sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
50dd7baa95a15f68bc922589852f7dc9fe3f370f89a2b67724e7a389b9afe7f4 | R | 35,913 | 894 | # ==============================================================================
# Script 21: Fig 3E, 3F & SupFig 10 - SV Fusions Analysis
# ==============================================================================
# Description: Identifies and visualizes gene fusions from Bionano structural
# variati... |
2f8d8ceb4ceacab659c65371a17132a2877bf02ae16fbf487356e0fc5eff057c | R | 35,952 | 1,036 | # Rewrite of the factor.switching package ---------------------------------
# sp_new <- function(iter, lambda_varimax, q, p, dim_all_c, all_c, lambda_hat, st,
# cost.matrix, perm){
# lambda <- matrix(lambda_varimax[,,iter], nrow = p, ncol = q)
# costs <- numeric(dim_all_c)
# for (i in 1:dim_al... |
00c240b7bb07cf8861f3c1374e78b744d25e48a0e33cff5a6a806d834bfa7c5c | R | 35,957 | 491 | library(ggplot2)
library(UpSetR)
library(data.table)
library(RColorBrewer)
library(dplyr)
library(tidyr)
library(ggsci)
################################################################################
##### Set paths & Define helper functions ######################################
{
setwd("./") # FIXME: SET TO THE F... |
7013a84401c2756eae112cf3fe46e72ad645784e1a522f89b081d59325e8d19e | R | 36,098 | 888 | ####################################################################
# Peak Set Creation Methods
####################################################################
#' Add a Reproducible Peak Set to an ArchRProject
#'
#' This function will get insertions from coverage files, call peaks,
#' and merge peaks to get a "... |
55c606fd5f9de0b97e2a35fb2d4055ec0f261cc5dded9c9061d0e6265e869d80 | R | 36,115 | 1,026 | ####################################################################
# Save Visualization Methods
####################################################################
#' Plot PDF in outputDirectory of an ArchRProject
#'
#' This function will save a plot or set of plots as a PDF file in the outputDirectory of a given ... |
93c26f0d73d95db133690116fb98c56f266dde9cdf36f51a7c18d88c22106230 | R | 36,151 | 1,062 | ---
title: "220516Geh - nf-core/rnaseq processing - with UMI"
author: "Charlie Whittaker and Yann Vanrobaeys"
date: "7/27/2024"
output:
html_document:
toc: true
toc_depth: 3
html_notebook: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(tidy=FALSE, cache=TRUE,
dev="png"... |
7bafbe0442d8b4c892ce6d2a8e6987d216dccff19779f06aa0a4803e86fe9c88 | R | 36,374 | 692 | ---
title: 'MultiNicheNet output interpretation: PreE vs PreNE'
author: "Robin Browaeys"
date: "2024-05-13"
output: html_document
---
## Prepare visualizations
```{r}
library(tidyverse)
library(nichenetr)
library(multinichenetr)
```
```{r pressure}
multinichenet_output = readRDS("../output/MNN_BCA_preEvspreNE_final_... |
5acb9dc6de2ab14c8acf58248f79ca21e3b91652f0a16f2faf88d2d728d486f5 | R | 36,519 | 696 | ##############################
### Run ArchR peak calling analysis on CAREmut multiome ATAC data for all malignant states - NPC, OPC, Undiff, MES, AC
### Author: Kevin Johnson
##############################
## Generate malignant UMAP and perform differential gene/peak accessibility on RNA-defined MALIGNANT states acro... |
9216bb9ed75bcf7032649ba7e5b7dce3bab751d0009d0d80376d3537e5d93954 | R | 36,555 | 599 | #set working directory ====
setwd("/athena/ganlab/scratch/lif4001/LG815C/DF_1stRound_mt5")
#install.packages
library(Seurat)
library(ggplot2)
library(DoubletFinder)
library(SoupX)
#for loading Cell Ranger counts:
sc = load10X('/athena/ganlab/scratch/lif4001/LG815C/cellranger/LG815_C_106/outs')
sc = autoEstCont(sc)
LG8... |
01c25a91550a775e0f495ef5249299c95f97e3401e08334744cba3edd2f1f1ad | R | 36,586 | 534 | # unit-tests for BLOBFISH
context("test BLOBFISH functions")
test_that("[BLOBFISH] SignificantBreadthFirstSearch() function yields expected results", {
skip_if_not_installed("matrixTests")
set.seed(42)
# Construct a starting network, which will be modified.
# Here, we expect genes A and B to be connected after... |
29ff31d2cc63ab3360517570233d116a7670ac298e26e4b22ff80d6b37667c27 | R | 36,699 | 1,038 | ## Azin's note: error handling code adapted from R core team/Martin Maechler
## as noted below.
##================================================================##
### In longer simulations, aka computer experiments, ###
### you may want to ###
### 1) catch all errors and warnings (and continue) ###
### ... |
b9cc774bbd680fbf2afc9389c2689d17c11671a9dfc3e430faae8bfdc42299f9 | R | 37,217 | 599 | #set working directory ====
setwd("/athena/ganlab/scratch/lif4001/LG815_TDI/DF_1stRound_mt5")
#install.packages
library(Seurat)
library(ggplot2)
library(DoubletFinder)
library(SoupX)
#for loading Cell Ranger counts:
sc = load10X('/athena/ganlab/scratch/lif4001/LG815_TDI/cellranger/LG815_Ctrl_160/outs')
sc = autoEstCon... |
ea5ee0e6d6b9f079ff5c633b232704d31a50305593a5c9956642890a6baae857 | R | 37,252 | 879 | ####################################################################
# Gene Integration Matrix Methods
####################################################################
#' Add a GeneIntegrationMatrix to ArrowFiles or an ArchRProject
#'
#' This function, will integrate multiple subsets of scATAC cells with a scRNA ... |
1fc41caf4c3e9ec0f0a103ce0fad6056dbbb457f87388d82c08ee36376c3d04d | R | 37,278 | 775 | ##################################
# 10x scRNA processing of MGG152 IDH-mutant gliomaspheres with CRISPR targeting CDKN2A from the Suva/Cahill labs
# Author: Kevin Johnson
##################################
library(tidyverse) # 1.3.1
library(Seurat) # 4.3.0
library(Matrix) # 1.6-5
library(ggpubr) # 0.4.0
library(Dou... |
10b837dd7a7af2166cd4427939f8c16ef5aadd88382aea5408ed8ece5eaa1b10 | R | 37,308 | 947 | # Clear variables
rm(list = ls())
library(readxl)
library(lme4)
library(optimx)
library(lmerTest)
library(effects)
library(emmeans) #
library(brms)
# load data
setwd("C:/Users/Eleonora/OneDrive/MyExperiments/Interoception_exp/2_pain perception/")
data <- read_excel("Data_v3 - 2504.xlsx")
# recode fa... |
1fe79da85ac016d1397c3649d9697bebe70d59a67d1ebbf513771f571e0308e4 | R | 37,320 | 1,078 | library(DESeq2)
library(pheatmap)
library(RColorBrewer)
library("gplots")
library(reshape2)
library(ggplot2)
library(limma)
library(EnhancedVolcano)
library(tidyverse)
countData <- Yan_count_matrix
mapper_df <- M23_Mapper.txt #"gene_id" "gene_symbol"
countData<- merge(countData, mapper_df, all.x = TRUE, by.x = 'Gene',... |
30d0006eec7c7a562307192427469302bea22a2941d932334d9ce188722f1795 | R | 37,362 | 735 | #######################################################################################
###############--------------- MODEL BASED TASK ANALYSES ---------------###############
#######################################################################################
### In this script:
# (1) Preprocess data
# (2) Model ... |
399a2fe371f8ae20dc0f6e00c7c3cc36567c1640d4ecc5875dc5fdb51d98aeb9 | R | 37,367 | 1,095 | #
# sleuth: inspect your RNA-Seq with a pack of kallistos
#
# Copyright (C) 2015 Harold Pimentel, Nicolas Bray, Pall Melsted, Lior Pachter
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software F... |
696455fee6e9c5ebb248160088d13f038e5f87296da9c4eab288aade630efc97 | R | 37,492 | 636 | #########################
# Supplementary tables #
########################
# GSEA table
library(dplyr)
# Retrieving GSEA data
load("C:/Users/User/Documents/Drive_PC/Lucas/GitHub/ROSMAP-MOFA/MOFA_real/Best_mofas_analysis/standart_50f/final_table_v3.RDATA")
# Renaming protein modules
final_table_v3$pathw... |
043c86b865c165f6b0ce7f2da88a7ae7f689ab421d68ff0367a5ed31d0cd8d21 | R | 37,523 | 687 | ##################################
# Visualize the CIBERSORTx estimated cell type/state abundance in the Glioma Longitudinal AnalySiS (GLASS) RNA sequencing dataset across grade, time points, and stratified by genetics.
# Author: Kevin Johnson
##################################
# This script generates figures related ... |
74a637c192e2b22d5a7e1d29516508cd9883f5a186900b39fd9e9d71f71af610 | R | 37,710 | 830 | #!/usr/bin/env Rscript
# ------------------------------------------------------------------------------
# Author: Gabriele Girelli
# Email: gigi.ga90@gmail.com
# License: MIT - Copyright (c) 2020 Gabriele Girelli
# ------------------------------------------------------------------------------
# UTILITIES ============... |
82f7a4e93d7597f7702c8ac7fbd698a8a328584fdee5b04e4e41a5bd09a65711 | R | 37,802 | 885 | # run_spp.R
# =============
# Author: Anshul Kundaje, Computer Science Dept., MIT
# Email: anshul@kundaje.net
# Last updated: Feb 12, 2012
# =============
# MANDATORY ARGUMENTS
# -c=<ChIP_tagAlign/BAMFile>, full path and name of tagAlign/BAM file (can be gzipped) (FILE EXTENSION MUST BE tagAlign.gz, tagAlign, bam or ba... |
cbd52f5441b4e24d36f671902533995872797e385ba93b1d458f536cb80578ba | R | 37,817 | 982 | #
# pliu 20150608
#
# module for processing RNA-seq data
#
main <- function() {
name2func <- list(
'selTrainingTr' = selTrainingTr,
'prepTSSPeakFeatures' = prepTSSPeakFeatures,
'prepPeakSignalGCLenFeatures' = prepPeakSignalGCLenFeatures,
'prepMultiTargetsFeatures' = pre... |
26afe56bc53e2317df61829471146a9617b2a0d67a95941a1b18670f4977fb8d | R | 37,847 | 1,137 | ---
title: "Figure 1: MIC-Drop-seq Proof-of-Concept Validation"
author: "Clay Carey"
date: "2024-05-08"
output: html_document
---
First- set your base directory to the folder with the downloaded 'input_data" folder. This contains all source data to run the code to reprodce figures.
```{r setup}
# Set working direc... |
519e21732c812a37e1b1fc5e6b0a180a6cbea71e32a0a818f26cd36fcaa7adc8 | R | 37,859 | 886 | # run_spp_nodups.R
# =============
# Author: Anshul Kundaje, Computer Science Dept., MIT
# Email: anshul@kundaje.net
# Last updated: Feb 13, 2012
# =============
# MANDATORY ARGUMENTS
# -c=<ChIP_tagAlign/BAMFile>, full path and name of tagAlign/BAM file (can be gzipped) (FILE EXTENSION MUST BE tagAlign.gz, tagAlign, ba... |
c43194fcdc546cf7b1cd3c03b42ccb4da88a9ede02fb5373f744c9c4b21eb99f | R | 37,918 | 888 | # Skeletonise flywire neurons
#' Skeletonise neuron meshes using skeletor
#'
#' @description You can skeletonise complex neuron meshes using skeletor
#' \href{https://github.com/schlegelp/skeletor}{skeletor-1.0.0}. Skeletor is a
#' python library and this function wraps a series of skeletor functions in
#' order... |
048dcf46ab6663218b233df2e3b53bdca5ccbbaa83006e6c2188eb451f51b9c1 | R | 37,964 | 889 | #!/usr/bin/env Rscript
# ------------------------------------------------------------------------------
# Author: Gabriele Girelli
# Email: gigi.ga90@gmail.com
# License: MIT - Copyright (c) 2020 Gabriele Girelli
# ------------------------------------------------------------------------------
# UTILITIES ============... |
a0ffbfef2c544edca8aaeb3d08367476dfb22ed23686714966dca098a0e381fb | R | 38,315 | 927 | #' Main ALPACA function
#'
#' This function compares two networks and finds the sets of nodes that best characterize the change in modular structure
#' @param net.table A table of edges, with the first column representing the TFs ("from" nodes) and the second column representing the targets ("to" nodes). The third colu... |
27929833f0e77fc393d1393707eaf50f1fbee370a5e2ed89de69e05bc0a741f1 | R | 38,699 | 1,442 | ---
title: "Physical functioning and physical fitness in glioma patients: SF36 AND CIS20 part 3"
output: html_document
date: '2024-03-04'
output: html_document
---
#### Email: m.e.c.blom@amsterdamumc.nl
#### Purpose of script:
Code analysis
#### Reviewed by Maxine Gorter
#### Notes
# Part 3 #
# 3.1... |
19d7730f687335be9af1a688ac25335c7e1fcce1512859d9e0298e6fdaf68ee9 | R | 38,932 | 843 | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
CCT_cpp <- function(pval) {
.Call('_SAIGE_CCT_cpp', PACKAGE = 'SAIGE', pval)
}
setGlobalVarsInCPP_LDmat <- function(t_impute_method, t_dosage_zerod_cutoff, t_dosage_zerod_MAC_cutoff, t_mis... |
19830b49fb3950e47fae60db636ada09afdf6eae3923a72b7dbcbca9890cbef6 | R | 39,054 | 931 | # ==============================================================================
# Script 24: Figure 6 - Patient Signatures & Resemblance Scores
# ==============================================================================
# Description: Generates ILC vs NST multi-omic signatures from TCGA patient
# tum... |
d239b1990c136f693817f306421362e89f0cbf8a228174c9f4d55247738e1c13 | R | 39,067 | 1,276 | ####################################################################
# Reading fragments from Arrow Files
####################################################################
#' Get the fragments from an ArchRProject
#'
#' This function retrieves the fragments from a given ArchRProject as a GRangesList object.
#'
#'... |
f75edd3682ab20846ba769f58c2fab81b390afc9204515cd998a1051333379f5 | R | 39,095 | 1,034 |
setwd("/Users/deidrejansson/Library/Mobile Documents/com~apple~CloudDocs/Documents/Iliff lab /Experiments/CP circadian project/Expt 13 sleep study mouse choroid plexus/Circadian R folder/CP circadian R data mining")
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("... |
74fae307d13018822a3c3fd9e164192e8199b72dfe9b828b2aff2cb9a9c4594f | R | 39,233 | 987 | # open R
srun -n 10 -p interactive --pty /bin/bash
module load cluster/gsl/1.15
module load cluster/htslib/1.9-devel
module load cluster/build_tools/llvm/8.0
module load cluster/util/gcc/8.2
module load hdf5_18/1.8.21
conda activate r_env
#conda deactivate
R
suppressPackageStartupMessages({
library(SummarizedExp... |
1f23c308acbc7261c23362a4c09f6ac8266406fb3ce2a95a41f2c55f0908b4cd | R | 39,699 | 959 | #' banc-synapses-v3-optimised — Bounding-box-accelerated v3 synapse classification.
#'
#' Same pipeline as `banc-synapses-v3.R` but `classify_chunk` adds an XYZ
#' bbox pre-filter before each `alphashape3d::inashape3d()` call, cutting
#' point-in-surface tests from ~5M to ~10⁴–10⁵ per neuropil.
#'
#' @section Reads:
#'... |
7dfad81eb40f8d483876cd487a39d3668e7f7d37c38fb1153dae766b0a741aba | R | 39,888 | 1,149 | ---
title: "N-back Preprocessing"
author: "Michael Colwell"
date: '22/03/2024'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
### N-back DDM + neuroimaging data processing scripts for the PEACE Study ('Pitolisant Effects on Affect and Cognition Exploratory Study') (NCT05... |
40415f12141a8dae89d4bb8d156f0a89829e91fa93a6a7a8d88157b51db66ce3 | R | 39,906 | 1,334 | library(MASS)
library(Matrix)
library(matrixcalc)
library(mvtnorm)
library(sinib)
library(prodlim)
library(foreach)
library(zeallot)
library(plyr)
library(ggplot2)
library(parallel)
library(foreach)
library(doParallel)
library(stringr)
library(dplyr)
find_interval <- function(val, num_levels){
breakpoints <- seq(0,1,... |
a0adc92b1b633058a65b30f612d231b5179c43ad9b5fcaf5fabf9ce5d43171ea | R | 39,974 | 1,040 | ---
title: "mediation"
author: "Neslihan Yildiz Ozhan"
date: "2024-12-12"
output: html_document
---
```{r}
install.packages("dplyr")
install.packages("mgcv")
install.packages("mediation")
library(mgcv)
library(mediation)
library(dplyr)
```
```{r}
df <- read.csv("~/Desktop/abcd_coi.csv")
df <- df %>%
mutate(
... |
6488a36da216b565cfa11bc47e30e5371f967909677b96a32f0b2c0ef04dce1d | R | 40,364 | 619 | #' @title get_ligand_activities_targets_DEgenes
#'
#' @description \code{get_ligand_activities_targets_DEgenes} Predict NicheNet ligand activities and ligand-target links for the receiver cell types. Uses `nichenetr::predict_ligand_activities()` and `nichenetr::get_weighted_ligand_target_links()` under the hood.
#' @u... |
0b3a679f2134e148613f80f7e6915b1002e4e1735cd785cf97efd70697006d44 | R | 40,593 | 1,171 | ---
title: "EEG Sleep Analysis"
author: "Emily Stanyer"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
df_print: paged
pdf_document:
toc: true
number_sections: true
params:
# ---- INPUTS ----
profile_dir: "Data/raw/EEG/sleep_profile/" # folder of nightly EEG profile .xlsx files
... |
8c88d5a3423f59d50b3c7d981978278ad1c54825c228cc551669c33b9907861b | R | 40,669 | 1,085 | #' Print information about fafbseg setup including tokens and python modules
#'
#' @description Print information about your \bold{fafbseg} setup including your
#' FlyWire/ChunkedGraph authentication tokens, Python modules and the
#' nat.h5reg / java setup required for transforming points between EM and
#' light ... |
12d2df00ab1699a2f0bc398f0434527fe1cb02a99d611afb7f51457b5c938b37 | R | 40,694 | 1,195 | ---
title: "20260620_Plotting_variables_and_groups_v1.12"
author: "Aaron Haeusler"
date: "`r Sys.Date()`"
output: html_document
---
```{r setup, include=FALSE}
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
readr,
dplyr,
ggplot2,
forcats,
ggnewscale,
RColorBrewer,
reshape2,
scales
... |
1f7df602893648e5406dc255c86e79c075ec109b399053216df5b7bfeddc825f | R | 40,720 | 685 | # The main script for quantifying spatial ligand-receptor interactions
# load libraries
library(patchwork) #1.1.1
library(Rmisc) #1.5
library(reticulate) #1.22
library(data.table) #1.14.2
library(readxl) #1.3.1
library(reshape2) #1.4.4
library(pheatmap) #1.0.12
library(Seurat) #4.0.2
library(ggplot2)
library(readxl)
l... |
db5a5d3e67deb4681f4f31745109731df1b0fdc6ecee1d999e185070d3c87abf | R | 40,813 | 1,162 | # #### Staircase ----
# #' Assign Stop-Signal Delays (SSDs) to trials
# #'
# #' @description
# #' This function assigns stop-signal delays (SSDs) to trials based on specified probabilities.
# #'
# #' @param d A data frame containing trial data with a response factor column 'lR'
# #' @param SSD A vector of stop-signal d... |
ae389371932669a89baeaacb83dd7a24e292ad5f2657fa1a20bf018d3a487f9a | R | 40,975 | 4,097 | hexamers <- c(
'AAAAAA',
'AAAAAC',
'AAAAAG',
'AAAAAT',
'AAAACA',
'AAAACC',
'AAAACG',
'AAAACT',
'AAAAGA',
'AAAAGC',
'AAAAGG',
'AAAAGT',
'AAAATA',
'AAAATC',
'AAAATG',
'AAAATT',
'AAACAA',
'AAACAC',
'AAACAG',
'AAACAT',
'AAACCA',
'AAACCC',
'AAACCG',
'AAACCT',
'AAACGA',
'AAACGC',
'AAACGG',
'AAACGT',
'AAACTA',
'AAACTC',
'AAAC... |
af3786cab0d9f045a1210a18052ff2c2183e8f3f9d3f297004e53127bfcd3395 | R | 41,107 | 1,295 | ###############################################################################
### (1) combine_factors()
###############################################################################
combine_factors <- function(df, factor_names, new_col_name) {
factor_names <- factor_names[factor_names %in% colnames(df)]
if (len... |
b8c30e194a3c70bee34f54762e56bb853a57fb7cc5d0c9a3aca5d89399227243 | R | 41,431 | 926 | here::i_am("scripts/1.neural_differentiation_dataset/1.1.mapping_and_QC/1.1.10.QC_and_filtering.R")
library(glue)
library(tidyverse)
library(dplyr)
library(biomaRt)
library(viridis)
library(cowplot)
library(Seurat)
library(plyranges)
library(patchwork)
library(foreach)
library(doParallel)
library(SingleCellExperiment)... |
464578538f50566420bc77eedf07332f89ac1cd9a7e0eb0162c1647c1a749b9a | R | 41,516 | 1,031 | ---
title: "A meta-analysis of genus-metabolite associations"
output:
html_document:
css: Custom_Formatting.css
toc: true
toc_depth: 3
df_print: paged
code_folding: show
---
## Preparations
```{r collapse=TRUE}
library(ggplot2)
library(viridis)
library(broom)
library(dplyr)
library(gt)
library(f... |
df92854d562cc21279c1568f87882aae189cc83f3356a84bed98d343257e6a69 | R | 41,552 | 1,040 | ### -----------------------------------------------------------------
### Legacy exploratory analysis by a member of the Wilson Lab.
### Historical record only — not part of the bancpipeline release.
### -----------------------------------------------------------------
######################
### load libraries ###
###... |
abeb43aa8da788cc97a5cca5fa9ee0d88ab8997184273ae16c3ca965048c2049 | R | 41,679 | 1,208 | # Helper Functions for Fly Connectome Data Access
# ================================================
# These functions provide unified access to connectome data from both
# Google Cloud Storage and local file systems, with support for lazy
# loading and filtering of large Parquet datasets.
#' Setup GCS Filesystem
#'
#... |
33a323d3e28481a37d8ac7dc643e75c98c88fb9b4e290d74892e2430390c0d14 | R | 41,768 | 739 | #set working directory ====
setwd("/athena/ganlab/scratch/lif4001/LG815C/DF_2ndRound_mt5")
#install.packages
library(Seurat)
library(ggplot2)
library(DoubletFinder)
library(SoupX)
#for loading Cell Ranger counts:
all <- readRDS(file = "/athena/ganlab/scratch/lif4001/LG815C/DF_1stRound_mt5/LG815_C_106_QC.rds")
#Doublet... |
78e8074887cea10e8677425075821d6f0d99d091a334c7c58372ed46e71b1901 | R | 41,770 | 1,145 |
##Mann-Whitney U test
# install.packages("ggcorrplot")
# BiocManager::install("ComplexHeatmap")
library(gmodels)
library("data.table")
library("dplyr")
library(ggplot2)
library(ggpubr)
library(effectsize)
library("ComplexHeatmap")
# Mann-Whitney U test based on RPKM values --------------------------------... |
ea2e75277a9e5c1c77f9ca37138258ef77a4853324ceffd68ec7498e9750efc3 | R | 41,908 | 985 | ###########################
### Assess synapse dump ###
###########################
source("banc/banc-startup.R")
library(vroom)
library(dtplyr)
########################################
### PROPORTION OF SYNAPSES PROOFREAD ###
########################################
# csv info
desired_columns <- c('id', 'size', 'pre... |
38ee1eb7a8f511ef96862b78fafb86bda5ee9e662ea9f11327fe09e5285d1ccb | R | 41,967 | 1,107 | ---
title: "Questionnaire_Analysis"
author: "Michael Colwell"
date: "2024-07-09"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Analysis script for Questionnaire data (PEACE Study), by Michael Colwell (michael.colwell@psych.ox.ac.uk / michaelcolwell92@gmail.com)
These... |
94cf8eac8cac92f5a5f6aee8df3924ca991ff544c807291c3396a51138a3783a | R | 42,038 | 1,231 | ---
title: "MIC-Drop-seq Figure 2 Analysis"
subtitle: "50-Gene Transcription Factor Screen in Zebrafish Embryos"
author: "Clayton Carey"
date: "`r Sys.Date()`"
output:
html_notebook:
toc: true
toc_float: true
toc_depth: 3
code_folding: show
theme: flatly
---
```{r setup, include=FALSE}
# =======... |
e8a0f8a24dfb50192d508b13a9fdae0e55766d5510d6f6aced329eb776ec4ce6 | R | 42,074 | 1,018 | get_stop_criteria <- function(stage, stop_criteria, type){
if(is.null(stop_criteria)){
if(stage == "preburn"){
stop_criteria$iter <- 50
}
if(stage == "burn"){
stop_criteria$mean_gd <- 1.1
stop_criteria$omit_mpsrf <- TRUE
if(type != "single"){
stop_criteria$selection <- c("a... |
52ffb69a201b85bcb28dc5cfcd9ab26bf148c46da2d14d869fbc8504e79570a7 | R | 42,095 | 928 | ##############################################
### Compile meta data from various sources ###
##############################################
source("banc/banc-startup.R")
message("##### Building BANC meta data #####")
version <- "elastix_tpsreg_0714"
version <- "elastix_tpsreg_240721"
# Register cores
cl <- setup_para... |
7d57da9dd4ef95949c2069b4be0a3ffae1e06520b1855a43261ee863becc4682 | R | 42,147 | 739 | #set working directory ====
setwd("/athena/ganlab/scratch/lif4001/LG815_TDI/DF_2ndRound_mt5")
#install.packages
library(Seurat)
library(ggplot2)
library(DoubletFinder)
library(SoupX)
#for loading Cell Ranger counts:
all <- readRDS(file = "/athena/ganlab/scratch/lif4001/LG815_TDI/DF_1stRound_mt5/LG815_Ctrl_160_QC.rds")... |
f4b056c7e91685a1d8f6dbf84e0b5f587fa8e32d6cd17e7f55aa50d834d22b23 | R | 42,197 | 829 | ---
title: "acesinabcd"
author: "FB"
date: "2024-03-11"
output:
word_document: default
html_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## ELA+ scores for ABCD data
Running this code will create ELA+ scores for Baseline through Year 3.
Need to run the setup file (ELAf... |
65b95731ceba0557d154398b51d77e933122fccab9c7c9d3df0622afe272cea6 | R | 42,198 | 1,019 | amos_peak_calling_function <- function(trk, percentiles = 0.99, canonical = FALSE) {
q <- gquantiles(trk, percentiles = percentiles, iterator = 20)
atac_hits = gscreen(glue::glue("{trk}>{q}"))
hits_v = gextract(trk, intervals=atac_hits, iterator=20)
hits_v = hits_v[order(-hits_v[,trk]),]
hits_peak = hits_v[!... |
2c37d21f19aa9e34a24f0a1d1e0ddae8befef0a23da49e3f3d59c0b862e14e7d | R | 42,216 | 1,042 | #' Main clustering function for condor.
#'
#' This function performs community structure clustering using
#' the bipartite modularity described in
#' \code{\link{condorModularityMax}}. This function uses a standard
#' (non-bipartite) community structure clustering of the uni-partite,
#' weighted projection of the orig... |
df38adc41f5847a09ac50e3af9d9c437874d54fcbedc2c9221784940dc2731cb | R | 42,514 | 1,135 | ---
title: "Figure_4"
author: "Clay Carey"
date: "2025-01-29"
output: html_document
---
```{r setup}
knitr::opts_knit$set(root.dir = "")
```
Import required packages
```{r message=FALSE, warning=FALSE}
library(Seurat)
library(tidyverse)
library(igraph)
library(ComplexHeatmap)
library(viridis)
library(scCustomize)
lib... |
d84ad129cde1572ea9a7ed44802dfcdf289be2200bcd060fd4fe8388e8864047 | R | 42,636 | 831 | ################################################################################
###############---------------- PARSING FUNCTION ----------------###############
################################################################################
## Parsing study data from JATOS files -------------------------------------... |
7fabe17cdfa2ce893b1698e31be094670f8839351d2f5aadcaa7446f2c90d43c | R | 42,944 | 907 | ###########################################################################################
###############--------------- ANALYSES OF CIRCADIAN EFFECTS ---------------###############
###########################################################################################
### In this script:
# (1) Create grouping ... |
6022ba16e4e141251054790a385593f56249425ce938aa067c235afa6f4dfefb | R | 43,192 | 703 | ---
title: "Introduction to spatialLIBD"
author:
- name: Leonardo Collado-Torres
affiliation:
- &libd Lieber Institute for Brain Development, Johns Hopkins Medical Campus
- &ccb Center for Computational Biology, Johns Hopkins University
email: lcolladotor@gmail.com
- name: Kristen R. Maynard
af... |
24cd7bc9aaf6a1a3dc6533e0059d3314320416c021efb4fb5ac6e668dd3d7f45 | R | 43,220 | 889 | ---
title: "MultiNicheNet analysis: MIS-C threewise comparison - sample-agnostic/cell-level alternative"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: MIS-C threewise comparison - sample-agnosti... |
7d589340b9a6887297f32c3d61a7481d0c84eedd08abf03a5a4236634651ea33 | R | 43,577 | 172 | #' Return a Neuroglancer scene URL for MANC dataset
#'
#' @description The default behaviour is to generate a rich neuroglancer scene
#' with including any passed \code{ids} using the current Clio DVID node. This
#' means that meshes should be in sync. See
#' \href{https://flyem-cns.slack.com/archives/C01MYQ1AQ5D... |
4e3eabdb9a99b25159a7a0adc74b291a06eec82379a5c29d0578e4cdd671a886 | R | 43,656 | 1,117 | # 2 predictors ------------------------------------------------------------
bf_sens_2int = function(m.orig, pred1, pred2, pr.desc, main.code, file.log, sense_dir, iter = 1000, reps = 1) {
ls.packages = c("brms", "bridgesampling", "tidyverse")
lapply(ls.packages, library, character.only = TRUE)
# set cor... |
a230be0d891fbb0c753f8e12c43edf60500550d5fb9b951ad0cf6cbc59e3f7bc | R | 43,672 | 1,029 | #' banc-al-type-changes — Detect BANC↔FAFB type mismatches for ALLN/ALPN neurons.
#'
#' Reads Codex BANC↔FAFB connectivity alignment scores for the antennal-lobe
#' local + projection neuron cutout, joins to SeaTable to compare against
#' the curated `fafb_cell_type`, emits review CSV + per-row neuroglancer
#' links, t... |
12ee4a775d432b9e2d880ab7185dc02517bf8060435dc333d62fff93e07b28e2 | R | 43,923 | 1,361 | ##########################################################################################
# Output Directory
##########################################################################################
#' Get outputDirectory from an ArchRProject
#'
#' This function gets the outputDirectory from a given ArchRProject. I... |
fd6e23a637d82445613efed7aea732b52924f88f65c63f46df02360952e6056b | R | 43,983 | 1,296 | ---
title: "Tutorial 05: Transcriptomics and Connectomics Integration"
author: "Alexander Bates"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
toc_float: true
code_folding: show
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(
echo = TRUE,
warning = FALSE,
message = FALSE,
fig.wid... |
5ad68b4c17d2a13002699d7b59d53532f9f3f1aa1663f04e1f1ae56a7d9d7f4f | R | 44,014 | 1,047 | library(Seurat)
library(Matrix)
library(ggplot2)
library(plyr)
library(tidyverse)
library(tidyr)
library(dplyr)
library(ggpubr)
library(reshape2)
library(rio)
library(data.table)
library(harmony)
library(GeneOverlap)
library(readr)
library(cowplot)
source('~/SCRIPTS/utility_functions.R')
set.seed(1234)
# set variables... |
45489342ffc293723e07336107ce3b33e6cd3490f855a86a70d611a1748f348b | R | 44,364 | 1,206 | ---
title: "S1: behavioural, conventional analysis with brms"
author: "I. S. Plank"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
number_sections: true
fontsize: 10pt
#geometry: margin=0.5in
---
```{r settings, include=FALSE}
knitr::opts_chunk$set(echo = T, warning = F, message = F, fig.align =... |
5addab210b9dfdf76fffe11919a35844961ee9f82909456961969bfabda797eb | R | 44,425 | 1,048 | ### -----------------------------------------------------------------
### Legacy exploratory analysis by a member of the Wilson Lab.
### Historical record only — not part of the bancpipeline release.
### -----------------------------------------------------------------
#############################################
###... |
05b6cfbea469f3ecb1283fb1764498e7a3b2a4802aa8e6e5314bad53a78f3dda | R | 44,506 | 822 | ####****差异分析以及功能富集--------------
####*****每个细胞类型在不同样本之间差异分析--------
scRNA <- readRDS(file = ".\\scRNA_anno_cluster.rds")
metadata <- scRNA@meta.data
##meta.data添加信息
group.id <- as.data.frame(metadata[,4])
rownames(group.id) <- rownames(metadata)
group.id$group <- t(as.data.frame(stringr::str_extract_all(group.id$`metad... |
2af8ebaa085b16c0813b7b159491f736ec643e68cd23aac48cab51dac3f8a853 | R | 45,087 | 1,145 | ---
title: "scRNA-seq processing"
author: "Charlie Whittaker and Yann Vanrobaeys"
date: "2024-07-08"
output:
html_document:
toc: true
toc_depth: 3
html_notebook: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(tidy=FALSE, cache=TRUE,
dev="png", message=FALSE, error=FALS... |
2e1b8e801f092c40687ac5cae49e4a6788117cad0edf0aa8e3c0e2db5d0ea17a | R | 45,136 | 1,013 | #' banc-ids — Discover BANC neurons to process and rebuild `banc_ids.csv`.
#'
#' Pulls SeaTable `banc_meta`, joins to CAVE proofreading-notes / status /
#' nuclei tables, and rebuilds `<banc.meta.save.path>/banc_ids.csv`. This
#' CSV is the canonical "which neurons exist for this pipeline run"
#' inclusion-set consumed... |
c3d455f7779da3b0bac9d7ddb6bf481e38932370f88761a154e3ce83689cd4ea | R | 45,200 | 890 | # ==============================================================================
# Helper Functions for ICLE Analysis Pipeline
# ==============================================================================
# Description: Centralized utility functions, color schemes, themes, and helper
# functions used ac... |
b4dabc060b0c4a0df3baa46d1b43ef980d337eee1e9ddc18a804df4c7bf09d37 | R | 45,241 | 1,238 | ---
title: "Tutorial 04: Indirect Connectivity and Influence"
author: "Alexander Bates"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
toc_float: true
code_folding: show
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE, fig.width = 10, fig.heigh... |
30e79baaa3e13f9ad8363f662299f436f6b8952475c074c2129ba58880d5be7b | R | 45,323 | 1,354 | ---
title: "Gene Family Expansion: Expression Analysis"
author: "Simone Rencken"
date: "`r doc_date()`"
output:
BiocStyle::html_document:
toc: true
toc_float: true
toc_depth: 3
highlight: tango
code_folding: show
---
```{r setup, include=FALSE}
library(knitr)
options(bitmapType = "cairo")
options... |
3f3592b1a8d5d8d568d971ffcacfbbe805fd592b1e7f8b7540f979375d9fac24 | R | 45,575 | 1,238 | # KOLF2.1J-iTF paper
#csaw analysis
#https://github.com/reskejak/ATAC-seq/blob/master/csaw_workflow.R
# open R
srun -n 10 -p interactive --pty /bin/bash
module load cluster/gsl/1.15
module load cluster/htslib/1.9-devel
module load cluster/build_tools/llvm/8.0
module load cluster/util/gcc/8.2
module load hdf5_18/1.... |
87fc8e1d35f9465015425517efbe1e7db5fff66fbd4f84527cffeeb6f75e0232 | R | 45,912 | 1,323 | sample_store_standard <- function(data, par_names, iters = 1, stage = "init", integrate = T, is_nuisance, ...) {
subject_ids <- unique(data$subjects)
n_subjects <- length(subject_ids)
base_samples <- sample_store_base(data, par_names, iters, stage)
par_names <- par_names[!is_nuisance]
n_pars <- length(par_nam... |
b2b05ec05c22286f3c58b50b5717f31396f83a4f1f4df48580dffc337f668847 | R | 46,108 | 1,217 | ##########################################################################################
# ggplot2 Wrapper Methods For Easy Plotting
##########################################################################################
#' A ggplot-based dot plot wrapper function
#'
#' This function is a wrapper around ggplot ge... |
537c25360b4bed134114e6d211b29427013c9887500cd73234831171bde494b2 | R | 46,428 | 998 | ##################################
# 10x scRNA processing of NORLUX patient-derived neurospheres treated with Dasatinib, CP-673451, and DMSO
# Author: Kevin Johnson
# Date Updated: 2026.04.06
##################################
library(tidyverse) # 1.3.1
library(Seurat) # 4.3.0
library(Matrix) # 1.6-5
library(ggpubr) ... |
3222c65ca31d41a1aa2c4d9b790e91f551cadb791c24dae0e1a0b4ead59569a7 | R | 46,434 | 920 | library(Seurat)
library(Matrix)
library(dplyr)
library(ggplot2)
library(reshape2)
library(MAST)
library(cowplot)
library(harmony)
#/histor/sun/wangtao/3_software/anaconda3/envs/ScenicProtocol/bin/R
#/histor/sun/wangtao/3_software/anaconda3/envs/R4.0/bin/R
########################
setwd("/histor/sun/w... |
5d7e7de4b301309aa1c8802705ce904a55b7daea70a7cd14d9eb06c131a9bcb7 | R | 46,846 | 1,169 |
#-------------------------------------------------------------------------------
# Utility functions for analysis and plotting results
#-------------------------------------------------------------------------------
# SSDN
# Author: Kuldeep Kumar
#
#----------------------------------------------------------------... |
3d701f8e1b34a8163145b3e0e43c6fb5c357203abae0dacb66842bc9f4423a73 | R | 46,871 | 1,174 | # #' Plot Inhibition Functions
# #'
# #' Plots panels of the inhibition functions (probability of responding; Pr(R)) for each
# #' level of specified factors of stop-signal data as a function of user-defined
# #' SSD bins/categories. Optionally, posterior and/or prior predictive
# #' inhibition functions can be overlai... |
a30449ee95ed09fc5e36d79577ac644f4dcf64dc492f093936bc0e04ade8fd6e | R | 46,884 | 1,188 | ---
title: "Physical functioning and physical fitness in glioma patients"
author: "Marieke Blom"
date: '2024-01-05'
output: html_document
---
#### Email: m.e.c.blom@amsterdamumc.nl
#### Purpose of script:
Code analysis
#### Reviewed by Maxine Gorter
#### Notes
# Part 1 #
# 1.1 SF36 PF data: glioma... |
af28c1fca2894acbb0154401e253b723c8e63a1c73633f2e2d444f9523c24717 | R | 47,127 | 1,225 | #' @useDynLib conos
#' @import Matrix
#' @import igraph
#' @import sccore
#' @importFrom dplyr %>%
#' @importFrom magrittr %<>%
#' @importFrom magrittr %$%
#' @importFrom rlang .data
NULL
## for magrittr and dplyr functions below
if (getRversion() >= "2.15.1"){
utils::globalVariables(c(".", "x", "y"))
}
#' @keywor... |
c56a160f929f2543222c9f403930b06ff807def3126b5d110467a02f66805cb6 | R | 47,572 | 1,187 | # -------------------------------------------------------------------
# Extracellular Vesicle & Organoid Proteomics Pipeline (R)
# -------------------------------------------------------------------
# This script ingests raw quantitative proteomics data, merges them with
# sample‑level metadata, cleans and normalises t... |
27fe68ee4046f74255f50ccce902323953ab016678470c2b0c87c22e3d0cff12 | R | 47,741 | 1,170 | #' Visualize 5 or 3-primes on a genome
#'
#' @export
plot.genome.region <-
function(visfrom, visto, genome=NA, plot.data, gene.plotdata=NA, TR.merged.data=NA,
geom = geom_bar(), geom2 = NULL,
prime='prime5', crop.FALSE=F, samples=NA, comb.all.samples=NA,
sum.counts.in.window=T, bin_w... |
7c9be2c8aca73fdba38445fd68f52e2df9d19c54d893825c3f70241321dfe439 | R | 47,821 | 942 | ---
title: "bddPTC_analysis"
output:
html_document:
toc: true
toc_depth: 3
theme: united
date: "`r Sys.Date()`"
editor_options:
markdown:
wrap: 72
---
**bddPTC_analysis**
```{r read library, echo=F, warning=FALSE, message= FALSE, cache=TRUE}
knitr::opts_chunk$set(echo = FALSE)
``... |
20638d63e17420d6ef5a552aace9f8f38328e17376b64f9af8061a02a65db6f9 | R | 47,854 | 1,178 | robust_hist <- function(ps, breaks = 50, cutoff = 0.0015, do_plot = TRUE, prob = FALSE, ...){
ps <- ps[abs(ps) < 1000]
for(i in 1:log10(length(ps))){
cuts <- cut(ps, breaks = breaks)
tab_cuts <- table(cuts)
good_cuts <- tab_cuts/length(ps) > cutoff
ps <- ps[cuts %in% names(good_cuts)[good_cuts]]
}... |
50339ca14893d0da8194780fb7ec1ce9ae8d63621748625056b7e9bf70a6f2f4 | R | 47,954 | 1,139 | #' banc-vnc-sexually-dimorphic — Propagate sexually_dimorphic labels across BANC, MANC, FAFB, maleCNS.
#'
#' Cross-dataset propagation: if a cell_type is `dimorphic` in any dataset
#' and matches a cell_type in another dataset (direct or via bridge columns),
#' the label is propagated. Hard-codes a small set of SNch ty... |
690c58b055b912f40ef2e9550a16ba1fbbd11cbf48d28c462d5dd9999fd47670 | R | 48,286 | 964 | ##################################
# 10x scRNA processing of MGG152 and mouse macrophage co-culture irradiation experiments
# Author: Kevin Johnson
# Date Updated: 2026.04.05
##################################
library(tidyverse)
library(RColorBrewer)
library(viridis)
library(Seurat)
library(harmony)
library(Matrix)
li... |
86d02045e8937bffee5fee3e88930cb4c8e36d74e96b5a363543fe29f9abda69 | R | 48,941 | 1,209 | sample_store_SEM <- function(data, par_names, iters = 1, stage = "init", integrate = T, is_nuisance, ...) {
args <- list(...)
sem_settings <- args$sem_settings
if (is.null(sem_settings)) stop("sem_settings is required")
n_factors <- if (!is.null(sem_settings$Lambda_mat)) ncol(sem_settings$Lambda_mat) else 0
... |
2362ba497e8e5f5fd129648f7ceab6498f99ee03e60bc45598d136643e73b61a | R | 49,441 | 1,116 | # ==============================================================================
# Script 02: Fig 1, SupFig 2-4 - Molecular Subtyping, SET, and Fig 1B Sankey
# ==============================================================================
# Description: Runs the full Figure 1 pipeline via run_fig1_subtyping_and_figures... |
a40cacd42679b8efa449e6df4b27cb34de04669a904b631668c561bd114fae7b | R | 49,560 | 1,350 | ---
title: "DESeq2 RNA-seq Analysis"
author: " Pia Grundschoettel"
date: "17.04.2025"
output:
html_document:
toc: true
toc_float: true
---
# 1. R requirements
## 1.1 Install and load packages
### Install CRAN
```{r}
# CRAN packages
list.of.packages <- c("apeglm",
"factoextra",
... |
04e1c52ece9b8001a7a9bc240b82e2d2fc952f2758cd7124f3777129e4d59921 | R | 49,952 | 935 | ##############################################################################
###############--------------- SIMULATION STUDY ---------------###############
##############################################################################
### In this script:
# (1) Simulate data
# (2) Model fitting
# (3) Parameter recov... |
732c66ff42c08eb9b5ba48fa4b522ee3dfe529f829ef2d1b10e21ecc83dc3230 | R | 50,054 | 563 | #' Transcriptional regulators
#'
#' 7 important transcriptional regulators during early neural differentiation that are used as cores to assemble modules around them.
#'
#' @format A character vector of 7 elements.
"regulators"
#' All genes
#'
#' The 300 genes that are used for the network inference.
#'
#' @format A ... |
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