with... |
2b5d29fb274683a545e182667634df3f89aade003700abf2b93d9882da109e45 | R | 16,349 | 380 | # Yang Yang 2020
# This script is for analyzing chromothripsis, using modified ShatterSeek code.
#
# Input files:
# 1. independent-specimens.wgs.primary-plus.tsv
# this file is used to choose independent specimens
# 2. analyses/copy_number_consensus_call/results/pbta-cnv-consensus.seg.gz
# CNV file is needed in shatter... |
cbd85c444ef94cf640ba978203d7b3d8bd98ba9b1a673ea3902b870a9ca0f797 | R | 16,354 | 402 | ---
title: "Annotate SNV subtype status for LGAT biospecimens"
output: html_notebook
author: K S Gaonkar
date: 2020
---
In this PR we will use identify LGAT biospecimens from pathology diagnosis and annotate subtype specific SNV status per biospecimen.
As per [issue](https://github.com/AlexsLemonade/OpenPBTA-analysi... |
dc098a95fc4d77956dc7e68206eba516471629c7920bc4299bda7559c33d566b | R | 16,360 | 521 | # The working directory is the directory that contains this test R file, if this
# file is executed by test_dir
#
# testthat package is loaded, if this file is executed by test_dir
context("tests/test_get_opr_mut_freq_tbl.R")
# import_function is defined in tests/helper_import_function.R and tested in
# annotator/tests... |
3ab055904529e6f3b1475b195b0fe78fb065903f7b039e600fed85acf88802e7 | R | 16,403 | 258 | library(dplyr)
library(parallel)
library(purrr)
library(tidyr)
source("/cbica/projects/luo_wm_dev/two_axes/code/results/main_figures_functions.R")
# Spin tests for Figures 6 and 7
## saves out the spun p-values, empirical test statistic, and dof where appropriate in a csv for each dataset
##################
# Set Va... |
9ea00a052a58a96448f89a9eb50659460e9503af12385c2b0cb49eb5cc358860 | R | 16,421 | 356 | #' Run a Defined Set of Single- and Multi-Cohort Discovery Experiments
#'
#' Orchestrates multiple biomarker discovery runs using specified single-cohort
#' (`biodiscvr_single`) and multi-cohort (`biodiscvr_multicohort`) functions.
#' Executes a sequence of experiments defined in a configuration file, including
#' base... |
669ce8b65f615d4edadac24411dbda74f4503fb39f6f7bc656bf87f7acda61a5 | R | 16,453 | 401 |
# ==============================================================================
# S4_clustering.R
# Server logic for Step 3: Clustering Analysis and Cell Annotation
# Implements:
# - Step 3.1: Preprocessing & Data Assessment (Normalization, Integration, PCA)
# - Step 3.2: Clustering Algorithm Selection & Visual... |
7a7df69989b6425802e89e7fd248c7693f75d0a3cd4dbeb1f8d1664883fa57b5 | R | 16,512 | 494 | # Differential expression analysis of RNA-seq data
# Budhaditya Basu
# NIHes1-KO vs Control samples
#Raw data is available at SRA data: PRJNA1256699
#https://www.ncbi.nlm.nih.gov/sra/PRJNA1256699
library(DESeq2)
library(ggplot2)
library(pheatmap)
library(RColorBrewer)
library(org.Mm.eg.db)
library(tidy... |
6cab9d039e17588da37c0eced0c8b189b5b29e88aede93d075c2cf596f2eda33 | R | 16,526 | 388 | rm(list=ls())
## COMMON LIBRARIES AND FUNCTIONS
source("100.common-variables.r")
source("101.common-functions.r")
source("200.variables.r")
## SCRIPT SPECIFIC LIBRARIES
## SCRIPT SPECIFIC FUNCTIONS
## SCRIPT CODE
##
##
for( TESTING in c(1) ) {
Print.Disclaimer( )
##
## Load and clean real data
## (... |
6ea27fbe4fcb8e86387d42cc81db57bb35badd0bc5a879842f2fde8189c8efe0 | R | 16,538 | 418 | ---
title: "Figure 3"
author: "Maksym Zarodniuk"
date: "Compiled on `r format(Sys.time(), '%d %B, %Y')`"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
```
```{r, include=FALSE}
library(knitr)
library(DESeq2)
library(tidyverse)
library(ComplexHeatmap)
s... |
312795f6dfecca3a941593cf70c30e00f1a700cd2e63969c93d9ce2a7a511bb0 | R | 16,553 | 461 | # S. Spielman for ALSF CCDL, 2022
#
# Makes PDF panels from the `immune-deconv` module for Figures 5 and S6, specifically:
## Panel 5C, immune cell fractions across immune cells, faceted by cancer group
## Panel 5E, CD274 expression across molecular subtypes
## Panel S6E, immune cell fractions across molecular subtypes... |
e546675a8c874e0ba0a17dc92d46918025bdac9d2bd37ce590859e3e634ee72d | R | 16,578 | 347 | ##' generate network based on Enrichment results
##' @rdname richNetwork
##' @param object richResult,GSEAResult object or dataframe
##' @param gene vector contains gene names or dataframe with DEGs information
##' @param top number of terms to display
##' @param pvalue cutoff value of pvalue (if padj set as NULL)
##' ... |
1f0674eb2946afbeee9f018da323ad1245fe895403eafa39869e96f28f8d5d89 | R | 16,610 | 419 | #' Density of empirical distribution
#'
#' @param x Vector of quantiles
#' @param xs Vector of possible values; if continuous, when sorted, each value
#' of xs represents the lower limit of the interval to which the corresponding
#' probability applies, while the next value of \code{xs} represents the upper
#' bound... |
29c64211c21ccdd0bee26bd6370dbf5057616a27d729d6dfcb3e640a9c1447c1 | R | 16,668 | 412 | # --- test-mult-g-comp.R ---
#
# This script contains a comprehensive test suite for the `mult.g.comp` function.
# It should be placed in the `tests/testthat/` directory of the R package.
# The `mult.g.comp` function is assumed to be available in the test environment,
# typically handled by `devtools::test()` or `devto... |
3428a183261d5bd0acba2e8f7b321e5365c27dbd7f814b8532340bb4dcbb125e | R | 16,701 | 257 | #' bayesReact method for motif activity inference
#' @description
#' Function for predicting motif activity from ranked sequence data using a simple Bayesian model implemented in STAN.
#' bayesReact_core can be run locally and used for motif activity inference for a set of motifs across a small data set.
#' For larger ... |
55a06f1a6e1c632b371e0bc12532d6119394661712bbb7a61361a7d75e246460 | R | 16,722 | 555 | #' Checking for needed packages and valid inputs
#'
#' @param colnames Character. Determines how to label the columns.
#' Must be 'assay', 'oid', or 'both' (default 'both').
#' @param ... Additional arguments used in \code{pheatmap::pheatmap}
#'
#' @return Null or error/warnings
#'
#' @keywords internal
#' @noRd
#'
plo... |
7624e81bd72cafc19315196dd4157ae4f1ee98aa3d08c679cd00b0b3493e9d8a | R | 16,725 | 434 | # 3. Neuroimmune DRAs ----------------------------------------------------------
## 3.1 Load packages and functions ---------------------------------------------
source("./codes/my_packages.R")
source("./codes/my_functions.R")
# set working directory
setwd("./data/Neuro_tables/GSEbatch/")
getwd()
## 3.2 Network neu... |
8c33b6944c25e5a27c983a8cddfa88a2008b50fc9a3334d157878a5174e6e99b | R | 16,822 | 555 | ---
title: "Results of Univariate Analysis"
author: "Kenji Fujisaki"
date: '`r format(Sys.time(), "%Y/%m/%d")`'
output:
html_document:
toc: true
toc_float: true
toc_depth: 4
number_section: true
code_folding: hide
---
**What does this script return?**
Descriptive statistics and test results for u... |
de4fd677a648545224d0731715c8b612f3f3da36441af9389a7c4ff52496b23b | R | 16,894 | 431 |
#' @title create a MOFA object
#' @name create_mofa
#' @description Method to create a \code{\link{MOFA}} object
#' @param data Input data can be in several formats:
#' \itemize{
#' \item{\strong{data.frame}:}{ it requires 5 columns: sample, group, feature, view, value.
#' The "group" column indicates the conditi... |
b5d386596ee2c43fe280717e4a93431680f179bfe8ec2ed43c75cdf6ffd0db4e | R | 16,956 | 401 | #' Run PCA on a BANKSY matrix.
#'
#' @details
#' This function runs PCA on the BANKSY matrix
#' (see \link[Banksy]{getBanksyMatrix}) with features scaled to zero mean and
#' unit standard deviation.
#'
#' When \code{lazy=TRUE}, PCA is computed without materializing the full BANKSY
#' matrix in memory using an implicit ... |
ed979d7c25e6e11ad42ed2fb3c4f24827067da33db141e0dc47204837bb16d3f | R | 16,993 | 260 | #' bayesReact method for motif activity inference
#' @description
#' Function for predicting motif activity from ranked sequence data using a simple Bayesian model implemented in STAN.
#' bayesReact_core can be run locally and used for motif activity inference for a set of motifs across a small data set.
#' For larger ... |
38461769aae52ee8b3e5ec0b8459d6f3959b94c1024d979801aa0d4920b7e440 | R | 17,068 | 408 | ---
title: "Tp53 SNV hotspots"
author: "K S Gaonkar, Jo Lynne Rokita"
output: html_notebook
params:
base_run:
label: "1/0 to run with base histology"
value: 0
input: integer
---
In this notebook we will add TP53 alteration status as discussed in [#837](https://github.com/AlexsLemonade/OpenPBTA-analysis/i... |
021c6ea39649b61676482ac0b08130276c447f02997fcfdf2a996e411d8dfe09 | R | 17,078 | 236 | #' bayesReact parallelization for motif activity inference on large data sets
#' @description
#' This function is a wrapper for bayesReact_core(), allowing for motif activity inference on large data sizes, including single-cell atlases.
#' bayesReact_parallel() performs data partitioning and currently utilizes the Slur... |
7720be80b3f97d6bf9506302e14b77b84a2df37c6bea796d7913146280daba1f | R | 17,111 | 427 | ##' richGO
##'
#' @name richGO
#' @title GO Enrichment analysis function
#' @param x vector contains gene names or dataframe with DEGs information
#' @param godata GO annotation data
#' @param ontology BP,MF or CC
#' @param pvalue cutoff pvalue
#' @param padj cutoff p adjust value
#' @param organism organism
#' @param ... |
c4dcf8d5558db40d9cf0e64c0333046e91814018fc38ea96113c3087c583aeed | R | 17,144 | 475 | # This script uses the original first version of the cross-product normalization
# for each pair of Olink products. Specifically, we will use:
# - OlinkAnalyze v 4.0.1 for Olink Explore HT - Olink Explore 3072
# - OlinkAnalyze v 4.2.0 for Olink Reveal - Olink Explore 3072
# - OlinkAnalyze v 4.4.0 for Olink Explore HT -... |
8c18db876384ea7063974878bcc83022eb8ff106cc45583dbdece2a015e0573e | R | 17,147 | 238 | #' bayesReact parallelization for motif activity inference on large data sets
#' @description
#' This function is a wrapper for bayesReact_core(), allowing for motif activity inference on large data sizes, including single-cell atlases.
#' bayesReact_parallel() performs data partitioning and currently utilizes the Slur... |
d8e4062f9edf2eda1028971ae065921ece04769c88ff1464ec4be19742f33273 | R | 17,155 | 423 |
############################################
## Functions to load a trained MOFA model ##
############################################
#' @title Load a trained MOFA
#' @name load_model
#' @description Method to load a trained MOFA \cr
#' The training of mofa is done using a Python framework, and the model output is s... |
d076caceff6564fc87b735ca134e6629a46e9f3a2e8119e13c8870b0381f4aa1 | R | 17,161 | 339 | #' Visualize genome-wide PAF alignments.
#'
#' This function takes genome-wide alignments of de novo assembly to the reference genome PAF format
#' and visualize the alignments with respect to all reference chromosomes in a single plot
#'
#' @param chromosomes User defined chromosomes (target sequence IDs) to be plotte... |
f8a98e5c9de20135ec8191c8861b88fc9502458ff28399094fe906d5e37fff15 | R | 17,164 | 565 |
library(Biobase)
library(GEOquery)
library(Seurat)
library(readxl)
library(ggplot2)
library(dplyr)
library(harmony)
library(GenomicRanges)
library(Seurat)
library(patchwork)
library(cowplot)
library(data.table)
library(scales)
library(org.Hs.eg.db)
library(rtracklayer)
library(gghighlight)
library(dplyr)
library(Seura... |
6c22f7af4b869328339785bf6fd7aa0494ea7d3989327f19746b76d661d25ba4 | R | 17,166 | 512 | library(miloR)
library(SingleCellExperiment)
library(scater)
library(scran)
library(dplyr)
library(scuttle)
library(ggrepel)
library(Seurat)
library(ggplot2)
library(gghighlight)
library(ggbeeswarm)
library(ggpubr)
library(RColorBrewer)
library(knitr)
library(gprofiler2)
######################
#### 3D vs FOETAL ####
#... |
be235ce487c58b7f7da4ef46cd010da7c9f695c017317cef532a70f7600b71e2 | R | 17,169 | 351 | options(Seurat.object.assay.version = "v3") # use old Seurat object version
library(Seurat)
library(ggplot2)
library(dplyr)
library(stringr)
library(ggpubr)
library(gridExtra)
library(cowplot)
source("~/PD_project_analysis/scripts/MV_utils.R")
dir_main <- ("/home/ubuntu/PDSCRBNG/18_04_24_merFISH_data") # Directory w... |
d16804123d00f8bd52a9d8111a34edcf6f598be4664aab71d2c88b1401e52f61 | R | 17,183 | 634 | # Test reference results from reference_results.rds against refResults.RData
testthat::test_that(
"reference results match",
{
# environments to avoid name conflicts ----
# new version
env_new_v <- new.env()
# get data if available, otherwise skip the test
lst_new_v <- get_example_data("refere... |
99be5a7af680571cb631bcb091f68f0ebe8949447de0321fbe0e0a4b903ee39b | R | 17,223 | 475 | # Functions for constructions
#
# Author: Xuran Wang
#' Construct artificial bulk tissue expression from single cell data
#'
#' Artificial bulk tissue expression is generated by adding gene expressions of all cells from
#' same subjects.
#'
#' @param sce SingleCellExperiment, single cell dataset
#' @param cl... |
b55122125215ff099cb6cec1eb6cc5799d4a4fb14b5e41de9d892fd0986eb728 | R | 17,230 | 368 | #' @name lgb_shared_params
#' @title Shared parameter docs
#' @description Parameter docs shared by \code{lgb.train}, \code{lgb.cv}, and \code{lightgbm}
#' @param callbacks List of callback functions that are applied at each iteration.
#' @param data a \code{lgb.Dataset} object, used for training. Some functions, such ... |
da77fcc3829cbd8287ada15023ccb8c929cfcc85d7d578c4da7c5e5df13e049b | R | 17,253 | 391 | # Meta-analysis of scRNA-seq data of Neocortex developmental time points - Part 1 : QC ---------------------
# E10-P4
# Rahul Jose
# SCB, RGCB
# October 2024
# Primary Aim :
# For the identification of NIHes1 and NDHes1 cells across developmental timepoints
# Data --------------------------------------------... |
78f6de6f7f85d326a0059f746d2f6c08624bd72b746e6720cdd92eb76f571720 | R | 17,255 | 464 | # pROC: Tools Receiver operating characteristic (ROC curves) with
# (partial) area under the curve, confidence intervals and comparison.
# Copyright (C) 2010-2014 Xavier Robin, Alexandre Hainard, Natacha Turck,
# Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez
# and Markus Müller
#
# This program is free soft... |
aa309a79bf00b57ea47bc71c50ad2796cbe8ffae5a25d03bb8241cd8decf409e | R | 17,263 | 609 | #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#################### VIRIDIS SHORTCUTS ####################
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#' Viridis Shortcuts
#'
#' Quick shortcuts to access viridis palettes
#'
#' @return A color pale... |
59ab54e50473b2c4365916ee25eca569f4cf29d1833f2107cd79530ead06ff7c | R | 17,303 | 483 | # TODO: Add comment
#
# Author: fec
###############################################################################
library(R6)
library(survival)
library(dplyr)
library(caret)
FeatureReductionContainer <- R6Class("FeatureReductionContainer",
public = list(
initialize = function(outcome, features) {
... |
9600f3a505acf0d2aa3611c6c7edf9d43fd9b85a252c4dca859b5cfde149aca6 | R | 17,370 | 452 | rm(list = ls())
# Packages ----
library(dplyr)
library(gamlss)
library(ggplot2)
theme_set(theme_light())
source("code/f_derivedPCA_WI_m.R")
# library(FactoMineR)
# library(factoextra)
COL = c(black = "black"
,red = rgb(100, 38, 33, maxColorValue = 100)
,green = rgb(38, 77, 19, maxColorV... |
64c463f79da33e5bea66e24d02d21e1632eea0663008d5bdf159c7abf129bb31 | R | 17,390 | 475 | ## RareComb helpers (minimal set used in the pipeline)
library(dplyr)
library(tidyr)
library(tibble)
library(biomaRt)
library(parallel)
library(doParallel)
library(foreach)
## number of cores for parallel sections
if (!exists("numCores")) {
nc <- parallel::detectCores()
numCores <- max(1L, nc - 1L)
}
## Ensembl ... |
4d94b498200320256a6a012e407f9f43b0ec93070622a39d127fca6cb4baa778 | R | 17,446 | 433 | # Using control qMRI data to fit LMs and project PD ST scores
# load in some libraries
library(ggplot2)
library(tidyverse)
library(reshape2)
library(ggpubr)
library(hydroGOF)
library(matrixStats)
# define directories
d0 <- getwd();
qMRI.data.dir <- paste(d0, "/../../raw_data/4layers_qMRI/", sep = "")
cell.data.dir <-... |
032ad1f5855adf7b1299967efa9c2be942a98fd4ea8e578e4e4e83108e68f765 | R | 17,496 | 484 | ---
title: "Methylation Analysis with methylkey"
author: "Vincent Cahais"
date: "`r Sys.Date()`"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Methylation Analysis with methylkey}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include=FALSE}
kni... |
6fa4d0c22eab171c33ad77c21a574e06d966555746989c2a202a8731457dfc82 | R | 17,503 | 572 | # Test olink_lod ----
test_that(
"olink_lod - works - Explore HT",
{
ht_fixed_lod_url <- "https://7074596.fs1.hubspotusercontent-na1.net/hubfs/7074596/000-documents/10-excel%20file/Explore%20HT_Fixed%20LOD.csv" # nolint: line_length_linter
# input is tibble ----
df_ht <- get_example_data("example_HT_... |
aee11cd7235fe53f31fc54612f111cce118f1916a7ebbcf3606832dad80b0a31 | R | 17,565 | 397 | # --- Internal Helper Functions ---
# Repeatability as error% (Standard Deviation of Residuals)
# Input: A fitted model object (e.g., from lmer)
# Output: Standard deviation of residuals
.fRep <- function(fit) {
return(stats::sd(stats::residuals(fit)))
}
# Group separation (t-statistic of the time:DX interaction)
#... |
5ebec262b70d90363f2e9333926bde2ad46927363fd00de6b7d5952526ff2a6e | R | 17,579 | 530 | ---
title: "Results of Classifier-Based MVPA"
author: "Kenji Fujisaki"
date: '`r format(Sys.time(), "%Y/%m/%d")`'
output:
html_document:
toc: true
toc_float: true
toc_depth: 4
number_section: true
code_folding: hide
---
**What does this script return?**
Descriptive statistics and test results fo... |
9166665c615efea8bec1e1b774ac9fc4ee342b0d6b715147832dd11a51db8083 | R | 17,581 | 525 | #!/usr/bin/env Rscript
# Load required libraries
suppressPackageStartupMessages({
library(Seurat)
})
# Get command line arguments
args <- commandArgs(trailingOnly = TRUE)
# Help function
show_help <- function() {
cat("Seurat Object Inspector\n")
cat("======================\n\n")
cat("DESCRIPTION:\n")
cat("... |
7f63f2802a53ee67219c9d242ad911d5c9bc07ec68f7eb11f0205bff7018cdd8 | R | 17,637 | 572 | ---
title: "Results of Similarity-Based MVPA"
author: "Kenji Fujisaki"
date: '`r format(Sys.time(), "%Y/%m/%d")`'
output:
html_document:
toc: true
toc_float: true
toc_depth: 4
number_section: true
code_folding: hide
---
**What does this script return?**
Descriptive statistics and test results fo... |
7e255943059689f1a209a2e07a2e42be68fc79ae1e78ce86ab42b1c814f99625 | R | 17,698 | 368 | ## Script for processing 7-, 22-wo and 82-wo ChP 4V and LV samples from our lab
## Subset to only Fibroblasts based on metadata processed objects
## Run until log normalization
## Save seuratobject
library('Seurat')
library('dplyr')
library('gridExtra')
library('scater')
source('/home/clintdn/VIB/DATA/Sophie/RNA-seq_... |
73736c55e348d0499c97aabda78762aa866296197ceab462ff9264151f6daa27 | R | 17,717 | 518 | # The working directory is the directory that contains this test R file, if this
# file is executed by test_dir
#
# testthat package is loaded, if this file is executed by test_dir
context("tests/test_annotate_long_format_table.R")
# import_function is defined in tests/helper_import_function.R and tested in
# annotator... |
165d26a884ab8f67f61b1e586c8aa66a50b004b5b496fc63d859cea38c9a76dc | R | 17,744 | 446 | library(Seurat)
library(ggplot2)
library(gghighlight)
library(ggbeeswarm)
library(ggpubr)
library(RColorBrewer)
library(tidyverse)
library(dplyr)
library(purrr)
library(ggplot2)
library(cowplot)
rootMain <- "figures/main/"
rootSupp <- "figures/supp/"
rootOthers <- "figures/others/"
querySeurat <- readRDS("saved/toZe... |
2d7c8f7c2845fb39db22165b7e9f05a272ba3edd3de8bd8134dee69389d14979 | R | 17,965 | 488 | ##################################################
### 03 --- examples pruning ----------------------
##################################################
# libraries
library(raster)
library(terra)
library(RColorBrewer)
library(sf)
library(dplyr)
library(DBI)
library(stars)
library(ggplot2)
library(exactextractr)
librar... |
d87dbd456cf4a9dc35aeec4a390ada79d5c80596778d92fe41b28f44835de74f | R | 17,975 | 678 | #' Plots for each bridgeable assays between two products.
#'
#' @author
#' Amrita Kar
#' Klev Diamanti
#'
#' Generates a combined plot per assay containing a violin and boxplot for IQR
#' ranges; correlation plot of NPX values; a median count bar plot and KS plots
#' from the 2 products.
#'
#' @param df A tibble co... |
12f44e4c34d305ab4cb34bc06d80ca8f281a0bd9bd98846e64afdd403ac02cd8 | R | 17,977 | 367 | ---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE,
fig.path = "doc/Figures/README-",
out.width = "100%")
# for tibbles...
options(pillar.neg=F, # do no print n... |
e347c90ee2c879f4d85166acacc70fb5ec746cd82f28d1d48b3b19730f4e677d | R | 17,991 | 549 | #############################
## iTReX maintenance tools ##
## Author: Yannick Berker ##
#############################
#' Save arguments in rds files named after arguments.
#'
#' @param ... Variables to be saved (not quoted).
debug_save <- function(...) {
debug_dir <- Sys.getenv("ITREX_DEBUG_DIR")
if (nchar(debug... |
88e2c9f7e10e0ed49f15ceb09442d2e3c43146372f85e29037752b950838038d | R | 18,104 | 476 | # --------------------
# title: FigureS9 Code
# author: Hu Zheng
# date: 2026-01-01
# --------------------
library(Seurat)
library(tidyverse)
library(ggpointdensity)
library(cowplot)
library(RColorBrewer)
library(scCustomize)
library(ggradar)
library(scRNAtoolVis)
library(viridis)
library(Biorplot)
source('bin/Palett... |
e1631e6e5286c10b779ded83d1b00761b7da8ae9d7779196985f4dcc03e3aecd | R | 18,127 | 423 | ################################################################################
### Wright et al., 2021
### Mouse Adult Distal Colon (MADC)
### scRNA-seq Reprocessing Via Seuratv5
### 50-day-old Wnt1-cre^(cre/wt) ; R26R-H2B-mCherry^(ch/wt) mice
###################################################################... |
cadff7bdc86ffb9306198c88a6011cfb85276af14d7c069319095fa6e04c438d | R | 18,150 | 494 | library(Seurat)
library(ggplot2)
library(purrr)
library(scrattch.vis)
library(scrattch.hicat)
library(Matrix)
library(dplyr)
library(tidyr)
library(parallel)
library(bigstatsr)
library(data.table)
library(arrow)
library(BiocNeighbors)
library(ggraph)
library(igraph)
library(tidyverse)
library(ggnewscale)
library(ggrepe... |
552d67974f31c28615b3c8fd541881d0a1f42c892024d4713c9b545478c80508 | R | 18,178 | 339 | # Author: Sangeeta Shukla and Alvin Farrel
# Function:
# 1. summarize Differential expression from RNASeq data
# 2. tabulate corresponding P-value
# This was compares 1 cancer group (Combined or Cohort specific) with one GTEx tissue type.
# The input arguments are the indices of the comparison of the cancer groups a... |
c647ea4baa30ef7a2b303cc7be3753629becd4ee063ac37d2649b5ad168a9969 | R | 18,249 | 284 | # Osprey GUI tutorial
This tutorial describes each step of the **Osprey** analysis workflow using the graphical user interface.
We will learn how to start the GUI, select the job file, load the raw data, process them into spectra, model the processed spectra, co-register the voxel to anatomical images, segment the an... |
c2e3420065c3c095a9dd1b183e45b3c9532460b9987c2ccc38a6a17e9e857556 | R | 18,253 | 544 | ---
title: "script04_analysis"
author: "Shamini Ayyadhury"
date: "`r Sys.Date()`"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## R Markdown
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more ... |
d4a99e7224606ca989ecabdf0d28bb9efca15ca9ff971e30fac05a4bd4cbce73 | R | 18,337 | 669 | # Test that a relevant error is thrown when a txt file was provided as parquet.
test_that(
"read_npx_parquet - error - random non-parquet file",
{
withr::with_tempfile(
new = "txtfile_p",
pattern = "txt-file_as_parquet-file",
fileext = ".txt",
code = {
# write some text in a txt... |
8c35c30fc9031d8a338c3d42f2fbc30e6bfb45e09225df95050b794bb8f9fd21 | R | 18,357 | 447 | #' Load default parameters
#'
#' \code{load_default_params} loads default parameters for the decision model
#' and creates a list
#'
#' @return
#' A list of all parameters used for the decision model
#'
#' @export
load_model_params <- function(
file.mort, # Path to background mortality data
file.surv, ... |
67a0b2e65dcda62611fe59e8814729f0db1586fff23870404cd7a23684b96d64 | R | 18,381 | 447 | # pROC: Tools Receiver operating characteristic (ROC curves) with
# (partial) area under the curve, confidence intervals and comparison.
# Copyright (C) 2010-2014 Xavier Robin, Alexandre Hainard, Natacha Turck,
# Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez
# and Markus Müller
#
# This program is free soft... |
34247955f3e0bf2f8fda43c116e50fb321c3bec031c3174f947825aeb2dbef55 | R | 18,473 | 601 | ---
title: "PedcBio CNV file preparation"
output: html_document
---
```{r load library}
library(tidyverse)
library(readr)
```
### Define directories
```{r define directories}
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
data_dir <- file.path(root_dir, "data")
analysis_dir <- file.path(root_dir, "analy... |
93a8946af6fe0e21f73490e935438c58bc541a3eeba69b5d1ec30ab85f16c4e5 | R | 18,575 | 473 | ---
output: html_document
author: "Mathis Nozais"
output:
html_document:
code_folding: hide
code_download: true
editor_options:
chunk_output_type: console
---
#################
Script for CRISPR bulkRNA analysis for "BEX" paper.
Made for Docker RNA 431
#################
```{r}
library(Rsubread)
library... |
80f08e5836b3b99dbc69c4bdd8b2064c1bcaaee5fc21f3ad79b401903e354fb8 | R | 18,670 | 255 | ################################################################################
# Phenotype Association Analysis for Co-occurring Rare Variants
# Analysis script for Figure 4
################################################################################
## Load helper functions
source("path/to/function_definition.R... |
c43edf211f81e4c4bb97acc6d765c0dbe2f4268d20d7fb16146a3756cd7c02f2 | R | 18,685 | 545 | library(Seurat)
library(ggplot2)
library(purrr)
library(scrattch.vis)
library(scrattch.hicat)
library(Matrix)
library(dplyr)
library(tidyr)
library(parallel)
library(bigstatsr)
library(data.table)
library(arrow)
library(BiocNeighbors)
library(ggraph)
library(igraph)
library(tidyverse)
library(ggnewscale)
library(ggrepe... |
ac6397890f816d5471625a31f8f6ad318608992407562a9fde76b85cfde4224a | R | 18,700 | 409 | ################################################################################
### May-Zhang et al., 2021
### Mouse Colon, Duodenum, and Ileum 6wks snRNA-seq Reprocessing Via Seurat
### 6Wks Phox2b H2B-CFP+ high intensity nuclei
### InDrop Runs
###################################################################... |
fee2b93b08f7f039255e6fcbdf03fd1fb879913293b69ef5eafcc2af352e91f3 | R | 18,778 | 556 | ---
title: "Molecularly Subtyping Embryonal Tumors - Final Table"
output:
html_notebook:
toc: TRUE
toc_float: TRUE
author: Stephanie J. Spielman and Jaclyn Taroni for ALSF CCDL
date: 2020
---
This notebook identifies samples to include in subset files for the purpose of molecularly subtyping embryonal tumor... |
53b33c2e33432f7820e4be5cebb5209a802afcf7b314ba724fdf2356e0d52b71 | R | 18,788 | 363 | # The script is intended viewed in R studio
# Blocks are titled
# "=" symbol was used as an assignment operator
# Setting options
getOption("scipen") # Default number notation is 0
options(scipen=999)
options(stringsAsFactors = FALSE)
options(show.error.messages = TRUE)
################### Package import ############... |
10fa7a02e57bd2a1b1bddc86bc6de031ce1b943b2eb5352476a7dfa742644072 | R | 18,791 | 501 | library(lme4)
library(lmerTest)
library(dplyr)
library(emmeans)
library(boot)
set.seed(123)
permute_sign_flipping_contrasts <- function(data,
formula,
compute_contrast_fn,
subject_col =... |
5e1b293a4b92fcd92627b10c6a2b708878e95b70439dbe8df4ec06001a837c95 | R | 18,819 | 291 | #!/usr/bin/env Rscript
#### For thalamus integration set
#### Loading libraries
library(dplyr)
library(Seurat)
library(patchwork)
library(ggplot2)
library(harmony)
input_dir = "/path/to/DecontX_scDblFinder/"
##################################################
######## First QC ################################
######... |
5ab9d3d7fde0f2793a4e08dd7a3d600b0dfe6a90dd42ae71033079f5a1138b95 | R | 18,848 | 437 | ############################
## iTReX module functions ##
## Author: Dina ElHarouni ##
############################
get_conc_unit <- function(input) {
switch(input$conc_select,
"other" = input$conc_text,
input$conc_select
)
}
MRA.mod <- function(input, drdata, output_dir, control_dir, PID,
... |
587cb2822d993463f4e6f89d543bb4e1d3aa7056bb805787476c014b6297ca77 | R | 18,858 | 364 | ---
title: "Object QC Functions"
date: 'Compiled: `r format(Sys.Date(), "%B %d, %Y")`'
output: rmarkdown::html_vignette
theme: united
df_print: kable
vignette: >
%\VignetteIndexEntry{Object QC Functions}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
***
<style>
p.caption {
font-size: 0.9em;
... |
062b437c748c71c815099d73ac8ac41fb5fdd46e702432efe2a147ae0aef8c17 | R | 18,859 | 361 | #' Subset PAF alignments at desired genomic range.
#'
#' This function takes loaded PAF alignments using \code{\link{readPaf}} function and then subsets
#' as well as cuts PAF alignments at desired target coordinates. This function can only be applied
#' to PAF alignments containing a single query and target sequence.
... |
c20c985325482303eeb4b503035024dc962fab5742e867f0bcbcdbf4d69208ca | R | 18,893 | 622 | if (!requireNamespace("here", quietly = TRUE)) install.packages("here")
source(here::here("stats","learning_models","_setup.R"))
scr_acq_ext <- scr_df %>%
filter(PHASE %in% c("acquisition", "retention", "extinction"),
TUS == "active") %>%
mutate(
PHASE = ifelse(PHASE == "acquisition", 1, ifelse(PHASE... |
8d6465e6c3cbb8ad05f4058f45b197de4918219c9a4b67e87a4f5903dc954736 | R | 18,910 | 438 | # Utility functions
#
# Author: Xuran Wang
# Copyright Xuran Wang (2018)
##########################################################################
#' Calculate relative abundance
#' @param X non-negative matrix for calculate relative abundance
#' @param by.col logical, default as TRUE
#' @export
relative.... |
f63d10e7317fc3cc7719abd979c59ff895da4c51a256dc92e13499446eae8eac | R | 18,965 | 418 | library(Seurat)
library(ggplot2)
library(patchwork)
library(dplyr)
library(tidyverse)
library(stringr)
library(cowplot)
library(optparse)
library(grDevices)
library(RColorBrewer)
# Define the command line options
option_list <- list(
make_option(c("-i", "--input_dir"), type = "character", default = "", help = "Input... |
8840f54e87c7115aa0c9095a47d8b3f8a2531297948d5fb0f5b403144147293d | R | 19,014 | 391 | ---
title: "Integrate molecular subtyping results"
output:
html_notebook:
toc: true
toc_float: true
author: Krutika Gaonkar, Eric Wafula, Jo Lynne Rokita
date: 2020, 2022
---
The purpose of this notebook is to integrate molecular subtyping results from
[molecular-subtyping-pathology](https://github.com/Ale... |
b68b84a1ed85e16e333f88c1db950a280d976497297b31690484da936f8d7bbd | R | 19,017 | 438 | library(pROC)
data(aSAH)
level.values <- list(
forward = c("Good", "Poor"),
reversed = c("Poor", "Good")
)
smooth.methods <- c("binormal", "density", "fitdistr", "logcondens", "logcondens.smooth")
for (marker in c("ndka", "wfns", "s100b")) {
for (levels.direction in names(level.values)) {
for (percent in c... |
181aa4cd3ed529842ced3ab484cee0e492d289f1dfdf2bf1c386dff34f620a85 | R | 19,029 | 387 | # Author: Ryan Corbett & Jo Lynne Rokita
# Function: Script to subtype MB SHH tumors
# Load packages
suppressPackageStartupMessages({
library(tidyverse)
library(data.table)
})
# Set directory paths
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
# Set file paths
data_dir <- file.path(root_dir, "dat... |
c0125dec7df80f887b07ef0efd9362a52ca5bafd6a4dedd223d62d729f542be3 | R | 19,123 | 483 | ## ----------------------------------------------------------------
## ORA helper functions (shared across enrichment functions)
## ----------------------------------------------------------------
#' Validate common enrichment inputs
#' @param x gene vector or data.frame
#' @param annot annotation data.frame (2+ colu... |
99b08c8d72cb8ec214c75402ab57f00bfac5d6ccf4f44fa2c76fff200036af2b | R | 19,182 | 490 | # Documentation
#' Lasy logistic regression function
#'
#' @description This function performs logistic regression and print results in tibble output.
#' This function aims to provide the results of the regression analysis in the format, which is frequently
#' desired in academic journals.
#'
#' @param data data frame ... |
dc0064bd24924485581e5004282f1ce8057c14107a5defa3843281d81939c343 | R | 19,184 | 553 | # JN Taroni and SJ Spielman for ALSF CCDL 2021-2022
#
# Makes publication ready OncoPrint panels, specifically for primary-only (PDFs)
#### Directories ---------------------------------------------------------------
# Detect the ".git" folder -- this will in the project root directory.
# Use this as the root director... |
7419defc01f6f15ae095950fa6d2daf2d7ef065cf77c27080f842b240119a9ce | R | 19,210 | 393 | # script to do some qMRI layer analysis
# load in some libraries
library(ggplot2)
library(tidyverse)
library(reshape2)
library(emmeans)
# define directories
d0 <- getwd();
qMRI.data.dir <- paste(d0, "/../../raw_data/4layers_qMRI/", sep = "")
dems.dir<- paste(d0, "/../../raw_data/participant_info/", sep = "")
results.... |
2be47bf996d2bc72c0427e7faaf6ceb5ea9639951e4620376ed99d445220e8b8 | R | 19,225 | 449 | #' @title Generate data files required for shiny app
#' @description Generate data files required for shiny app. Five files will be generated,
#' namely (i) the shinycell config \code{prefix_conf.rds}, (ii) the gene
#' mapping object config \code{prefix_gene.rds}, (iii) the single-cell gene
#' expression \code{prefi... |
ebcc73d77716486462ba37f617a10751d2806119a09c4cb402fd86181621b541 | R | 19,230 | 479 | library(Seurat)
library(destiny)
library(slingshot)
library(conflicted)
library(scran)
library(purrr)
library(SingleCellExperiment)
library(ggthemes)
library(ggrastr)
library(base64enc)
library(ggplot2)
library(readxl)
library(Biobase)
library(ggbeeswarm)
library(cowplot)
library(stringr)
obj <- readRDS("saved/toZe... |
9f1fc5c51fcc607b439986a2bea1b56055e709d53fca6a904b4d575801965801 | R | 19,232 | 524 | source("./source/OverallAnalysisFunction/Annotation/MSIdenti_DESI.R")
Dirdatabase <- "./source/Database"
#' @title Extract Spatial Matrix
#' @description Extracts the feature expression matrix and coordinates from a Seurat object.
#' @param data A Seurat object containing 'Spatial' assay and 'x'/'y' coordinates.
#... |
276cfa5c6f77a5388af664a1a536018e7609241535dc6a576dfb197cb681c600 | R | 19,250 | 420 | rm(list = ls())
# Packages ----
library(dplyr)
library(Boruta)
library(ranger)
# library(randomForest)
library(caret)
library(ggplot2)
theme_set(theme_light())
COL = c(black = "black"
,red = rgb(100, 38, 33, maxColorValue = 100)
,green = rgb(38, 77, 19, maxColorValue = 100)
,bl... |
a8066dce8d43e3a78fe05a1c5eb02b7201bad9a4e37bace7d9d7948bc37b8c58 | R | 19,275 | 503 | rm(list = ls())
# estimating shap values
# Packages ----
library(dplyr)
# library(Boruta)
# library(ranger)
# library(randomForest)
# tensorflow::install_tensorflow(version = "2.7")
# Load the tensorflow package
# Install the Python TensorFlow backend
# Note: This requires Python to be installed on your s... |
31d72b91f58ffea695b4dcfaf86f203c3fad3e49f8800618dea0577b149f1ec2 | R | 19,313 | 617 | #' @importFrom R6 R6Class
CVBooster <- R6::R6Class(
classname = "lgb.CVBooster",
cloneable = FALSE,
public = list(
best_iter = -1L,
best_score = NA,
record_evals = list(),
boosters = list(),
initialize = function(x) {
self$boosters <- x
return(invisible(NULL))
},
reset_para... |
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