sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e2dacf35bb26c64e4952b10140ed18c0c1d781351836f14cb04eee179e5a5b5e | R | 13,746 | 388 | ---
title: "MOFA+: simultaneous multi-view and multi-group integration using single-cell multi-modal data"
author:
name: "Ricard Argelaguet"
affiliation: "European Bioinformatics Institute, Cambridge, UK"
email: "ricard@ebi.ac.uk"
date: "`r Sys.Date()`"
output:
BiocStyle::html_document:
toc: true
vignette:... |
9efcc1d19e7f3c9fdf3f2828f1ff6e7a63d77b157896b90cb901681413542efe | R | 13,825 | 374 | ---
title: "MOFA+: integration of a heterogeneous time-course single-cell RNA-seq dataset."
author:
name: "Ricard Argelaguet"
affiliation: "European Bioinformatics Institute, Cambridge, UK"
email: "ricard@ebi.ac.uk"
date: "`r Sys.Date()`"
output:
BiocStyle::html_document:
toc: true
vignette: >
%\VignetteI... |
c4f404559af65d13f9dda95c41cbc71f88fd905bd33fa893783e79737b59a0ba | R | 13,841 | 499 | ---
title: "CN Status Heatmap"
output:
html_notebook:
toc: true
toc_float: true
author: Candace Savonen for ALSF - CCDL
date: 2020
params:
final_figure: FALSE
---
## Purpose:
Create a summary heatmap of copy number status from the consensus CNV call data.
This is done by binning the genome and calcul... |
8dc52d8560406069c53ac6dd2e1246238a0b9d4985ea66bf48c1dbbfe049b629 | R | 13,897 | 366 | ### DEG analysis and GSEA for each cell type ###
## This script performs differential expression analysis and Gene Set Enrichment Analysis (GSEA) for each cell type in the Seurat object.
## It compares GF vs CONV, 2wk vs GF, and 4wk vs GF conditions, saving results to CSV files.
## Overexpression-based pathway analys... |
c24bae5e0baabd86b7339982aa103899ef821a0302d9c59f4d0d32e269c92aff | R | 13,910 | 301 | ---
title: "RELACS marks on MSL1 peaks"
output: html_document
date: "2024-04-18"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
I want to overlap the MSL1-V5 peaks with some of the RELACS marks
#h3k4me3
```{r}
module load slurm
module load deeptools
SlurmEasy -l logs 'computeMatrix referen... |
fb4828f886946d567d95b668abf8d1edfea42f57314f279ef37d91c3111da090 | R | 13,922 | 247 | #############################################################################
#
# Temporal feature abnormality for Agitated MDD
#
# For this pipeline, we tested the temporal structure among agitated MDD, HC
# and retarded MD, focuing on slow-4 band (0.027 - 0.073 Hz)
#
# The alternative features include:
# ... |
5f7fe1cb6737bc2d2b1901451074af44468799b1391abc0900e16a508c532361 | R | 13,928 | 364 | rm(list = ls())
library(ggplot2)
library(dplyr)
library(patchwork)
# Define renamed method labels
rename_methods <- c(
"ustat_based_permutation_test" = "Global_U",
"distance_based_permutation_test" = "Global_F",
"pergene_u_test" = "Local_U",
"pergene_u_fisher_perm" = "Local_U",
"pca_score_test" = "PCA",
"... |
31afeba6ab01b016644538894efce0bc685e9de8a685dbb8a5efd93110a1ac80 | R | 13,934 | 387 | # Rversion>=4, need distances, dplyr, optparse,
# if diag=T, need ggplot2, gridExtra
###### load environment ###########
suppressPackageStartupMessages(library(distances))
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(optparse))
####### read arguments ##############
option_li... |
e4711a8dd455adb7f11e1385b526d4b16e052fed26f7490852b27a8decc347b7 | R | 13,946 | 338 |
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... |
4c86deb21e6740a54844dbf1b8dd1604bc4cde153f0a9146556be85c555c28d0 | R | 13,952 | 307 | ---
title: "Preliminary QC Report for Multi-Sample Analysis"
subtitle: "Initial Sample Preprocessing - scATAC-seq"
date: '`r Sys.Date()`'
output:
html_document:
toc: true
toc_float:
collapsed: false
number_sections: true
code-fold: true
toc_depth: 3
fig_he... |
0c91f10aa4f4e423df376714d897fc40c0576c844f289c8116eb0c6d7c659780 | R | 13,960 | 349 |
############################################
## 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... |
94ca9d9c2db0c3cdac6f31197535880483cd653a58c204fb6b445ac9b6fbacc8 | R | 13,974 | 383 | #' UpSet plot for visualizing set intersections with color support
#'
#' Creates an UpSet-style plot from named gene lists, built entirely with ggplot2.
#' Supports per-set coloring of bars, matrix dots, and connecting lines, without
#' requiring or modifying the UpSetR package.
#'
#' @param x A named list of character... |
023ca49d577312c2a9c85b1fb3c960e023274f0f937bc1334108306d69b6c800 | R | 14,032 | 332 | # Various useful functions
#' Number of CVR combinations given a number of regions to choose from
#' It considers A/B equivalent to B/A.
#' @param x number of regions to choose from
#' @noRd
.combos <- function(x) {
(3^x-3*2^x+3)/6
}
# `%||%` <- function(lhs, rhs) {
# if (!is.null(lhs)) {
# lhs
# } else ... |
85e66cc34fc4e06891495c8bb60cbaaad4ecb6e2fbf3cc2caa72ef99e68578c6 | R | 14,033 | 330 | ## run example:
## Rscript MAPS_regression_and_peak_caller.r /home/jurici/work/PLACseq/MAPS_pipe/results/mESC_test/ MY_115.5k 5000 1 None pospoisson NA
##
## arguments:
## INFDIR - dir with reg files
## SET - dataset name
## RESOLUTION - resolution (for example 5000 or 10000)
## chroms - number of chromosomes (19 for ... |
8241a31bd913ec2b3d287be5ed6a1c3dca2ba9140bad3e77f510cb6a98476740 | R | 14,034 | 276 | library(Seurat)
library(ggplot2)
library(gridExtra)
library(SingleR)
library(scRNAseq)
library(scater)
library(cluster)
library(optparse)
library(dplyr)
library(stringr)
option_list <- list(
make_option(c("-w", "--workdir"), type='character', action='store', default=NA,
help="Path to the working direct... |
9291efb0216588175ea96211e6a6181283b7a8fad089dbc50cea56149459531c | R | 14,057 | 405 | library(tidyverse) # dplyr, tibble, stringr, readr, etc.
library(Seurat) # CreateSeuratObject, NormalizeData, ScaleData, AddModuleScore, GetAssayData
library(ComplexHeatmap) # Heatmap
library(RColorBrewer) # brewer.pal
library(circlize) # colorRamp2 (from circlize, auto-loaded by ComplexH... |
5bc0771f092c165bd274aa62aded3b83aa7d5be4ef81976750a2e64d6653c30b | R | 14,059 | 413 | volcano_plot = function(results_df, title) {
library(ggrepel)
library(cowplot)
results_df_sub = results_df %>%
mutate(logP = -log10(padj))
results_df_sub$gene_name = rownames(results_df_sub)
x_lim = max(abs(results_df_sub$log2FoldChange))
lab_df = results_df_sub %>%
filter(DE!=0)
co... |
e3a40bf1f268eaf8a9ceb07d2d071c575d400792187522afb6b4c505023136e4 | R | 14,084 | 301 | ---
title: "Heatmaps_Degron"
author: "AF"
date: "`r Sys.Date()`"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
In this Script I am producing the deeptools Heatmaps for the MSLc members mapped onto the MSL1 peak I called in the NPCs.
These
```{r}
module load deeptool... |
a7d5a148d90b088c39935e93a07e851b4c8e14bee21cc7f25b1e11425b7e75b0 | R | 14,104 | 436 | ---
output:
github_document:
toc: true
toc_depth: 2
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "bench/fig-"
)
```
```{r, echo = FALSE}
library(ggplot2)
```
# Benchmarks
... |
1aa8b7ff76179f8a2e5dc4150147444bf02fb982b27ec48ab3a766975f931d58 | R | 14,126 | 210 | expected.placements <- list(
"ndka" = list(
"forward" = structure(list(theta = 0.611957994579946, X = c(
0.805555555555556,
0.625, 0.680555555555556, 0.763888888888889, 0.0416666666666667,
0.277777777777778, 0.513888888888889, 0.930555555555556, 0.972222222222222,
0.930555555555556, 0.9305... |
b07aa2c598afde57ef36c5c56cf6fca74f3e05a6ff49fb7f6fd9d71aaaf64dca | R | 14,154 | 287 | ## Creating Fibroblast origin subset object with only the Fibroblast clusters from the Fibroblast origin complete object
## Workflow: don't take along prolif FBs or PVM or vascular cells and only take cells from clusters 1,2,5,8,14,20
## Only took along cells from those clusters which mapped on the left side of the UMA... |
0f51bb245bd22399f7cae0459567dbe165b0106c3743b8e086fd1f7ae58bf27f | R | 14,165 | 399 | # J. Taroni for ALSF CCDL 2019
# This script processes MAF, CNV, fusion files and prepares them for oncoprint
# plotting.
#
# NOTES:
# * The `Tumor_Sample_Barcode` will now corresponds to the `sample_id` column
# in the histologies file
# * We remove ambiguous `sample_id` -- i.e., where there are more than two... |
4c3f8b87ee5752fab948fff6a89a1306857c9dc753bcfd8179aba11c9fe45976 | R | 14,174 | 320 | library(ggplot2)
library(ggrepel)
library(ggnewscale)
library(patchwork)
library(scales)
library(dplyr)
library(tidyr)
library(forcats)
library(stringr)
library(tibble)
library(readr)
library(purrr)
library(broom)
library(broom.mixed)
library(lme4)
library(ineq)
library(pheatmap)
library(RColorBrewer)
library(Matrix)
l... |
d3edaa46151a30070950e4417d14656f5cf373128f0c71004aa7497733ce573e | R | 14,187 | 373 | library(data.table)
setwd(choose.dir())
genotype_data<- fread(choose.files())
# Define personalised ggplot theme ----------------------------------------
theme_angie <- function(){
theme_bw() %+replace% #replace elements we want to change
theme(
#text elements
plot.ti... |
7307589dd56e0dc4988f644ec0d4980173e387077ff620a69b9bb1dc43f173c7 | R | 14,223 | 421 |
############ Testing package ############
dat <- escalc(measure="OR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
dat
dat.long <- to.long(measure="OR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, append=FALSE)
rma(yi, vi, data=dat)
rma.mv(yi, vi, random = ~ 1 | trial, data=dat)
levels(dat.long$group)... |
e38130b79c8dbd9fb375193b7434c2a3e6504e9f8ccba0abb5d3e37b0438e87b | R | 14,238 | 404 | # --------------------
# title: Figure7 Code
# author: Hu Zheng
# date: 2026-01-01
# --------------------
library(Seurat)
library(tidyverse)
library(caret)
library(Matrix)
library(xgboost)
library(PRROC)
library(scCustomize)
library(cowplot)
library(ggpointdensity)
library(Biorplot)
source('bin/Palettes.R')
source('b... |
ddf7d72ee0269ebb5e2dfeb0cf4bb83d35b36baea6ca550cf7af695c83a40e84 | R | 14,260 | 524 | test_that(
"olink_one_non_parametric - works - Friedman - match reference results",
{
# load reference results
ref_results <- get_example_data(filename = "reference_results.rds")
skip_if_not_installed("FSA")
skip_if_not_installed("broom")
skip_if_not_installed("rstatix")
# expected results... |
2c295c370203706077d6054a778f951f45c9fbb67a652b306578aa07d9a015a0 | R | 14,263 | 524 | ---
title: "MOFA+: analysis of matching scRNA-seq and scATAC-seq data"
author:
name: "Ricard Argelaguet"
affiliation: "European Bioinformatics Institute, Cambridge, UK"
email: "ricard@ebi.ac.uk"
date: "`r Sys.Date()`"
output:
BiocStyle::html_document:
toc: true
vignette: >
%\VignetteIndexEntry{MOFA2: Appl... |
6ca16e6ecfe4e1a2c4c616c932c71a96cf219da375c93119f6bec850d63b515d | R | 14,284 | 339 | ---
title: "Molecularly Subtyping Embryonal Tumors - Which samples to include?"
output:
html_notebook:
toc: TRUE
toc_float: TRUE
author: Stephanie J. Spielman and Jaclyn Taroni for ALSF CCDL
date: 2019
---
This notebook identifies samples to include in subset files for the purpose of molecularly subtyping e... |
de3c1c316e384683ed0dc17e0bc19a9872153ad25265d3a757b716e1494c3a5f | R | 14,297 | 377 | ##### scRNA #####
load("pheno_ROSMAP.Rdata")
set.seed(3)
# source("scripts/utils.R")
#Load packages
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
library(Seurat)
library(SeuratObject)
#### Load data ####
scRNA_OLIG = readRDS("./excitatory_neurons_set2.rds"... |
94d428c73f6045cd1cfc847a8f60be2d1e844c074028463746043d0370ecef73 | R | 14,315 | 383 | #' Plot KEGG Cluster Visualization
#'
#' This function merges two cluster-plot approaches:
#' \itemize{
#' \item \strong{Enrichment mode}: requires columns \code{Term}, \code{Padj}, \code{Significant}, \code{Annotated}, etc.
#' \item \strong{GSEA mode}: requires columns \code{pathway}, \code{padj}, \code{NES}, etc.... |
9269f0635fc4ce19e8a1f831cc50cb234db51b4908cbe0940193f453b6b8a9c3 | R | 14,335 | 316 | ################################################################################
### Morarach et al., 2021
### Mouse Small Intestine
### Reprocessing Via Seuratv5
### P21 Baf53b-Cre;R26R-Tomato mice
################################################################################
### Loading Packages:
librar... |
46ec436ceb2d56bc189f4e00340af63038252a04a0abfe5c50086cb2cc331567 | R | 14,369 | 296 | ---
title: "Cell Bender Functionality & Plotting"
date: 'Compiled: `r format(Sys.Date(), "%B %d, %Y")`'
output: rmarkdown::html_vignette
theme: united
df_print: kable
vignette: >
%\VignetteIndexEntry{Cell Bender Functionality & Plotting}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
***
<style... |
48f00d1842b28a42a2834ab55145307a7b83f8af56f298a9847526f7794f43e7 | R | 14,378 | 227 | # group-wise effects gfap on glu:
em_results_glu <- lmer_GFAP_glu_groupwise %>% emtrends(~ diagnose_group, var = "GFAP", data = NeuroMET %>% filter(!is.na(GFAP))) %>% confint()
em_results_p_glu <-lmer_GFAP_glu_groupwise %>% emtrends(~ diagnose_group, var = "GFAP", data = NeuroMET %>% filter(!is.na(GFAP))) %>% test()
co... |
681e403897981a79ab07b44fd38575d5c60a7aa41eab3c1fb0bbf6ced5f48bc4 | R | 14,393 | 414 | ---
title: "Purdue Pegboard training analysis"
author: "Marcos Moreno Verdú"
date: "2024-04-05"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Load packages and data
Packages
```{r include = FALSE}
library(tidyverse)
library(modelsummary)
library(ggdist)
library(readxl... |
bd39a480b2903ff65444305cae55f12c9f98c3caf0ca75b7a207e389fffd5810 | R | 14,417 | 445 | library(miloR)
library(SingleCellExperiment)
library(scater)
library(scran)
library(dplyr)
library(scuttle)
library(ggrepel)
library(Seurat)
library(ggplot2)
library(gghighlight)
library(ggbeeswarm)
library(ggpubr)
library(RColorBrewer)
library(knitr)
##################
#### 2D vs 3D ####
##################
otherFig... |
85b406d6dd6522d86fec7cb453dfb2d198c44e507d4ce6b1258c1734a637a891 | R | 14,422 | 393 | suppressMessages(library(ggplot2))
suppressMessages(library(dplyr))
suppressMessages(library(showtext))
suppressMessages(library(Seurat))
suppressMessages(library(RColorBrewer))
suppressMessages(library(ggtext))
suppressMessages(library(igraph))
suppressMessages(library(ggraph))
# font_add("sans", regular = "arial.ttf"... |
be2593b68cb433ca9f56b9579077067c674a1d029a35a3647c5f41c7efdca32a | R | 14,456 | 384 | # Analyses f) and g): to see whether a change in PAD is associated with atrophy (f) and cognitive decline (g)
# Load required libraries
library(mvtnorm)
library(data.table)
library(LMMstar)
library(mets)
library(riskRegression)
library(dplyr)
library(boot)
library(writexl)
library(mmrm)
### Functions
select_outcome_v... |
be6714e3c55430a8354d624958043eeed33545b79580893431a338b1151b3c7e | R | 14,533 | 447 | #====================================================
#==========Exploratory and Univariate Analaysis =====
#====================================================
# Dynamic directory based on the location of the research folder
library(rstudioapi)
setwd(dirname(rstudioapi::getSourceEditorContext()$path))
getwd()
... |
7ad9ba5b360038b8cd791703583081d33c6c936a4862defce0ff49364a8781c5 | R | 14,559 | 396 | # --------------------
# title: Figure3 Code
# author: Hu Zheng
# date: 2026-01-01
# --------------------
library(Seurat)
library(tidyverse)
library(ggsci)
library(aplot)
library(ggpointdensity)
library(scRNAtoolVis)
library(scCustomize)
library(viridis)
library(RColorBrewer)
library(cowplot)
library(ggradar)
library... |
6227f85a6321434db491f954ec54302d08d7d02bbd19f0026671f25bc2507228 | R | 14,564 | 430 | ### analysis nuclear intensities single channel with different thresholds
# with t-tests vs first group, and, if more images than replicates, lmerTest analysis
# go to main directory (parent directory of scripts)
if (basename(getwd())== "00_scripts"){setwd("../.")}
#load packages
library("tidyverse"... |
a64ac12c499a0861f711307beb107ee4187bea76ee7e283493be88b090255f58 | R | 14,670 | 273 | ---
title: "Mapping mFISH data to reference data set"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Mapping mFISH data to RNA-seq reference}
%\VignetteEngine{knitr::rmarkdown}
\usepackage[utf8]{inputenc}
---
This code reads in all of the data for an example mouse SST mFISH experiment and c... |
870b8dad9749fb4b9e0fc5103f74f2c2d25c13cb104acb71aedcb97b0183f160 | R | 14,716 | 420 | # LASSO implementation fatiga cognitiva
rm(list = ls())
library(rjags) # rjags library allows R to interface with JAGS
library(coda) # coda package provides tools for summarizing and visualizing MCMC output
library(ggmcmc) # ggmcmc is used for diagnostics of MCMC chains and plots
libra... |
d0b278f0026a3b9fa3bbd09a06e564f6ec3d8ae77f6f60337e6ba056dfe6fd1e | R | 14,726 | 360 | # Read filtered fusion calls to convert into json format for OpenTarget portal
# attached gene and disease annotation and gatheres frequency at FusionName or
# Gene_Symbol level
suppressPackageStartupMessages(library(optparse))
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(r... |
2f3a758ac989a8813ed0017c6ee0ffe4730d62185cdc68681b17d769a07435ae | R | 14,744 | 393 | suppressMessages(library(ggplot2))
suppressMessages(library(dplyr))
suppressMessages(library(showtext))
suppressMessages(library(Seurat))
suppressMessages(library(RColorBrewer))
suppressMessages(library(ggtext))
suppressMessages(library(igraph))
suppressMessages(library(ggraph))
# font_add("sans", regular = "ar... |
3afa04fed4a524a8265d29452d7ea43dfac34fee9aaad1b52dd8077ca3ba6e24 | R | 14,751 | 457 | ---
title: "Target_Met_analaysis"
author: "MM"
date: "`r Sys.Date()`"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(psych)
library(FactoMineR)
library(factoextra)
library(dplyr)
library(ggplot2)
library(ggrepel)
library(gridExtra)
library(r... |
6500e0ff0f801468b8805d2faba877ca80e1caed2989ff1c7ac9416978e08f50 | R | 14,849 | 328 | ## Script for processing 7- and 22-wo ChP 4V and LV samples from our lab
## Run until log normalization
## Save seuratobject
## Rebuttal update: only include FBs and vascular cells this time, so no subset required later! Better for clustering too
## Remove CPE and immune cells based on metadata of the objects!!
libra... |
b309d98d767d83db8512e36c3e117453eba2d3f9a9725de99fea9fb0c2e5198d | R | 14,861 | 423 | # Note: All libraries are loaded from R/_libraries.R
# All R files in the R/ folder are automatically sourced by Shiny
# Specify the application host and port
# This ensures the app runs on all network interfaces and listens on port 8180.
options(shiny.host = "0.0.0.0")
options(shiny.port = 8180)
# Add resource paths... |
3367ed16980b7c69e4a3ad52b5ecc58f2dba346737f47f51df3240b0b9b988a8 | R | 14,866 | 462 | # 导入必要的库
library(dplyr)
library(pheatmap)# 加载 Nebulosa 包
library(Nebulosa)
library(Seurat)
library(readr)
library(data.table)
# 读取计数矩阵
rawcount <- fread("./GSE183093/GSE183093_POAcountmatrix.tsv", header = TRUE, stringsAsFactors = FALSE, fill = TRUE)
metadata <- fread("./GSE183093/GSE183093_POA_Cell_metadata.t... |
7738e0612e87c06f20870a7b6510674af34d109fb38e98015f8128d33d7d2245 | R | 14,909 | 399 | library(dplyr)
library(data.table)
library(scales)
library(heatmaply)
library(MatrixGenerics)
library(reshape2)
library(ggsankey)
library(gplots)
###################################################################
#
# Read rds files from potential synapses computed with an HPC
#
####################################... |
17df9fff9de68d49d81808aac55a70c95ac98ac9cf29499a6aa791e7ced9f848 | R | 14,948 | 448 | #Meta-analysis of Adult-SVZ P30 scRNA-seq data
#Code written by Budhaditya Basu
#Data was collected from:
#https://data.humancellatlas.org/explore/projects/e8808cc8-4ca0-4096-80f2-bba73600cba6
#GEO: GSE67833
#Publication DOI: 10.1016/j.stem.2015.07.002
library(Seurat)
library(SeuratDisk)
library(tidyverse)
... |
b83ee4f4868311af488db6982c67428f44a48ce0b96c51adb3caa2f16ffd2d7d | R | 14,995 | 357 | #---------------------------------------------------------------------------------------------
# R (version 4.2.1) code for drawing PNV maps in the following paper:
# 'Predicting dominant terrestrial biomes at a global scale:
# Assessments of machine learning algorithms, climate variables indexing, and extreme clim... |
d0926971e902fdf9745f23eff537f68fa4f699b456285e4dd954ba11f87581fb | R | 14,995 | 408 | ---
title: "Compile LGAT subtyping"
output: html_notebook
---
In this notebook, we will be compiling the subtype annotation for LGAT samples. Subtypes are described in [#790](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/790) which were gathered through the following scripts :
`01-subset-files-for-LGAT.R... |
29f0c4a8f233272f9565a11b54459dac7cc20a874632234dfe97def27a17891f | R | 14,996 | 350 | suppressPackageStartupMessages({
library(optparse)
library(dplyr)
library(GenomicRanges)
library(AnnotationDbi)
library(org.Hs.eg.db)
library(rtracklayer)
library(tidyverse)
})
# This script converts a seg file into a tsv file with CN information and gene
# annotation.
#
# Code adapted from the PPTC PDX ... |
16806574acf9a92531e7f0f53e3c2c87bdc452b3c07fba79938eec1c4856e983 | R | 15,008 | 408 | ############################################################
## Main Figure 1
############################################################
## Load helper functions
source("path/to/function_definition.R")
## Packages
library(tidyverse)
library(data.table)
library(ggpubr)
library(cowplot)
library(ggrepel)
library(broo... |
e2b92c5109a1cc58e8141090ef74828ef30f078bf2e0e4efb113021728777d6d | R | 15,016 | 405 | # rm(list=ls(all=TRUE))
library(data.table);library(dplyr);library(susieR,lib='/home/lorincn/Rpkgs')
###############
pop='EUR'
gene='SYK'
# gwasfp='/home/lorincn/beegfs/lorincn/data/phenotype/T2D/1kgSNPs_Suzuki_EUR_Metal_LDSC-CORR_Neff.v2.txt.gz'
gwasfp='/home/lorincn/beegfs/lorincn/data/phenotype/AD/AD_Bellenguez_2022... |
9251d0479231f00a9adcb30963f514b1c107d85f54329c09e14657ad89cb0a17 | R | 15,026 | 353 | # 5. Synapse -------------------------------------------------------------------
## 5.1 Load packages and functions ---------------------------------------------
source("./codes/my_packages.R")
source("./codes/my_functions.R")
# Load classification lists:
# genes classification:
neuro = scan(file = "./data/proteinat... |
bc7751bdcb60367f20d5048c781551fee85fbda3419226197cfc6a5e872815ea | R | 15,028 | 504 | if (!requireNamespace("here", quietly = TRUE)) install.packages("here")
source(here::here("stats","learning_models","_setup.R"))
scr_ext <- scr_df %>%
filter(PHASE %in% c("retention", "extinction") & TUS == "active") %>%
mutate(
US = ifelse(US == "reinforced", 1, ifelse(US == "unreinforced", 0, NA)),
CUE =... |
a74fbb374fd26044264a23464fb5c552a710ebe4f483ad13c2544647539ca55f | R | 15,029 | 438 | ## ----------------------------------------------------------------
## show methods
## ----------------------------------------------------------------
#' Show methods for richR S4 classes
#'
#' Display a concise summary when an object is printed at the console.
#'
#' @param object An S4 object of class richResult, G... |
5a2fd472364aedfe36d296071ea5c3b91ed9efdd0f591178878e1cf87aba5aab | R | 15,034 | 632 | # hdWGCNA analysis
library(Seurat)
library(tidyverse)
library(cowplot)
library(patchwork)
library(WGCNA)
library(hdWGCNA)
theme_set(theme_cowplot())
set.seed(12345)
enableWGCNAThreads(nThreads = 8)
##load obj
seurat_obj <- readRDS('GSE282955_ARH_Sex_by_Nutr.rds')
#setup
seurat_obj <- SetupForWGCNA(
seurat_obj,
... |
6c05b955fff7f785ff94e4827fb8b2ce75aa6201e4ab0e93104faad2c38a474c | R | 15,045 | 375 | ### Example Bulk RNA-seq DEG Analysis ###
#This is an example script for performing normalization, filtering, differential expression analysis, and gene set enrichment analysis on bulk RNA-seq data.
#In this example, germ-free (GF) mice were compared to E. coli (EC) mono-colonized mice, however, similar steps were use... |
1735306d1d49d156a4f7f1700c82e40c85099c7e1cd4b0d1b07ca4e4f0b7d7cb | R | 15,063 | 334 | #!/usr/bin/env Rscript
# combinefile <- commandArgs(trailingOnly = TRUE)
# # print(c("combinefile: ", combinefile))
# print(combinefile)
###### EANMDflagcount.R v1.45
##### Written by Kaining Hu 2024-09-20 Add AS.SUPPA
library(getopt)
library(dplyr)
library(stringr)
spec <- matrix(
c("Output", "o", 1, "character"... |
6b63874c9e410886d72e6a8920893227b83fa74b5f49565b68a790ec4e4b8552 | R | 15,111 | 343 | ---
title: "Cancer group distribution of putative onocgene annotated fusions "
author: "K S Gaonkar for D3B ; Jaclyn Taroni for CCDL, Jo Lynne Rokita (D3b)"
output: html_notebook
params:
histology:
label: "Clinical file"
value: data/histologies.tsv
input: file
dataPutativeFusion:
label: "Input puta... |
51c1651bfcbfc00da07b996872e93e77b263e7fbb9965a889f4acff7fda16aa5 | R | 15,117 | 329 | library(readxl)
library(tidyverse)
library(kableExtra)
library(lme4)
library(lmerTest)
library(emmeans)
library(patchwork)
library(knitr)
library(ggeffects)
library(splines)
library(cowplot)
library(broom)
library(glue)
library(pbkrtest)
library(MetBrewer)
diagnose_colors <- c("#376795","#72bcd5","#ffd06f","#ef8a47")
... |
29f68517710cd6163f995c13b6104d5034e6afe78565356698cfdd11dc171e7a | R | 15,184 | 424 | #INFORMATION-----------------------------
#LOAD LIBRARIES ------------------------
library(data.table)
library(dplyr)
library(DT)
library(ff)
library(fgsea)
library(GEOquery)
library(ggheatmap)
library(ggplot2)
library(ggpubr)
library(ggrepel)
library(gplots)
library(gridExtra)
library(limma)
library(Matrix)
library(m... |
199c6a15b90eb2417d696588d06c9063aa2dd3105d89add98d12438c431c6b71 | R | 15,221 | 518 | ---
title: "MotiMus Demographic Data"
Me: Ségolène M. R. Guérin
output:
html_notebook:
code_folding: hide
toc: yes
pdf_document:
toc: yes
html_document:
toc: yes
word_document:
toc: yes
editor_options:
markdown:
wrap: sentence
---
# Preamble
```{r}
# ------ CLEANING R SESSION ####
rm... |
8624711697103b18eb1e889e667af2221f1ebcf70a581e5148d50e4e1fbdef91 | R | 15,274 | 427 | library(mediation)
library(data.table)
library(tidyverse)
library(readxl)
library(tidyr)
library(ggplot2)
library(forcats)
library(dplyr)
library(openxlsx)
#load data
load("~/Data/ksads/covariat_all_18.Rdata")
load("~/Data//diag_all_name.Rdata")
load("~/Medication/hold_w24.Rdata")
load("~/Data/proteomics/proteomics_dat... |
87e56c4fb7c25a8cbebcc46c2265fbe9ce5e262fac34ba82d39ad0f0d735bee7 | R | 15,277 | 283 |
library(Seurat)
library(monocle3)
library(RColorBrewer)
library(ggthemes)
library(ggrastr)
library(base64enc)
library(ggplot2)
library(readxl)
library(Biobase)
library(ggbeeswarm)
library(cowplot)
library(stringr)
library(ggridges)
library(tidyverse)
rootMain <- "figures/main/"
rootSupp <- "figures/supp/"
rootDir <... |
2eaccf9548e66bac90d61cf44347826289c5687b6ce3a6ddfa36866dc3f8598a | R | 15,315 | 368 | ---
title: "Survival analysis by TP53 and telomerase activity"
authors: Run Jin (D3B), Jo Lynne Rokita (D3B), and Stephanie Spielman (CCDL)
output:
html_notebook:
toc: true
editor_options:
chunk_output_type: inline
---
Note that for models that consider the `cancer_group` predictor or are performed separatel... |
0d0c7f679aaad22a2eb984d1cdb5f5431ce7a00fd2ddeebca3aefe6af6c18f68 | R | 15,317 | 474 | # Analysis c) to investigate whether an increased PAD at baseline is associated with future conversion from CN/MCI to MCI/AD.
# Load required libraries
library(mvtnorm)
library(data.table)
library(LMMstar)
library(mets)
library(riskRegression)
library(dplyr)
library(lava)
### Functions
calc_var_lp <- function(vec_valu... |
2348c1f58eb4549b71c28a7d576b0ddf81c71a263e36ada2c05f19561666c220 | R | 15,354 | 403 | ###############################################################################
# Title: Early deviations from normative brain morphology and cortical microstructure in schizophrenia spectrum disorders
# Author: Claudio Aleman Morillo . Universidad de Sevilla
# Date: 2025
#
# Purpose
# This script runs three re... |
8261208ac6c649858146a72834731738da0736f38ecfefac5c9fa9403a4a14ba | R | 15,401 | 328 | #' DimPlot LIGER Version
#'
#' Standard and modified version of LIGER's plotByDatasetAndCluster
#'
#' @param liger_object \code{liger} liger_object. Need to perform clustering before calling this function
#' @param group.by Variable to be plotted. If `NULL` will plot clusters from `liger@clusters` slot.
#' If `combin... |
8d20815cbc19f51415db46a1546951cbe99c14b3e03030df4f4325dbdea53358 | R | 15,419 | 478 | # Analysis c) to investigate whether an increased PAD at baseline is associated with future conversion from CN/MCI to MCI/AD.
# Load required libraries
library(mvtnorm)
library(data.table)
library(LMMstar)
library(mets)
library(riskRegression)
library(dplyr)
library(lava)
### Functions
calc_var_lp <- function(vec_valu... |
3b5f0c18e052f3d366995f7991759f3ab680d2efa3591cca1403aa5119e079b2 | R | 15,420 | 514 | test_that(
"olink_boxplot - works",
{
skip_on_cran()
skip_if_not_installed("ggplot2", minimum_version = "3.4.0")
npx_data_format221010 <- get_example_data(
filename = "npx_data_format-Oct-2022.rds"
)
npx_check <- check_npx(df = npx_data_format221010) |>
suppressWarnings() |>
s... |
548709af99976283a722422b1162c6855cc6c289f3113d51326e4158f11cea6b | R | 15,427 | 324 | # 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... |
530ba42e74fb591308d02d27b14255989fe27f31038251cd03deed0716dab4bb | R | 15,440 | 271 | #' Iteratively Refine Biomarker by Single-Region Ablation to Minimize SSE
#'
#' Takes an initial biomarker definition (numerator and denominator regions) and
#' iteratively removes the single region whose removal most decreases the
#' aggregated Sample Size Estimate (SSE) across specified datasets and groups.
#' The pr... |
b4dd55b74ba7f5bdab62ddb0ed57d3490c5ed5d177ccb7de2a7c7390553ddd13 | R | 15,460 | 365 | ---
title: "Preliminary QC Report for Sample `r params$sample`"
subtitle: "Initial Sample Preprocessing"
date: '`r Sys.Date()`'
output:
rmdformats::robobook:
lightbox: true
number_sections: true
gallery: true
code-fold: true
toc_depth: 3
params:
seuratdir: seurat
sample: ... |
319f9559e6e3fb1c25b229c5b47eb046103a5c5187dc97b091a2165e592c8efa | R | 15,477 | 356 | # various helper functions for converting psychopy data to SPM-able events ----
## get path to events file from subject/run/task ----
# run should be in run-%02d bids format
get_raw_events <- function (subject, task, run) {
file <- list.files(here::here("ignore", "data", "beh", subject, "raw"),
... |
87654dfe1241ddb74dfcb8a956821332b9cf1da0e661def566c1da8d1508cbed | R | 15,516 | 230 | ########################################################################################################
## ANOVA / DiffEx -- 3 core user functions:
##
## parANOVA.dex -- create ANOVAout dataframe of tests for differential expression/abundance
## plotVolc -- create PDF and HTML Volcano Plots, output v... |
5f2e90352475f4365ec6956396f6ef63785a7c2c66c8d9a505d1ebf221ce897d | R | 15,573 | 456 | library(shiny)
library(shinyjs)
library(shinycssloaders)
library(MARVEL)
library(tidyverse)
library(ggtext)
library(gh)
library(viridisLite)
library(fontawesome)
# The following MARVEL files had to be Monkey Patched in order to fix a bug
# and to use less memory.
source("MARVEL/Script_DROPLET_07_ADHOC_PLOT_PCA_2_PlotV... |
53903c96b9a33355416f8d78c9b8086f2219e72808821ce0e4a4fef7d7969f44 | R | 15,620 | 353 | #!/usr/bin/env RScript
library("DESeq2")
library("dplyr")
library("tibble")
library("ggplot2")
library("ggrepel")
library("ggiraph")
library("ComplexHeatmap")
library("pvclust")
library("circlize")
library("RColorBrewer")
library(optparse)
library("R.utils")
# Getting options from command line
option_list = list(
m... |
78642d13d48d27ac2b1719db7641f0acac65950ecb1ba50d18abab5be49b303b | R | 15,621 | 316 | # ==============================================================================
# U1_Tutorial.R
# UI definition for the "Tutorial" tab.
#
# Purpose:
# Displays the landing page of the application, including:
# - Overview of the SMIntegration platform features.
# - Detailed descriptions of core analytical... |
55751da9186bd34e5fa68d2e9197fa1e0f1db55149ef9673ef48ba4fa0080f09 | R | 15,678 | 416 | ########
12*42*3*5
downsampled_DE_celltype3 <- tibble(cell_type3 = 0, comparison = 'a', condition = 'a', downsampled = 0, randomseed = 0, DE = 0, .rows = 7560)
rownum = 0
for(cl in as.list(unique(ARH_Sex_by_Nutr@meta.data$cell_type3))){
for(i in c(50, 100, 200)){
for(j in c(43445,746774,411735,275672,957057))... |
8708d52a5ed3f353903b2adfb03bcd1dfbc87369e47c9f5a1f21db6e34361099 | R | 15,718 | 308 | #' Visualize PAF alignments.
#'
#' This function takes PAF output file from minimap2 alignments, and visualize the alignments
#' in a miropeat style.
#'
#' @param highlight.sv Visualize alignment embedded structural variation either as an outlined ('outline') or filled ('fill') miropeats.
#' @param color.by Color align... |
2a78c79b1eb2b54e3513bb01669a182a4c9873912a44409a8914c8b18b1218e1 | R | 15,726 | 414 | library(data.table)
setwd(choose.dir())
genotype_data<- fread(choose.files())
# Define personalised ggplot theme ----------------------------------------
theme_angie <- function(){
theme_bw() %+replace% #replace elements we want to change
theme(
#text elements
plot.ti... |
783606c8940058e87aa23ce6fb86af0815b368657d80332d23c50236f33506a2 | R | 15,767 | 278 | # K. S. Gaonkar 2019
# Filters standardized fusion calls to remove artifacts and false positives.
# Events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal
# tissue require stringent filtering, making it difficult for researchers and clinicians to discern true ... |
e0443b525fe68ed80348cb1e119517fc948a8357bac514d930303241bc6e2069 | R | 15,781 | 440 | 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)
,blue = rgb(28, 24... |
a40f3f8a0e75aa12c7f59f2513b0f932c45978e5b75919fb6b7a783e5a558e06 | R | 15,783 | 403 | library(data.table)
setwd(choose.dir())
genotype_data<- fread(choose.files())
# Define personalised ggplot theme ----------------------------------------
theme_angie <- function(){
theme_bw() %+replace% #replace elements we want to change
theme(
#text elements
plot.ti... |
689cd612c4b808c7e96af3c2d365f753cd368b155fb136e7ac2d0c91eaee5493 | R | 15,818 | 335 | ################################################################################
# Script to perform generalized linear modeling (glm) and generalized linear
# mixed modeling (glmer) on MIND networks and psychiatric symptoms
################################################################################
# Cop... |
65a60da684759c507b6ac003f7ace4ec06818fdf2e2c52fe88a9579b0c9b8b39 | R | 15,819 | 369 | ---
title: "MOFA+: integration of heterogeneous single-cell DNA methylation data sets"
author:
name: "Ricard Argelaguet"
affiliation: "European Bioinformatics Institute, Cambridge, UK"
email: "ricard@ebi.ac.uk"
date: "`r Sys.Date()`"
output:
BiocStyle::html_document:
toc: true
vignette: >
%\VignetteIndexE... |
5374bac87817db810dd05f4557883fbc070cbe5ce934a3e16ad66a83886be3d6 | R | 15,829 | 459 | # --------------------
# title: FigureS1 Code
# author: Hu Zheng
# date: 2026-01-01
# --------------------
library(Seurat)
library(scCustomize)
library(tidyverse)
library(cowplot)
library(ggtree)
library(aplot)
library(pheatmap)
library(ggpointdensity)
library(sciRcolor)
source('bin/Palettes.R')
all.Adult <- readRDS(... |
34b8753d2a1b6e4b39560243c5f835f4ce90176e21f17b0045b806a046814940 | R | 15,843 | 288 | ---
title: "mediation_imputation"
output: html_document
date: "2023-11-24"
author: A. Klimesch
note: This script performs a multiple imputation on the "preimp_prepped_for_imputation.csv" dataset (n=2042) which was prepared in "01_preprocessing_preimp.Rmd". Then, the sum scores of the questionnaires, ordinal questionnai... |
4a6e3350b4808a8748f16cf38113194e0c7b406574e11abd92544ee0faed10d5 | R | 15,856 | 447 | ---
title: "Correlations of Neural Dissimilarity with Relationship Duration"
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?**
Test result... |
28e89bc519a26d6fae893246cf9dce9df821be5d11ad92e7397c5b9a4555eda7 | R | 15,931 | 329 | ---
title: "Biodiscvr Workflow with User Data"
date: "`r Sys.Date()`"
toc-title: "Overview"
output:
rmarkdown::html_vignette:
toc: true
number_sections: true
vignette: >
%\VignetteIndexEntry{Biodiscvr Workflow with User Data}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup... |
115cf46009ae5c7f00efcf6f788182d707331d747e61f3a48d1ff02eb3cb54e2 | R | 15,968 | 332 | library(cowplot)
library(data.table)
library(dplyr)
library(ggplot2)
library(ggpubr)
library(grid)
library(gridExtra)
library(gratia)
library(knitr)
library(mgcv)
library(RColorBrewer)
library(scales)
library(stringr)
library(rjson)
library(tidyr)
########################
# Supplementary Figs
########################... |
c4953f0887f4fbd6391694e22bd8a79072e3d288c66921f9a840e3eb1710cfa4 | R | 16,004 | 552 | ##-------------------------------------##
## DEA TAB ##
##-------------------------------------##
get_dea_allMethods <- function(ID, mat, group1, group2, methods, token){
library(spatstat.core)
library(Seurat)
library(matrixStats)
ram <- memuse::Sys.meminfo()
while (ram$f... |
363d62099ab72c9e052ddb15ba766067f0f2bb20f23b031a6c2ce46730eca9fa | R | 16,050 | 235 | library(data.table)
library(parallel)
library(Matrix)
library(ggplot2)
library(rlist)
######Functions######
Barcode_Collapse_Function<-function(x){
VBCs<-as.character(working.cell.split[[x]]$barcode)
return(VBCs)
}
Barcode_Calling_Function<-function(x){
working.set<-working.cell.split[[x]]
bar... |
6d7f0bd3d2ec8a01476105dc00462eb6b9528640dfe40b03960e65b2c4ab8fd9 | R | 16,105 | 378 | ### Sub-clustering and analysis of just the immune cell cluster ####
## This script performs sub-clustering and analysis on immune cells subsetted from my seurat object to identify different immune populations and their responses to treatment.
# Code created by Lisa Blackmer-Raynolds
#Load required packages----
libra... |
fc892a72a2691e4298aa7468fdd0666246d6ce628df15d9228079a197669539a | R | 16,108 | 510 | #' Function to make a UMAP plot from the data
#'
#' @description
#' Computes a manifold approximation and projection using umap::umap and plots
#' the two specified components. Unique sample names are required and imputation
#' by the median is done for assays with missingness <10\% for multi-plate
#' projects and <5\%... |
e382b6a961e4fe6a6ee830a4bd809f202037c2d7202c8b8d32490c33d40c2d93 | R | 16,112 | 495 | #' Format the output of olink_normalization for seamless use with downstream
#' analysis functions.
#'
#' @author
#' Danai G. Topouza
#' Klev Diamanti
#'
#' @description
#' For within-product bridging and subset normalization:
#' * Adds non-overlapping assays between projects to the bridged file without
#' adjustme... |
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