sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
89be70bc048de035b7ba81a8d8405e4905b00735da83bb09b47e297bfcbe56cc | R | 17,159 | 440 | ---
title: "Diet and the Gut Microbiome in Patients with Parkinson's Disease"
author: "Dayoon Kwon"
date: "2023-12-22"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(dplyr)
library(vegan)
library(phyloseq)
library(Maaslin2)
library(microbiome)
library(dada2)
library(Bi... |
45a686ddb23e80da3a8757956108dbb0dfc720d3ac191bca5a2e15cc40046893 | R | 17,241 | 471 | # random seed -------------------------------------------------------------
set.seed(123)
# load library ------------------------------------------------------------
library(Seurat)
library(tidyverse)
library(harmony)
library(SCORPIUS)
# save image --------------------------------------------------------------
save.i... |
39e4979eb50e8bb681e3292769f7ad86724a9d0f519d7bdef7547812e30cd127 | R | 17,299 | 475 | conda_args <- reticulate:::conda_args
#' Install StellarPath required python packages in conda or virtualenv environment
#'
#' Credits for this function go to spacyr R package: https://github.com/quanteda/spacyr/tree/master/R
#' Respect for these fellow R developers who developed a way to automatically create and dete... |
8cac180d52e2732cdf82eae58bbc89819919aebd7fa034978edaf3b73b6e5da9 | R | 17,527 | 416 |
###### Replication Study (2018) - Elena Andres and Chuan-Peng Hu ##########
# ------------------- Load libraries and preparing ----------------------------
rm(list = ls()) # remove all variables
### load library
library(tidyverse, ez)
windowsFonts(Times=windowsFont("TT Times New Roman"))
apatheme = ... |
a04797c59c5cecd98e67b2346138d37bb45db8afc3a3083fb06f7f395674be0b | R | 17,615 | 385 | #!/usr/bin/env Rscript
# Linear and non-linear modelling of hemispheric average values
# This code corresponds to the hemispheric differences and age sensitivity sections (with a focus on hemispheric averages)
# 30.10.2023, Max Korbmacher (max.korbmacher@gmail.com)
#
#
# PREP ####
# load packages
if (!require("pacman")... |
467d5a1c3d3b6a6aff9d4345469eefcb6533ac09b7078ab18040f60fe9842575 | R | 17,786 | 281 | #if you have access to the ABCD data, please setwd() here to whichever file location the tables are stored in csv format
library(psych)
library(dplyr)
library(purrr)
library(tidyr)
library(stringr)
library(tableone)
library(MatchIt)
library(car)
library(ggplot2)
library(ggstatsplot)
library(jtools)
library(sensemakr)... |
b2a2930be6fae70b3e5c057dba8449710a01030ad3ebc733664b8cc71c1ffef2 | R | 17,862 | 440 | #################################################################################################################
#################################################################################################################
######
###### Title: pqtl_ms_make_fig2_figS2
######
###### Des... |
2400c48ebab5091dd01f2ada5e34e35676d210b89035516baaa375089597aa01 | R | 17,897 | 444 | ---
title: "Vignette_1: Data Introduction with a mouse study: OGD_WT vs NORMOXIA_WT"
output:
html_document:
theme: united
toc: yes
vignette: "%\\VignetteIndexEntry{Vignette} \n%\\VignetteEngine{knitr::rmarkdown} \n%\\VignetteEncoding{UTF-8}\n"
editor_options:
markdown:
wrap: 72
---
```{=h... |
dc4268eb73de144f0cb727c450980934fc14a6050ae48342ab2d772093bf2e54 | R | 18,050 | 588 | #!/usr/bin/env Rscript
library(pheatmap)
library(data.table)
library(ComplexUpset)
library(tidyverse)
library(vcfR)
library(argparse)
parser <-
ArgumentParser("Parameters for donor matching based on Pearson coorelation. ")
parser$add_argument("--result_csv", help = "The path to the csv file or the directory containi... |
bd24efa14d4f8982093034e8030d66fc9c5a597835a15225d85d0f3f34c3850c | R | 18,054 | 684 |
suppressPackageStartupMessages({
library(Seurat)
library(Matrix)
library(stringr)
library(sctransform)
library(future)
require(scales)
library(RColorBrewer)
library("readxl")
library(dplyr)
library(dendextend)
library(patchwork)
library(ggplot2)
library(Orthology.eg.db)
library(org.Mm.eg.db... |
d7f321fddb43a96e9881eba35248fcfbcca07b622b97403abd683e1f7bf152e9 | R | 18,084 | 488 | ## ---------------------------
##
## This script was created with R version 4.2.1 (2022-06-23)
##
##
## Title: Personalized identification and characterization of genome-wide gene expression differences
## between patient-matched intracranial and extracranial melanoma metastasis pairs
##
## Purpose of script: H... |
1b71158eec19d464b79e9100b2bef57edd3b2b9bf06a7b459fcd98883a6fb485 | R | 18,088 | 451 | ---
title: "ScPCA Benchmarking: Run Time and Memory Comparison"
output: html_notebook
---
This notebook compares the run time and memory footprint of pre-processing 4 scRNA-seq samples across 4 different tools. We used cellranger v6, kallisto, alevin, and alevin-fry.
Alevin-fry was used with and without `--sketch` mo... |
ada766bfc093bbff8f82e170458aa511cec3a8a43872a80cfa42aaa78bc553c1 | R | 18,208 | 299 | library(Seurat)
library(ggplot2)
setwd("/Projects/deng/Aging/DANeuron/Kamath_GSE178265")
GSE178265.data <- Read10X(data.dir = "rawData/")
MetaData=read.table("rawData/METADATA_PD.tsv",header=T,row.names=1) #https://singlecell.broadinstitute.org/single_cell/study/SCP1768/single-cell-genomic-profiling-of-human-do... |
17fc9887b95090f7f2efa8c07655e881771c849c1939c27989dbbba28e1ff428 | R | 18,336 | 468 | ---
title: "SCRNAseq quantification comparisons: Data Import"
author: "Joshua Shapiro for CCDL"
output:
html_notebook:
toc: true
toc_float: true
---
This notebook contains code to import and do preliminary processing single cell expression data, quantified by Alevin, Alevin-fry, Kallisto, and Cellranger.
A... |
5f234b232d814e4de5ea9c0e7170ada5cc2160051c7aed22206a053cee2441b6 | R | 18,389 | 416 | #############################################################################################
# These codes have been costumly designed for brain network analysis of 1-2 time point data
# generally acquired by immunolabelling of activity-dependent proteins (i.e. c-fos, Arc)
#
# Many functions here have been largely bas... |
ee169fd8a6f13a3d50f2be5163e1fe1882f5ff69610d4c7d36e96385cfd6e6c2 | R | 18,391 | 316 | library(Seurat)
library(ggplot2)
library(ggpubr)
setwd("/Projects/deng/Aging/Ex/AllEx/cellNumberVariation")
ExAll.integrated=readRDS("/Projects/deng/Aging/Ex/AllEx/ExAll.integratedTSNE.rds")
ExAll.integrated=subset(ExAll.integrated,idents=c(0:15))
C3C5=subset(ExAll.integrated,idents=c(3,5))
C3C5Number4EachSamp... |
94b807123c3cfa3ddbefba025a66509eef3f306a7435487f47e14b3d8a415870 | R | 18,420 | 501 | # Following
# https://bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html
# https://github.com/hbctraining/DGE_workshop_salmon_online
# https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html
#
# Import salmon quant.sf files using tximeta
librar... |
3367937ed5ebd8db23b750a7b73861a667817fe7682b80482c5dd879326b34f8 | R | 18,435 | 434 | # exploring hemispheric age predictions
## PREP ####
# packages
#install.packages("afex")
#install.packages("tidyquant")
library(tidyquant)
library(afex)
library(effects)
library(dplyr)
library(reshape)
library(ggplot2)
library(tidyr)
library(viridis)
library(lme4)
library(MuMIn)
library(effectsize)
library(ggpubr)... |
9d88d65573b23785e6211e0d00b6d65204f1616e8333881ab168a0503f894e2a | R | 18,497 | 229 | # Statistical graphics authored in R/ggplot2 at a fixed 180 mm journal width.
# No smoothing, inferred clinical grades, local health fits or invented intervals.
options(encoding='UTF-8',warn=1)
suppressPackageStartupMessages({library(ggplot2);library(patchwork);library(grid)})
args <- commandArgs(trailingOnly=TRUE)
roo... |
7d406abf0d690dda288cd95d3d8e65912c6c49ae43524f243b2ed1b9b9b4937b | R | 18,597 | 440 | ---
title: "HBN Sample Selection"
author: "Audrey Luo"
output: html_document
---
# Sample Selection process
1) original sample: N=2255, ages 5-22, 6915 scans total
2) exclude participants with medical conditions affecting brain function, gross neurological abnormalities: no medical exclusion in HBN
3) include passing ... |
914db0467e69e0a14a1b9b41b47523414a2b1fad1adacc087e07cb6c8a3a3d74 | R | 18,887 | 496 | ---
title: "220627_more_methods_comparsions"
author: "Jennifer Fisher"
date: "6/27/2022"
output:
html_document:
toc: true
theme: united
---
# START
Goal/Purpose of operations:
Conduct comparison analysis on enriched Go biological process go terms for each cancer/method. Also create plots to summari... |
b4563ba0d70b7b1191b8c2f18c62269962b14e2b975d6ef6380ea4bdbc451c22 | R | 19,020 | 491 | .libPaths("/home/u23/haozhang1/miniconda2/envs/seurat/lib/R/library")
# from https://github.com/satijalab/seurat/issues/5257
# the error in MapQuery() is caused by an update in uwot
# need to install the previous version of uwot and restart the RStudio session to solve this error.
# devtools::install_version("uwot", v... |
eb8a72c62347fca86e319b2e659ca045ddebdcf39adcf8aede6240e7bd366a6f | R | 19,031 | 345 | ---
title: "COVID Microglia scRNA Clinical Data Cleaning"
output: html_notebook
---
# Setup
## Import packages
```{r}
library(tidyverse)
library(readxl)
library(ggplot2)
library(ggsci)
library(ggsignif)
library(patchwork)
library(Cairo)
library(gridExtra)
library(grid)
library(gtable)
library(qwraps2)
```
... |
0585f757b891fe910bf2c5e06fe7585a1fcdd6dca381e715b026b0ed12b4fd60 | R | 19,074 | 494 | .libPaths("/home/u23/haozhang1/miniconda2/envs/seurat/lib/R/library")
# from https://github.com/satijalab/seurat/issues/5257
# the error in MapQuery() is caused by an update in uwot
# need to install the previous version of uwot and restart the RStudio session to solve this error.
# devtools::install_version("uwot", v... |
4a77edf2d08e00322e0c858030e03aae8d86d9f4f6e2a1b435b22f86ec228784 | R | 19,342 | 354 | library(readr)
library(dplyr)
library(ggplot2)
library(stringr)
library(grid)
devtools::load_all("breaktools/")
source("00-utils.R")
detect_rdc = function()
{
debug=F
dir.create("reports/03-detect_rdc", recursive=T, showWarnings=F)
#
# Load offtargets
#
offtargets_df = readr::read_tsv("data/offtargets_d... |
a6256371a1b525d93f092656ad4120a1b04d6621614b7ca46d25af7b1fcb5c08 | R | 19,354 | 392 |
library(dplyr)
library(magrittr)
library(rjson)
source("/cbica/projects/network_replication/manuscript/code/scripts/main_analyses/GAM_functions.R")
##################
# Set Variables
##################
args <- commandArgs(trailingOnly=TRUE)
config_file <- args[1]
##################
# Set Directories
#########... |
f0621218f630c49d5b1b9b17f2d742a15050511f6a91deb859566cc0fbe1cca8 | R | 19,450 | 615 |
library("stringr")
if (T) {
source(sprintf ("%s/matrix_presets.R", str_split(rstudioapi::getSourceEditorContext()$path, "get_red_mats.R")[[1]][1]))
}
len <- length
euc_dist <- function(a, b) sqrt(sum((a - b)^2))
get_binned_index <- function(i, window_size) {
rst <- floor((i)/window_size) + ifelse(... |
7cb45b4c9773f02549c8dd307c129e0fad95efcb7c1315611c4e4bacacfd778c | R | 19,563 | 463 | ---
title: "Comparison of EmptyDrops to CRLikeEmptyDrops"
author: "Ally Hawkins for CCDL"
output:
html_document:
toc: yes
df_print: paged
html_notebook:
toc: yes
toc_float: yes
---
In this notebook, we are exploring different methods of filtering the output of Alevin-fry when using the `--unfiltere... |
19750789ed46cf66a206d526c6019c83bebc4c0b20ceda40dd2cbed8cfbcb94d | R | 19,576 | 529 | ---
title: "Analysis of Genes detected between Tools"
author: "Ally Hawkins for CCDL"
output:
html_notebook:
toc: true
toc_float: true
---
This is a quick comparison of the genes that are detected when using cellranger or when using alevin-fry.
Here, we have alevin-fry that has been run in two different re... |
d30cf6d5466516f0413abae68a5fe53007b2e3c0e1139c18868cedfcfaf73675 | R | 19,638 | 423 | #######
# setup functions
lsi_workflow = function(bmat, dims, metadata=NULL, log_scale_tf=TRUE, reduction='pca.l2', resolution=0.3) {
tfidf_mat = tfidf(bmat, log_scale_tf=log_scale_tf)
pca_mat = do_pca(tfidf_mat, dims=max(dims))
seurat_obj = run_dim_reduction(bmat, pca_mat, dims, metadata) %>%
Seurat::Find... |
a7fdb9be30d4367d737c5c64cd477a9be7d2cf84eb0fbfc5c704b94a6de8d35e | R | 19,684 | 560 | #' Desc
#'
#' @param object Rootogram Object
#' @param ... and more
#'
#' @return test
#' @export
rootogram <- function(object, ...) {
UseMethod("rootogram")
}
rootogram.default <- function(object, fitted, breaks = NULL,
style = c("hanging", "standing", "suspended"),
... |
a9df4c61dd9c362ae8c107e817c5751a01f0174b54684d995a0aa5f8a987a1e5 | R | 19,702 | 374 | #' Chromosome analysis of passed VCF file
#'
#' This function takes in the loaded VCF (read_vcf()) and operates calculations for the chromosome analysis
#'
#' @param VCF_DATA loaded VCF file (read_vcf() output)
#' @param METHOD how to count (and plot) variants for each chromosome ("RAW"=raw number, "LEN"=n/chr-length(r... |
90a98ca812bff56b275f04ef0f973d3309fce153102d79cb5be091ff4b87ce86 | R | 19,840 | 424 | library(data.table)
library(dplyr)
library(tibble)
library(igraph)
library(tidyverse)
library(philentropy)
library(dendextend)
library(parallel)
library(Seurat)
library(ggplot2)
library(reshape2)
library(viridis)
library(rgl)
library(data.table)
library(waldo)
library(scCustomize)
library(prismatic)
library(RColorBrewe... |
42171e2d9b5897a7d57c4d6f249a37dd9e76c0ee888f5fcf4f6e894a0f8feda6 | R | 19,861 | 508 | #############################################################################################
# These codes have been costumly designed for brain network analysis of 1-2 time point data
# generally acquired by immunolabelling of activity-dependent proteins (i.e. c-fos, Arc)
#
# Many functions here have been largely bas... |
8f7f8e00dcdd3386bde48e93b7840c6c701b669f9c0787846a5079b1901055da | R | 19,898 | 574 | ---
title: "sporo3perc_analysis"
author: "T Attenborough"
date: "21/03/2022"
output: html_document
---
Load packages
```{r}
library(Seurat) #Seurat v4.0.2
library(dplyr)
library(patchwork)
library(here)
library(ggplot2)
library(clustree)
library(ggrepel)
library(leiden)
#sessionInfo()
```
Import the lit marker docume... |
aa5231161e1267b16b85147204d31feba88e83ca69cef14958c10870b640f808 | R | 20,072 | 457 | # exploring hemispheric age predictions
## PREP ####
# packages
#install.packages("afex")
#install.packages("tidyquant")
library(tidyquant)
library(afex)
library(effects)
library(dplyr)
library(reshape)
library(ggplot2)
library(tidyr)
library(viridis)
library(lme4)
library(MuMIn)
library(effectsize)
library(ggpubr)... |
e2bd4304ffa2707d2368682780d8e505e4404c42405414ad6d383aa6a3f8897e | R | 20,246 | 448 | #!/usr/bin/env Rscript
################################################################################
# filterMassChroQ.R 1.1.0 #
# Authors: Victor Laigle (Institut Curie) #
# Contact: myproms@curie.fr ... |
d9945d401e2e1e675473272de8c77637ce252f3e469a45a200ea4029241408a7 | R | 20,343 | 427 | ###Tested with R version 3.5.
library(metacell)
library(plyr)
library(reshape2)
library(dplyr)
library(zoo)
library('RColorBrewer')
library(scales)
library(pheatmap)
library(ggplot2)
scr_load_cell_type_table=function(input_table,mc_object){
cell_type_table=read.table(input_table,h=TRUE,sep="\t",comment.char="",s... |
f11763d41dcaced37c0b53bf4523f9ef33ae520bf27c5383bc9921ff7495eebf | R | 20,359 | 335 | ---
title: "Vignette_5: StellarPath vs GSEA (traditional enrichment tool)"
output:
html_document:
theme: united
toc: yes
vignette: "%\\VignetteIndexEntry{Vignette} \n%\\VignetteEngine{knitr::rmarkdown} \n%\\VignetteEncoding{UTF-8}\n"
editor_options:
markdown:
wrap: 72
---
```{=html}
<sty... |
d8288e425ac178c017c18f9d5ab8fc7784244d3230b353a372f35760e9c007c5 | R | 20,410 | 680 | library(future)
library(future.apply)
library(princurve)
library(tidyverse)
library(data.table)
library(parallel)
library(MASS)
library(lme4)
library(lmtest)
library(future)
library(pscl)
library(vcd)
library(ComplexHeatmap)
library(ggpubr)
library(gridExtra)
library(ggrepel)
library(viridis)
library(parameters)
count_... |
c23b92fa6661453e586e08e9bd8122b1585a36ba2b6bc2626fff4330f1da69a2 | R | 20,419 | 392 | library(readr)
library(dplyr)
library(ggplot2)
library(stringr)
library(grid)
library(xlsx)
devtools::load_all("breaktools/")
source("00-utils.R")
remove_this = function()
{
biosamples_ids = readr::read_tsv("reports/00-upload_ncbi/biosamples_ids.tsv") %>%
dplyr::mutate(sample_id=gsub("(.*_(rep|replicate)_?\\d+)... |
3aa36332733bed14e5f28ecd5015af9449ffa75f4e77e13192f043fce6a3c2be | R | 20,449 | 371 | #DLX and MEIS peaks in mouse
## data from Lindtner et al., 2019
library(tidyverse) #v1.3.1
library(plyranges) #v1.8.0
library(liftOver) #v1.12.0
library(readxl) #v1.4.0
colnames <- c("seqnames", "start", "end", "name", "score" ,"strand" ,"fold_change" ,"-log10pvalue" ,"-log10qvalue" ,"rel_summit_pos" )
## read... |
86539f71dca987a392f713b1a60ecee5ac8829175b5cbf19cf28ff282e0a79aa | R | 20,512 | 363 | library(readr)
library(dplyr)
library(ggplot2)
library(stringr)
library(ggpattern)
devtools::load_all('breaktools/')
source("00-utils.R")
APH_concentration = function()
{
dir.create("reports/05-APH_concentration", recursive=T, showWarnings=F)
debug = F
group_palette = c("APH 0.2 uM 96h"="#C49A6C", "APH 0.3 uM 9... |
bec3fc3fb3f38eb263b8e71c28a079cd0b8f1ea1bc4793d0a187fad2876f75f8 | R | 20,529 | 567 | #' Human gene-gene interaction network
#'
#' @format list
#' \describe{
#' \item{NETWORK}{gene-gene interaction network in adjacent and edge list format}
#' }
#' @source{
#' \url{https://www.ebi.ac.uk/intact/home}
#' }
"dbs_hsa_net_l"
#' Mouse gene-gene interaction network
#'
#' @format list
#' \describe{
#' \it... |
5f4a0201e99a13bdd20806aa55a63e7339def8d2ff40dc3136f4eef660aa2e7e | R | 20,568 | 371 | #overlap of DLX5, MEIS and LHX6 peaks in mouse GE
## published data data from Lindtner et al., 2019 & Sandberg et al., 2016
library(tidyverse) #v1.3.1
library(plyranges) #v1.8.0
library(liftOver) #v1.12.0
library(readxl) #v1.4.0
colnames <- c("seqnames", "start", "end", "name", "score" ,"strand" ,"fold_change" ... |
61028ed9e516b292eafeb1ca2f9aa42b8a8f419222cf60a0c71d755647eddfab | R | 20,816 | 725 | ---
title: "AD3 ATACseq - Figures for paper"
output:
html_document:
df_print: paged
---
```{r global_options, include=FALSE}
knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE)
```
```{r, libraries}
library(tidyverse)
library(Signac)
library(Seurat)
library(JASPAR2020)
library(GenomeInfoDb)
libr... |
0fb200a536c4b829aff13a3de5c4e266df2dbce11012c2eb7abf76e5ecd13e5a | R | 20,851 | 527 | # J. Taroni 2018
# For import only: source(file.path("util", "plier_util.R"))
PLIERNewData <- function(exprs.mat, seed = 12345) {
# A wrapper function for applying PLIER to a data set. We use the following
# genesets that come with PLIER: bloodCellMarkersIRISDMAP, svmMarkers,
# and canonicalPathways. We set the... |
315e21a0428bae74b0895be4fe357cdc431a26ab7ffa27a864f029f373c7cc18 | R | 20,903 | 632 | #' Calculate Mann Whitney U from a vector of ranks
#'
#' Maximum sum of ranks, rank_sum_max: len_sig * max_Rank
#' Minimum sum of ranks, rank_sum_min: len_sig * (len_sig + 1)/2
#' Maximum U statistic, Umax: Maximum sum of ranks - Minimum sum of ranks
#' Minimum U statistic, Umin: 0
#' Normalized U statistic (0 to 1), ... |
66c30e54a0788a6aaeb240aecab30960d3186b93aa43cbd512984eab941ba864 | R | 21,060 | 607 | #################################################################################################################
#################################################################################################################
######
###### Title: pqtl_ms_make_fig1_figS1
######
###### Des... |
6bc3c4f2c4f033fb10d01f14012bfdc2afaa4981d40c46dc1c1ee8418d32a5c5 | R | 21,069 | 417 | ################################################################################
# quantiSwath.R 2.0.14 #
# Authors: Matthieu Lhotellier & Alexandre Sta (Institut Curie) #
# Contact: myproms@curie.fr ... |
3c671f1fb016f4e409e543d14006337a7a84ff1dcc4f7225bd242d12e6ad921a | R | 21,232 | 420 | ---
title: "060923_V2_Integrated scSeq Analysis Bap1"
author: "Sabine Schneider"
date: "June 09, 2023"
output: html_document
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(eval = FALSE)
```
Load WT and KO datasets needed for this integrated analysis and load relevant libraries
I will combine the already norm... |
6818e862648c9b39cbbf48b291ac7d2cac8bb73111c7b6b7bf6c99cb2aec53e8 | R | 21,548 | 681 | ---
title: "Shape Illusion Stats"
author: "Iona McLean"
date: "2023-12-6"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
#Load in packages
library(stats)
library(tidyverse)
library(ggpubr)
library(rstatix)
library(reshape2)#used for Cochran Q
library(psych)#used for Cochran Q... |
1221d3765294632ff7089bbd8e2b43895f4563a5fd12529862e8e32081be6e19 | R | 21,807 | 615 | library(sp)
library(rgdal)
library(lubridate)
library(ctmm)
library(sp)
#Load interpolated tracks (loaded in chunks becaue they were run in parallel in chunks)
load("~/onetofour.RData")
load("~/fivetoeight.RData")
load("~/ninetotwelve.RData")
load("~/thirteentosexteen.RData")
load("~/seventeentoeighteen.RData... |
71fb0f03bc713aa9c76557b91249f88619f1408362c9b4d154d3c8edab3cb537 | R | 22,379 | 582 | ############################################################################
# This script contains the code necessary for importing and preprocessing behavioural and ephys data
#Reported in the manuscript "Freezing responses during prolonged threat memory retrieval reflect trait-like anxiety endophenotypes in female ... |
8baed5462e7c39ecee310a032ee1b2a33d1910e1e553c576171f414a7196023f | R | 22,518 | 434 | # Rscript build_meco_sentitems.R /fs/project/schuler.77/meco/joint_fix_trimmed.rda ee
# Language codes (wave 1): "du" "ee" "en" "fi" "ge" "gr" "he" "it" "ko" "no" "ru" "sp" "tr"
# Language codes (wave 2): "ba" "bp" "da" "en_uk" "ge_po" "ge_zu" "hi_iiith" "hi_iitk" "ic" "no" "ru_mo" "se" "sp_ch" "tr"
args <- commandArgs... |
a9c5bb6e93c37b80d567c819ccfe36e6388e6e066352908211a5d913c772be9c | R | 22,753 | 90 | setwd('/work/AnneSophiaHartebrodt#6698/ms-project/')
require(rhdf5filters)
require(rhdf5)
require(Rhdf5lib)
renv::activate('/work/AnneSophiaHartebrodt#6698/ms-project/r-single-cell')
renv::repair()
set.seed(11)
require(harmony)
require(tidyverse)
require(data.table)
library(cowplot)
library(rsvd)
library(Rtsne)
librar... |
88734450d1309f2de866493cae775438b98a04d380056c70296a54c25bf3d7ed | R | 22,938 | 469 | setwd('/home/eteleeb/projects')
library(ggplot2)
library(ggpubr)
library(ggsci)
dir.create('omics_integration/iCluster_output/cell_specific_pathways')
folder_names <- list.dirs('/home/delaguilaj/DE_soma/', full.names = F, recursive = F)
## function to remove shared genes
comps <- c('C1', 'C2', 'C3', 'C4')
remove_sh... |
4ee191efad8a6a1df8d95db6173cff85bd82ea1b449993bae3020d8649632d50 | R | 23,080 | 398 | # Hemispheric brain age plot: beta coefficients by p-values EXTENSION: ABSOLUTE ASYMMETRIES
# Max Korbmacher, 05.09.2023, R version 4.1.2 (2021-11-01), updated 09.11.2023
####### PREP ####
# load library
# load packages
if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, stringr, ggpubr, ggrepel, ... |
a50295dcc1faaa8ddbe1058dfa29b995430f29ca58d85b6add2859407dfb264f | R | 23,101 | 504 | library(Seurat)
library(SeuratDisk)
library(SeuratData)
ExAll.integrated=readRDS("/Projects/deng/Aging/Ex/AllEx/ExAll.integratedTSNE.rds")
ExAll.integrated=subset(ExAll.integrated,idents=c(0:15))
ExAll.integrated$SourceStatus=paste0(ExAll.integrated$Source,"_",ExAll.integrated$Statues,sep="")
table(ExAll.inte... |
af94bafff36c4eece70bca93969444fa3da2472c37369c692572c5af228b6a70 | R | 23,170 | 385 | # Paper : Detecting subtle transcriptomic perturbations induced by lncRNAs Knock-Down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network
# Code : R script to produce the figures of the manuscript
# Author : Marin Truchi
#-----------------------------------------------------------... |
d1c4610be65169a29c14f71c68de8f16583ba9f2e9a7c601e3922dc1dab4fac1 | R | 23,256 | 534 |
#####################################
#### HiPlexUp AUTOMATED ANALYSIS ####
#####################################
# Images have been cropped to grey matter only (butterfly shape)
# Segmentation has been performed with Zen software (NT based, 80% confidence, 50 um^2 minimum size, watershedding xxx)
# Quantifica... |
4c18988cee17f15b8320409ece98a1c308257d0a538d3ffccadfd04c28edfe70 | R | 23,403 | 390 | library(Seurat)
library(ggplot2)
library(DoubletFinder)
library(dplyr)
library(clustree)
#######################################################################################
############## Preprocessing snRNA from Lau et al, ###########
##############################################... |
3f0bbe58329dc489935668d833f76425c6111302c34e57a829dad727b29ba923 | R | 23,636 | 458 | ---
title: "BirdSoloLTRs"
output: html_notebook
author: "chenguangji"
date: "11/03/2024"
editor_options:
chunk_output_type: console
---
```{r Figure 1A}
# Figure 1A
rm(list = ls())
require("writexl")
require("readxl")
library("dplyr",quietly=T)
library("ggplot2",quietly = T)
library("ggtree",quietly = T)
library("... |
1b5830c6e0aaceb32ce0b3c9dfe36ce7630cb7043ddb5b63997d6f02b27f3866 | R | 23,957 | 723 | ---
title: "220523_pca_analysis_other_cancers"
author: "Jennifer Fisher"
date: "5/23/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
PCA analysis of the the new new cancers (lung, pancr... |
dbf88e7ac8934533f24f50118f6b6fae736415f8d9b6795f7d42d5e1374abed0 | R | 24,121 | 689 | library(sp)
library(rgdal)
library(lubridate)
library(ctmm)
library(sp)
load("~/onetofour.RData")
load("~/fivetoeight.RData")
load("~/ninetotwelve.RData")
load("~/thirteentosexteen.RData")
load("~/seventeentoeighteen.RData")
load("~/nonteentotwentytwo.RData")
load("~/twentythree.RData")
load("~/twentyfour... |
e575267e3e19344bae0a414c1245c9022999ee1a02dd68b626c76d1ca8c2a7df | R | 24,122 | 689 | library(sp)
library(rgdal)
library(lubridate)
library(ctmm)
library(sp)
load("~/onetofour.RData")
load("~/fivetoeight.RData")
load("~/ninetotwelve.RData")
load("~/thirteentosexteen.RData")
load("~/seventeentoeighteen.RData")
load("~/nonteentotwentytwo.RData")
load("~/twentythree.RData")
load("~/twentyfour... |
c7d41cfbede5563381de064220d4603512b3698dd2f165b6fff2d9d1811a01d3 | R | 24,141 | 656 | # Plot results of regression models. Plot each model in a single panel figure (instad of all in one figure)
#
# Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M.,
# Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor
# rhythms are uniquely li... |
713886ff8f10dfcdac2ae930b221ea5be49c9137899d366fa57516bb7be3fe77 | R | 24,383 | 729 | ---
title: "220118_GBM_SignatureSearch"
author: "Jennifer Fisher"
date: "1/18/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Conduct Signature Reversion on GBM samples with both the DE... |
15ebaa4899f743c395844049589dccf0a074fcf223a3499389d36d234d358491 | R | 24,454 | 385 | setwd("/home/eteleeb/projects")
library(ggplot2)
library(gridExtra)
library(reshape2)
library(data.table)
library(gplots)
library(ggsignif)
library(RColorBrewer)
library(VennDiagram)
###########################################################################
## extract shared metaboloties between Knight ADRC and ROSMA... |
d7e1660735af7c3c8f75046bbd9d12059f9552502630edc4ee0036a6725d35aa | R | 25,057 | 445 | # Rscript preprocess_meco.R /fs/project/schuler.77/meco/joint_fix_trimmed.rda /fs/project/schuler.77/meco/joint_l1_acc_breakdown.rda en
# Language codes (wave 1): "du" "ee" "en" "fi" "ge" "gr" "he" "it" "ko" "no" "ru" "sp" "tr"
# Language codes (wave 2): "ba" "bp" "da" "en_uk" "ge_po" "ge_zu" "hi_iiith" "hi_iitk" "ic" ... |
f884004212e79e609873886b2e0ffae68823afe75589c240169b7234a7e84dc8 | R | 25,760 | 630 | library(igraph)
library(mvtnorm)
library(truncnorm)
library(TruncatedNormal)
library(Matrix)
GCut.z = function(z, graph){
GCut = list()
for(label in c(0, 1)) {
where = which(z == label)
G = igraph::graph.adjacency(graph[where, where], mode = "undirected")
G = igraph::set.vertex.attribute(G, "node", val... |
b4e52a9a7fbd1d3932fa380ea0c1114555afd525b3de9e3e800e5cf9e70d16d6 | R | 25,790 | 636 | #!/usr/bin/env Rscript
################################################################################
# hydrophobicity.R 1.0.0 #
# Authors: Victor Laigle (Institut Curie) #
# Contact: myproms@curie.fr ... |
888c3dbd245dfbda49dd2fad744517a10829a04c64ce9f72197f97c399f33dae | R | 25,805 | 612 | #
# Gene set enrichment analysis
#
library(clusterProfiler) # clusterProfiler_4.8.1
library(org.Mm.eg.db) # org.Mm.eg.db_3.17.0
library(enrichplot) # enrichplot_1.20.0 {http://yulab-smu.top/clusterProfiler-book/chapter12.html}
library(tidyverse) # tidyverse_2.0.0
library(cowplot) # cowplot_1.1.1
library(venn)... |
a5a2c92a3f7a6dbc146cf79e50494e8efac14b97b92fc2d889eea6fd0d7c99c5 | R | 25,869 | 731 | ---
title: "Human COVID microglia scRNA low-level processing"
output: html_notebook
---
# Setup
## Goals
1. Rerun all analysis using cellranger 7 with introns excluded (and without cellbender)
## Load packages etc.
```{r}
library(tidyverse)
library(SoupX)
library(Seurat)
library(tidyseura... |
62c8e8260a241902ebd0296e8e78f212943f01dbb220184e7d434fbd8ca9296f | R | 26,446 | 424 | library(Seurat)
library(ggplot2)
library(homologene)
library(RColorBrewer)
library(scCustomize)
setwd("/Projects/deng/Aging/Ex/Mouse_Allen_GSE207848")
GSM6321077.count=Read10X_h5("rawData/GSM6321077_PFC_90wk_1_matrix.h5")
GSM6321077 <- CreateSeuratObject(counts = GSM6321077.count, project = "GSM6321077")
GS... |
81cc90610f40fc640810bf568a06ad2f2214369a4bb0cb9085c3ced5b3f98885 | R | 26,526 | 561 | setwd('/work/AnneSophiaHartebrodt#6698/ms-project/')
require(rhdf5)
require(rhdf5filters)
require(Rhdf5lib)
renv::activate('/work/AnneSophiaHartebrodt#6698/ms-project/r-single-cell-new')
renv::repair()
set.seed(11)
require(Seurat)
library(tidyverse)
require(data.table)
require(ggplot2)
require(ggrepel)
require(colors... |
f62fca975f4675e23d1a08a2901bd066c31be3b8c8c30e26f7a376f0c34ca0fb | R | 26,590 | 587 | #############################################################################################
# These codes have been costumly designed for brain network analysis of 1-2 time point data
# generally acquired by immunolabelling of activity-dependent proteins (i.e. c-fos, Arc)
#
# Many functions here have been largely bas... |
1a019e8b53c49d3589cd91755e1a1db2088f5b79fa8fa8f5049f84c135ce60ce | R | 26,675 | 515 | #####################################################################
# Script to analyze Deeplabcut outputs from open field data #########
# Reto B. Cola ######################################################
#
# Run this script in the same directory, that contains the companion
# raw tracking data downloaded f... |
9ee2ec828754ddb180b51b80c6388b2d415ebf57afae1e9df4f82c5f73447071 | R | 26,688 | 541 | #' Download the Human DLPFC Visium data from LIBD
#'
#' This function downloads from `ExperimentHub` Visium, Visium Spatial
#' Proteogenomics (Visium-SPG), or single nucleus RNA-seq (snRNA-seq) data
#' and results analyzed by LIBD from multiple projects.
#' If `ExperimentHub` is not available, this function will
#' dow... |
8f941678fd2ba63c1b8601e1956e24997d58e36de19acc3574494241707c77f4 | R | 26,805 | 748 | # UPDRS stats: analysis of sensorimotor signal feature on MDS-UPDRS-III score divided into factors.
#
# Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar,
# M., Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical
# sensorimotor rhythms are uniquely linked t... |
9eb2cfeb0f7db16f5f1c8a3928a17a6c0072ab5818ec92415bd0319d78bfe7a2 | R | 27,131 | 503 | ---
title: "062323 Glia Single Cell Analysis Bap1"
author: "Sabine Schneider"
date: "June 23, 2023"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
Loading the necessary libraries
```{r load library, include=FALSE}
library(dplyr)
library(Matrix)
library(ggplot2)
library(... |
48e68175364cf8ac0583284366c6f8151dbcff2067d117d93be9d7e6fec478bb | R | 27,179 | 994 |
local({
# the requested version of renv
version <- "0.16.0"
# the project directory
project <- getwd()
# figure out whether the autoloader is enabled
enabled <- local({
# first, check config option
override <- getOption("renv.config.autoloader.enabled")
if (!is.null(override))
return(... |
783c0b5b25ce805b079cf471c0f57d0a1010b0bac0d2cd05888e6fd130bc2216 | R | 27,671 | 731 | ---
title: "Pre Processing Metrics Benchmarking"
author: "Ally Hawkins for CCDL"
output:
html_notebook:
toc: true
toc_float: true
---
This notebook is a follow up notebook to previous benchmarking done in `02-compare-quants.RMD`.
Here, we have used the most recent release of [Salmon](https://github.com/COM... |
c2cff5abb69ec3694798c101c558dd3d8f072871cd62eba8668c260ed53a5417 | R | 28,025 | 731 | library(shiny)
library(readr)
library(stringr)
library(dplyr)
library(tidyverse)
library(zip)
options(shiny.maxRequestSize = 300 * 1024^2)
ui <- fluidPage(
titlePanel("Object Counter"),
sidebarLayout(
sidebarPanel(
style = "height: 95vh; overflow-y: auto;",
fileInput("left","Please... |
a5e7a9a59d601f4c23dac522a60cb4712cfa39331eb3710137896c395e4cae77 | R | 28,455 | 539 | ##### not used in our revised version #################################################
#######################################################################################
library(Seurat)
library(ggplot2)
library(clustree)
library(pheatmap)
library(presto)
library(dplyr)
library(msigdbr)
library(tibble)
... |
c979741b014f3d1c7608f5a8eb1d141ae1b48e46d9aaa9c5d80d2cb96bcf80c5 | R | 28,711 | 1,020 |
local({
# the requested version of renv
version <- "0.17.2"
# the project directory
project <- getwd()
# figure out whether the autoloader is enabled
enabled <- local({
# first, check config option
override <- getOption("renv.config.autoloader.enabled")
if (!is.null(override))... |
fe7f4f998d13a52965b89dcf265e26b42b291243fdfa137a6709fbaad2aa97e5 | R | 28,789 | 710 | ancova_post_hoc <- function(file = "../../HKFI-FoodIntake/code/ABCdata.tsv",
name = "Figure1"){
library(multcomp)
library(emmeans)
require(tidyverse)
require(rstatix)
require(ggpubr)
require(broom)
require(patchwork)
library(interactions)
dataABC = read_tsv(file)
# ==... |
d09522988a2f2c0cae6182ae65de13cd0c1d697edeccffacb7b73c6dda08c71c | R | 28,855 | 570 | #' Predict concentrations from raw MFI values using a 5PL fit
#'
#' @param MFIs dataframe containing raw MFI values in column "MFI". All other columns are ignored.
#' @param standards dataframe containing the standard curve data with the columns "analyte", "MFI", and "expected"
#' @param return_plots toggle to output ... |
a785e08b149a84c680ae820e5734232da474520b22dc8d1567ac5bf7197282d4 | R | 29,042 | 703 | ---
title: "Cytokine 'deconvolution' analysis"
output: html_notebook
---
# Setup
## Load packages
```{r}
library(tidyverse)
library(ComplexHeatmap)
library(janitor)
library(viridis)
library(ggrepel)
library(ggsci)
library(Cairo)
library(circlize)
library(ggsignif)
pal = pal_npg("nrc")(9)
set.seed(666)
pal_lo... |
b3af62ed46d3008aa6c0be227e233a35c8aaa42b047a88edab972f080f1b263a | R | 29,104 | 727 | .libPaths("/home/u23/haozhang1/miniconda2/envs/seurat/lib/R/library")
options(stringsAsFactors = FALSE)
library(argparse)
library(tidyverse)
library(Matrix)
library(DelayedArray)
library(Seurat)
library(irlba)
library(patchwork)
library(plyr)
library(stringr)
library(harmony)
library(Signac)
library(S4Vectors)
library... |
95f6931ed95a4234a14e6030df735714ab7731835515f05011ec7de8649bb40f | R | 29,694 | 872 | ---
title: "CosMx_Analysis_060923"
output: html_document
date: "2023-06-09"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
Load libraries
Load libraries
```{r load labraries}
library(Seurat)
library(future)
library(rgeos)
library(ggplot2)
library(rlang)
library(... |
c9a3f376ed142270b359dfb03562682c181591bf4b0a3713087be9ba9d767ca3 | R | 29,708 | 744 | .libPaths("/home/u23/haozhang1/miniconda2/envs/seurat/lib/R/library")
options(stringsAsFactors = FALSE)
library(argparse)
library(tidyverse)
library(Matrix)
library(DelayedArray)
library(Seurat)
library(irlba)
library(patchwork)
library(plyr)
library(stringr)
library(harmony)
library(Signac)
library(S4Vectors)
library... |
ef84ff2798a5947b993792b4094bdabe3e01cfe9bace4f9954fc0610688f2f4f | R | 29,851 | 531 | setwd("/dragon-home/general/Cruchaga_Data/bulkRNASeq")
library(CellMix)
library(ggplot2)
library(reshape2)
library(grid)
library(gridExtra)
#study = "201703_MendelianVsSporadics/pipeline-v1-hg38"
study = "201904_MGI_bulkRNAseq_SUNSHINE"
study="201703_MendelianVsSporadics"
# load in deconvolution algorithm #
#source( ... |
1d675054b4fa2691bc820df4f056032e9e36bb79c0945e30e45c7821930c24d3 | R | 29,998 | 742 | #################################################################################################################
#################################################################################################################
######
###### Title: pqtl_ms_make_fig3_figS3
######
###### Des... |
50b037c1d5180b2d782b85f43bea3ed2f788d64552d42975d27e50159a878bef | R | 30,115 | 267 | setwd('/work/AnneSophiaHartebrodt#6698/ms-project/')
renv::activate('r-single-cell-new')
renv::repair()
set.seed(11)
require(data.table)
library(GWENA)
library(magrittr)
require(stringr)
require(ComplexHeatmap)
bulk.data.dir<- '/work/AnneSophiaHartebrodt#6698/ms-project/submission/data/bulk'
out.dir<-file.path('/... |
6b76cb108bd25cf308cb6d5522b6002a2a66c0f1dedea19a545ef5c776b673c0 | R | 30,357 | 374 | library(lme4)
library(lmerTest)
library(ggplot2)
library(ggdist)
library(report)
library(tidyverse)
library(ggpubr)
library(rstatix)
library(nlme)
library(emmeans)
library(effectsize)
library(rstatix)
library(ggpattern)
# Graph with 3 groups hemispheres combined
asl_roi_3group <- read.csv("benzogap_asl_3groupsgraphs_S... |
d1b27628f73a91c4d223ded8d0e51ccbe322e7c724b4ea439c416a02027e7c47 | R | 30,860 | 766 | #' Find enriched pathways represented by a significant PSN
#'
#' Remove the excessive context-specific pathways (ban_list).
#' Remove the pathways which size is bigger than max_size (max_size:200).
#' Keep the (n_top_pathways:50) having the highest number of significant elements (sign_df).
#' For each pathway (pathways... |
fa812a9bf9d3d4d7fa74504a47c1c34afe2e8c9333d2ef5f59dcc3bc0311a9c0 | R | 31,602 | 801 | ---
title: "Spatial Transcriptomics Benchmarking"
author: "Ally Hawkins for CCDL"
output:
html_notebook:
toc: true
toc_float: true
---
In this notebook we are comparing the use of Alevin-fry and Spaceranger for quantifying spatial transcriptomics libraries.
Two spatial transcriptomic libraries were quantif... |
5c2476ac746008c607d160386facc1384ef88b78eadbd3dea5fcb224db852ab2 | R | 31,967 | 668 | # Fit models for the main analysis. Analysis of signal features as as a function
# of age, sex, group, and cortical thickness.
#
# Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M.,
# Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor
# rhy... |
004133e5f37d5f449dc775aa3a55123188f123f67f20f5d4cb49d97b6ff4f5b6 | R | 32,279 | 1,254 | library(dplyr)
library(Seurat)
library(patchwork)
library(tidyverse)
library(gridExtra)
library(cowplot)
library(hdf5r)
# Loading the dataset 2
#assuming /home/rstudio/BSN_NewData/filtered_h5s contains data from set 2, modify as approppriate
data.dir="/home/rstudio/BSN_NewData/filtered_h5s"
setwd(data.dir)
#set 2 d... |
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