sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
90933117d049bcbe1d675c40fdb87ebc68a9c9ac66f171a362c5e25289bdfe85 | R | 50,118 | 1,073 | check_cave <- memoise::memoise(function(min_version=NULL) {
check_reticulate()
tryCatch(
cv <- reticulate::import("caveclient"),
error = function(e) {
plp=reticulate::py_list_packages()
plpc=plp[plp$package=='caveclient',]
errmsg <- if(nrow(plpc)==0)
paste(
"Please instal... |
8d8b307bc049156f2173d48cf726c84916f075f4b696f88964acdef7da83940b | R | 50,568 | 1,041 | ---
title: "MultiNicheNet analysis: SCC paired analysis - wrapper function"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
output_dir: "/Users/robinb/Work/multinichenetr/vignettes"
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: SCC paired ana... |
8042f25812de76a6953dfabbeef2e84d6e8459edfddc44e37429c343410833b2 | R | 51,477 | 934 | ---
title: "MultiNicheNet analysis: Workflow for condition-specific cell types"
author: "Robin Browaeys"
date: "2023-06-06"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: Workflow for condition-specific cell types}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UT... |
8adcb6e6a2af3a40e685ee1597d057350d44e4ff8982d52f8133acf1eb74e073 | R | 52,020 | 1,168 | plotPruningExample <- function(moduleOfInterest, initial_modules, consensus_network, n_iterations) {
# adjacency matrix
adjMat <- as_adjacency_matrix(consensus_network, attr = "weight")
# filter module data
initial <- initial_modules %>%
dplyr::filter(regulator == moduleOfInterest)
#pruning nr. 1... |
558776207f40c0e2a0a78390c027c13c7b23f2750bda3ec98b253a21359cfdd1 | R | 52,106 | 1,259 | #' @export
print.emc <- function(x, ...){
n_chain <- chain_n(x)
cat("Iterations: \n")
print(chain_n(x))
sub_names <- names(x[[1]]$data)
cat("\n")
cat("Subjects: \n")
print(sub_names)
par_names <- x[[1]]$par_names
cat("\n")
cat("Parameters: \n")
print(par_names)
return(invisible(list(iterations =... |
a11aa8eaf7c1df5fb3fbd80d29d23f7b47e6c7c58d9366d7fd60151426cb6d4b | R | 52,245 | 1,304 | apply_contrasts <- function(events, contrast = NULL, cell_coding = FALSE, remove_intercept = TRUE, levels = NULL) {
factor_name <- events$factor[1]
colnames(events)[colnames(events) == "event_type"] <- factor_name
# If a contrast is provided, use it; otherwise let R default to its default contrasts.
if(!is.nul... |
e444920bed4aad370e0c89936a23dd383cd7d7b4f02715805b775c0f9a40a825 | R | 52,539 | 856 | library(tidyverse)
library(methylclock)
library(survival)
library(survminer)
library(ggpmisc)
library(viridis)
library(ggrepel)
library(ggplot2)
library(dplyr)
library(ggpubr)
library(ggh4x)
library(ggsci)
raw <- read_rds("./input/fhs/epigenomics.rds")
clocks <- DNAmAge(raw, clocks = c("Horvath", "Hannum", "Levine"),... |
6d2471f344100a97b32814d595efcaf11d4a054c522ae6eba68f3f45973a0fff | R | 53,183 | 1,100 | ---
title: "MultiNicheNet analysis: include additional data modalities: serum proteomics in MIS-C"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
output_dir: "/Users/robinb/Work/multinichenetr/vignettes"
vignette: >
%\VignetteIndexEntry{MultiNicheNet a... |
3bc33b9bf99fd170bd64cbc4dae1e5fbf906bacefbfa2e159831398c9e4c739a | R | 53,430 | 1,306 | #
# 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... |
e3239da41da5796fff3f52b33c84e96aa2571e6a56e96f69c4cde2273716b337 | R | 53,716 | 1,461 | ##########################################################################################
# LSI Dimensionality Reduction Methods
##########################################################################################
#' Add an Iterative LSI-based dimensionality reduction to an ArchRProject
#'
#' This function wil... |
b442a01795f5c56bece888bf7d46cdca53a18ebbc9c49c3b5ca7fbaba2235ea3 | R | 54,356 | 828 | ## This file will be used to store common functions that are useful in scRNA-seq anlysis.
## Quote, Unquote and Quasiquote: https://masterr.org/r/quote-n-quasiquote/
## Quasiquotation: https://adv-r.hadley.nz/quasiquotation.html
## Non-standard evaluation: http://adv-r.had.co.nz/Computing-on-the-language.html
## ht... |
ed8f3cffe87d3b98ee21fe270326a7811a56113e856613ce9274024e900d85a0 | R | 54,453 | 1,314 | memo_sqlite_con <- memoise::memoise( function(db, flags=RSQLite::SQLITE_RO, ...) {
con <- RSQLite::dbConnect(RSQLite::SQLite(), db, flags=flags, ...)
con
})
memo_tbl <- memoise::memoise(function(db, table) {
check_package_available('RSQLite')
check_package_available('dbplyr')
if(is.null(db))
return(NULL)... |
aac103658d8cb8fe38679340a230178d29f0937a15f5e623907b95bd61f8790c | R | 54,763 | 1,535 | ##########################################################################################
# Marker Feature Methods
##########################################################################################
#' @export
markerFeatures <- function(...){
.Deprecated("getMarkerFeatures")
getMarkerFeatures(...)
}
#... |
bf61a67f5d512ed1dac40c6dda58c94e2f6a90b95be68d6aabda8fe200c65a8b | R | 55,070 | 1,411 | ---
title: "PAL simulation-based calibration"
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 = 'center', fig.w... |
41d5f4d7903065cbda28d11beda82111f246c1250c525fd503397b9086810e70 | R | 56,047 | 1,352 | #' Summarise edits for one or more FlyWire segment ids
#'
#' @details When \code{filtered=TRUE} the following are removed \itemize{
#'
#' \item edits that are outside of the given root id - meaning these edits are
#' in the history of the cell but the affected part of the arbour was since
#' cut off.
#'
#' \ite... |
bb1990b5321f691475d64629f2981e903b735f1cfca5570f08104955c21671b0 | R | 56,583 | 1,340 | setwd('~/d/sci/src/prp_mrm')
options(stringsAsFactors=FALSE)
library(sqldf)
library(reshape2)
library(minpack.lm)
library(beeswarm)
percent = function(proportion,digits=2,format='fg') {
return ( gsub(' ','',paste(formatC(proportion*100, digits=digits, format=format),"%",sep="") ) )
}
alpha = function(rgb_hexcolor, ... |
09c36b2c8866c85edfa29718ad57c2cfa3613df925104358dd762b3937fd98de | R | 57,737 | 1,027 | #' @title get_muscat_exprs_frac
#'
#' @description \code{get_muscat_exprs_frac} Calculate sample- and group-average of fraction of cells in a cell type expressing a gene.
#' @usage get_muscat_exprs_frac(sce, sample_id, celltype_id, group_id)
#'
#' @inheritParams multi_nichenet_analysis
#'
#' @return List with two dataf... |
e8e95a731934fd9fcc7c2d89882c78592f313c91c0abb67d9518e2d24b3daf41 | R | 57,775 | 1,597 | setSparseSigma = function(sparseSigmaFile) {
Check_File_Exist(sparseSigmaFile, "sparseSigmaFile")
sparseSigma = Matrix:::readMM(sparseSigmaFile)
locations = rbind(sparseSigma@i, sparseSigma@j)
values = sparseSigma@x
nSubj = dim(sparseSigma)[1]
sigmaMatListR = list(locations = locations,
... |
875822d3130e5675b5ca6658551ef51f041d7a371ad4d0e4a4d577fd611948a2 | R | 57,835 | 1,491 | ####################################################################
# Trajectory Analysis Methods
####################################################################
#' Add a Supervised Trajectory to an ArchR Project
#'
#' This function will fit a supervised trajectory in a lower dimensional space that
#' can then... |
693be40b722d6e3ac5231a12ff6c6c068e0ad3fb9697d1fd5c5f22b84788ae90 | R | 57,881 | 1,586 | ##########################################################################################
# Annotation Methods
##########################################################################################
#' Get peakAnnotation from an ArchRProject
#'
#' This function gets a peakAnnotation from a given ArchRProject.
#' ... |
5a296fdadaccd92539ca867a72ec67d5a00f8a98b56a935544384aba55e8f54f | R | 58,368 | 1,316 | ##############################################
### Integrate BANC meta data with seatable ###
##############################################
source("banc/banc-startup.R")
message("##### Building seatable meta data #####")
# Update BANC meta seatable
bancr:::banctable_updateids()
# Save snapshot
bc.orig <- banctable_q... |
c98e7f89c856c0fe1e16da9936e587cd300a7960433fb47913426b0513fde701 | R | 58,481 | 1,660 | ---
title: "Tutorial 03: Connectivity Analyses"
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.height =... |
36add748d2eb7a136f10e235619411b73c84e78a9d0ee2a77236ce19395f4c8d | R | 59,204 | 1,274 | ---
title: "MultiNicheNet analysis: Integrated lung atlas analysis - correct for batch effects to infer differences between IPF and healthy subjects"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
output_dir: "/Users/robinb/Work/multinichenetr/vignettes"... |
ffdeb12147fb6872355720c1bf24617fe15f55cffb1fbdb89a08f14659dcbe53 | R | 59,289 | 1,485 | #' author: Gavin Ha
#' Dana-Farber Cancer Institute
#' Broad Institute
#' contact: <gavinha@gmail.com> or <gavinha@broadinstitute.org>
#' date: June 26, 2018
loadDefaultParameters <- function(copyNumber = 5, numberClonalClusters = 1,
skew = 0, hetBaselineSkew = NULL, alleleEmissionModel = "binomial", symmet... |
98c2a7b4763f10150cfbdc25a3d13c8ed3df53f32da324d37e7d538d80aa7fc9 | R | 59,323 | 1,235 | #' banc-calculate-completion — Synapse-capture rates across v1, v2, v3 detection rounds.
#'
#' Classifies each synapse's pre/post as proofread / identified / fragment
#' and emits per-source capture-rate CSVs + a 3-way comparison.
#'
#' @section Reads:
#' - GCS v1/v2/v3 synapse parquets, `banc_<ver>_synapses_v3.parqu... |
4d32a5c90b77e73345115954074a876be3d1170912c4f856bca18debc2d04e6d | R | 59,701 | 1,396 | ---
title: "DESEQ CP circadian data"
output: html_document
date: "2023-02-22"
editor_options:
chunk_output_type: console
---
#Analysis of RNAseq data from sleep/circadian choroid plexus
###There are several different ways to analyze this data as there are 3 conditions, awake, asleep and sleep disrupted. Previous an... |
2687443f130c35cc68c865795cf3bedd8faadd77804c62857c99dbcf62feb215 | R | 60,299 | 948 | ################################### PACKAGES, HELPER FUNCTIONS, LIST OF TRAITS ###################################
library(ggplot2)
library(ggrepel)
library(readxl)
library(googlesheets4)
library(stringr)
library(latex2exp)
library(Cairo)
library(ggtext)
library(stringi)
library(patchwork)
library(reshape2)
library(mlt... |
50ac5fa7dbe3f2528cd7e47b8f72e581f96f3a76b8c299d0a77bf2a606bed8a8 | R | 60,353 | 1,522 | library(Seurat)
library(Matrix)
library(dplyr)
library(ggplot2)
library(reshape2)
library(cowplot)
library(fields)
library(KernSmooth)
library(ROCR)
library(parallel)
library(DoubletFinder)
#/histor/sun/wangtao/3_software/anaconda3/envs/ScenicProtocol/bin/R
########################
setwd("/histor/sun/w... |
5ca276797e8e8db921683141ec04d73abe569e486eec974eadded3f627838874 | R | 60,832 | 1,325 | #' banc-frankenbrain — Build the franken-brain meta CSV (FAFB + MANC merge).
#'
#' Merges FlyWire (FAFB) and MANC metadata into a single cross-dataset
#' "franken" metadata table, using BANC-mediated cell_type bridges where
#' available. The output is the canonical reference loaded everywhere via
#' `franken_meta()`.
#... |
3a542840011b34e052b54c65e823d6305065b6e7d2aefe5dbbbb2ad93935cbf3 | R | 61,050 | 1,614 | #' Specify a Design and Model
#'
#' This function combines information regarding the data, type of model, and
#' the model specification.
#'
#' @param formula A list. Contains the design formulae in the
#' format `list(y ~ x, a ~ z)`.
#' @param factors A named list containing all the factor variables that span
#' the d... |
de4c2022b91c88a1a265e926c692d9f587fdb99227f8d49f7a889cacbbf02e02 | R | 62,070 | 1,866 | # AD risk variants annotation
# 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
# Load libraries
library(... |
836ca9b0e172142ef57c0c91e5fb554abb426fb5ec6603ec6bbb25980479090e | R | 62,454 | 1,109 | #' @import ggrepel
#' @import gridExtra
#' @import leidenAlg
#' @import R6
#' @import Rtsne
NULL
## exporting to inherit parameters below, leiden.community
#' @export
leidenAlg::leiden.community
#' @title Conos R6 class
#' @description The class encompasses sample collections, providing methods for calculating and v... |
30afb5b5481fb3f9db9bb10c4490584e77bc0e45526af403e6f9d07a35c308a4 | R | 63,016 | 1,569 | title: "R Analysis of Spine/Astrocyte data by Dr Francesco Gobbo (original code input by Tara Spires-Jones" output: html_notebook ---
Load libraries
```{r}
library(readr)
library(plyr)
library(forcats)
library(lme4)
library(ggplot2)
library(stargazer)
library(lmerTest)
library(rcompanion)
library(dplyr... |
95bccb4d1f8079e606fa15a5ad2a69e0e906ebddd7ed6d1df76ce154b1859fbb | R | 63,341 | 1,351 | #' banc-data — Assemble the versioned BANC release: meta, metrics, synapses, edgelists.
#'
#' @section Reads:
#' - `banc_<ver>_synapses_<src>.parquet`, `banc_<ver>_edgelist_simple_<src>.feather`
#' - `banc_metrics.feather`, NT-prediction feathers, per-neuron split CSVs
#' - SeaTable `banc_meta`
#'
#' @section Wri... |
20e797a75bded3687632bd4fbb8936111fc415039e8057ce25208d90ccba48c4 | R | 63,903 | 1,594 | # Script to compare target genes in iTF cells
# 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
library(G... |
5df44f098609c5fb08d66ec9b5ef8cdf29b2a70f4f20d2f0787052a418a53615 | R | 65,618 | 1,164 | #' @title multi_nichenet_analysis
#'
#' @description \code{multi_nichenet_analysis} Perform a MultiNicheNet analysis in an all-vs-all setting.
#' @usage multi_nichenet_analysis(
#' sce, celltype_id, sample_id,group_id, batches, covariates, lr_network,ligand_target_matrix,contrasts_oi,contrast_tbl, senders_oi = NULL,re... |
fb2eafdcded0274d169129ec764cf161b9fb9680fcdf3581316651538ec76914 | R | 67,045 | 2,080 | #' @import shiny
#' @import SingleCellExperiment
#' @import ggplot2
#' @import grid
#' @import paletteer
#' @importFrom cowplot plot_grid
#' @importFrom viridisLite viridis
#' @importFrom sessioninfo session_info
#' @rawNamespace import(plotly, except = last_plot)
#' @importFrom grDevices as.raster pdf dev.off
#' @impo... |
1ea79acfae17e45f27a12dd22f47a214e82fecc0b98b695e85642341524f42b7 | R | 67,908 | 811 | #' @title generate_prioritization_tables_condition_specific_celltypes_sender
#'
#' @description \code{generate_prioritization_tables_condition_specific_celltypes_sender} Perform the MultiNicheNet prioritization of cell-cell interactions. Focus on including condition-specific cell types as sender cells. This implies no... |
a55a39f27a529144138a40ab37a0800911021b7d5f6206df53af9b60f84f7adf | R | 68,138 | 1,180 | library(bhr)
source("correct_winners_curse.R")
library(pracma)
########################################BHR basic estimates (h2, intercept) #############################
path = "/Users/daniel/Desktop/rare_h2/ms/genebass_summary_statistics_null/"
phenotype_file <- read.csv("~/rv_h2/reference_files/ms_phenotype_sheet.cs... |
75674ed0fdc6a2d14612f732543c30063434fc9ee32a738b7c3864da82ae4b7b | R | 68,779 | 2,141 | library(dplyr)
library(tidyr)
library(cluster)
library(ggrepel)
library(FactoMineR)
library(ggplot2) # Only if you want to use ggplot for visualization
library(factoextra) # Load factoextra package
library(ggforce) # For drawing circular shape
library(psych)
library(plotly)
library(purrr) # Load the purrr package
l... |
a2ec4a5d7e35e7b39047e4890863cb5d5d94343edd4a2d91795dc36aeb790cd7 | R | 68,901 | 2,253 | #' @title Regional plot
#'
#' @description `fig_region` creates a regional plot, i.e. a scatter graph of
#' genomic markers associations (e.g. log10(p-values)) with a gene bar
#' underneath.
#'
#' @name fig_region
#'
#' @import dplyr
#'
#' @import tidyr
#'
#' @import ggplot2
#'
#' @import ggiraph
#'
#' @import ggre... |
9dd2ba89ff6fd5a54d33c7553f62c0913ae15ef283b9c91f40d1f01a80eaa7cd | R | 69,267 | 1,720 | check_seatable<- memoise::memoise(function(min_version=NULL) {
check_reticulate()
tryCatch(
st <- reticulate::import("seatable_api"),
error = function(e) {
if(interactive()) {
chc=readline("Install the seatable_api python package for flytable access (y/n)? ")
if(tolower(chc)=='y') {
... |
ca5f632f066d6ab3ac0f9361ce9e78885b0f7f9647aea2db6d5485476bd7a7da | R | 69,393 | 1,613 | ---
title: "getting_module_scores"
output: html_document
date: "2024-05-07"
author:
- name: Vladyslav Storozhuk
---
# 1. Processing peaks with scores
```{r}
random_modules_in_extended_format <- readRDS("/data/share/htp/hack_GRN/NPC_diff_network_analysis/07.module_assignment/randomModules/initial4000_min20_ext.rds")... |
06a0405190a6c6cd86e26c8f394172f5181b652b0f9d0c933eeb552045883354 | R | 70,545 | 1,667 | # load packages
library(patchwork)
library(Seurat)
library(rhdf5)
library(DropletUtils)
library(DropletQC)
library(dplyr)
library(Matrix)
library(ggplot2)
library(plyr)
library(tidyverse)
library(tidyr)
library(ggpubr)
library(reshape2)
library(rio)
library(data.table)
library(harmony)
library(ggrepel)
library(edgeR)
l... |
d0c9b580984e1ea612a150e87471934cacb2de52eb73d614200d236163448cf1 | R | 71,690 | 1,747 | ##########################################################################################
# Assay Correlation Methods
##########################################################################################
#' Correlate Matrices within an ArchRProject
#'
#' This function will correlate 2 matrices within an ArchRPr... |
4a94ae2e14bf039a5bb60a91793882456a862b7f05a4eb214e9bc97b936d2ad6 | R | 72,710 | 1,532 | ---
title: "Analysis Report of EPS effect on NMO transcriptome using bulk RNA-seq"
output:
html_document:
theme: journal
toc: true
toc_float:
collapsed: false
smooth_scroll: false
date: "2025-10-16"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE,warning = F,message = F)
`... |
72fce5042130ddd1bf6651413b351ef278e64c1d8b7c6a2372398dbdd62ff8db | R | 73,813 | 1,241 | #' @import shiny
#' @importFrom shinyWidgets pickerInput pickerOptions updatePickerInput
#' @import SingleCellExperiment
#' @importFrom DT DTOutput
#' @importFrom SummarizedExperiment assays
app_ui <- function() {
## Get options
spe <- golem::get_golem_options("spe")
docs_path <- golem::get_golem_options("d... |
e71214062bf9587dbfcae3b3c6a1f7980da62db9886995528cd11d330ab445b4 | R | 74,050 | 1,641 | ---
title: "MultiNicheNet analysis: aPD1 treatment response breast cancer - multifactorial design - sample-agnostic/cell-level alternative"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: aPD1 tre... |
ac30dd4906e6588851d0dd6f423253c54c5ceac466475b5ef38537f429862092 | R | 74,412 | 1,396 | ---
title: "MultiNicheNet analysis: MIS-C threewise comparison - step-by-step"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
output_dir: "/Users/robinb/Work/multinichenetr/vignettes"
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: MIS-C three... |
66b01c820c738240d4b99c2241bd008488832cc2f7fb4b3b0aba1b6f78a472cc | R | 76,193 | 1,733 | #' banc-dimorphic-density — Density plots of sexually dimorphic presynapses (combined VNC + brain).
#'
#' VNC: JRCVNC2018U space for BANC, maleCNS, MANC. Brain: JRC2018U for
#' BANC, FAFB, maleCNS. Reads the `sexually_dimorphic` column from each
#' dataset (set by `banc-vnc-sexually-dimorphic.R`) and produces faceted
#... |
09d35aef481640a9bf520fe03d0cc2ea9bdb46ce7c1adcf269ba542c9cc7f72b | R | 76,958 | 1,677 | monsterAnalysis <- setClass("monsterAnalysis", slots=c("tm","nullTM","numGenes","numSamples", "logging"))
setMethod("show","monsterAnalysis",function(object){monsterPrintMonsterAnalysis(object)})
#' monsterGetTm
#'
#' acessor for the transition matrix in MONSTER object
#'
#' @param x an object of class "monsterAnalysi... |
6bf2fdc11336fc7e4264580a755c8c2ab65df50f995dfda0f5b4502c880f60c8 | R | 77,875 | 1,270 | #' @title get_abundance_info
#'
#' @description \code{get_abundance_info} Visualize cell type abundances.
#' @usage get_abundance_info(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, batches = NA)
#'
#' @inheritParams multi_nichenet_analysis
#' @inheritParams combine_sender_receiver_inf... |
6b0b26ac6c0b8942f4c7eb8a037ecdc6e0cc8737a4325132947e5bc74a986448 | R | 79,734 | 2,286 | ---
title: "Ambra Villani's microglia RNA-seq"
author: "Izaskun Mallona, Mark D. Robinson's lab, UZH"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
toc: true
toc_float: true
code_folding: hide
code_download: true
number_sections: true
df_print: kable
theme: lumen
param... |
70da773cfa582b2c72ebf2722c5e34e532dba1d8a9d7bb088312617976fe8889 | R | 80,561 | 1,741 | ---
title: "MultiNicheNet analysis: anti-PD1 Breast cancer multifactorial comparison"
author: "Robin Browaeys"
package: "`r BiocStyle::pkg_ver('multinichenetr')`"
output:
BiocStyle::html_document
output_dir: "/Users/robinb/Work/multinichenetr/vignettes"
vignette: >
%\VignetteIndexEntry{MultiNicheNet analysis: anti... |
49e581edf0f4408563fb8c98016912c993641a82b229fcc1ae5acc9dc5d2502f | R | 80,562 | 2,141 | ####################################################################
# Signal Track Plotting Methods
####################################################################
#' Launch ArchR Genome Browser
#'
#' This function will open an interactive shiny session in style of a browser track. It allows for normalization o... |
52724d6c74e935b03930c844ecada22c0a3298ca5ad666ffc7f1940bac0538cf | R | 81,551 | 1,994 | create_group_key <- function(df, factors) {
if (length(factors) == 0) return(rep("All Data", nrow(df)))
key <- apply(df[, factors, drop = FALSE], 1, function(x)
paste(paste(factors, x, sep = "="), collapse = " "))
levs <- lapply(df[,factors],levels)
for (i in 1:length(factors)) levs[[i]] <- paste(factors[i]... |
f234cb8383357fc9772804785e95cbd1b6b96e4b8caa571ae981012d1b7dded8 | R | 82,045 | 2,032 | ---
title: "RESTORE NPCRA & Light Analysis"
author: "Emily Stanyer"
date: "`r Sys.Date()`"
output:
html_document:
theme: lumen
toc: true
toc_float: true
toc_depth: 2
code_folding: hide
---
This code calculates standard non-parametric circadian rest-activity (NPCRA) and light exposure metrics u... |
ef273156c98d8f1d2928a59863dee9c74f5590f806d2f868f66bc77399c13b60 | R | 82,398 | 879 | scale_quantile_adapted = function(x, outlier_cutoff = 0){
y = nichenetr::scale_quantile(x,outlier_cutoff = outlier_cutoff)
y = y + 0.001
return(y)
}
#' @title generate_prioritization_tables
#'
#' @description \code{generate_prioritization_tables} Perform the MultiNicheNet prioritization of cell-cell interaction... |
85521b22907fc127aedc92be370639ad434b819919547c3e52658daf1f307b38 | R | 83,486 | 2,383 | ---
title: "Memory_Encoding_Analysis"
author: "Michael Colwell"
date: "2024-04-05"
output: html_document
---
#Memory encoding task (or 'Hippocampal task') behavioural and neuroimaging data preprocessing analysis scripts for the PEACE Study ('Pitolisant Effects on Affect and Cognition Exploratory Study') (NCT05849... |
bdd6e634bbf73d99d111c0dd4e37816a748139f064e2c13e63b3b518afbe1cf9 | R | 83,952 | 2,075 | #' Create a trend specification for model parameters
#'
#' @param par_names Character vector specifying which parameters to apply trend to
#' @param cov_names Character vector specifying which covariates to use for each trend
#' @param kernels Character vector specifying which kernel function to use for each trend
#' @... |
8238a9fa0f7fd51392cc8f45f9c1bcef8fe165e5ce0d0b328304b80f9bf11cd2 | R | 83,977 | 2,106 | #
# 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... |
d3cbb1930f6fdce30b1437ac71f8a072e3e4084c0ad5e42dd4c1fa5d9896291c | R | 84,324 | 1,602 | #' banc-nblast-compile — Consolidate per-query NBLAST CSVs into per-dataset feathers.
#'
#' Updates compiled feathers from reviewed CSVs + scanned PNG review
#' folders. Run AFTER `banc-nblast-wrong-matches.R`.
#'
#' @section Reads:
#' - per-query NBLAST CSVs, reviewed CSVs, PNG review folders, existing feathers
#'
#... |
0ced56353b2526dc83f37ff411b74f3c6b065175297195295233c37f8cfc01cf | R | 85,789 | 1,745 | library(readxl)
library(dplyr)
library(ComplexHeatmap)
library(circlize)
library(tidyr)
library(ggplot2)
library(cowplot)
library(lmtest)
library(broom)
library(outliers)
library(stringi)
library(plotrix)
library(ggforce)
library(FSA)
library(ggpubr)
#
#Synapses
#
exp_names <- list.files("AtlasV8 Sp... |
d81f5fa27d962591f1779d8cec3027ca59073ce61a82d6f8a3d9396e3fa9b66e | R | 87,095 | 1,837 | # ==============================================================================
# Script 22: Fig 4 & SupFig 11 - DNA Methylation Alterations (DMI, ILC vs NST)
# ==============================================================================
# Description: Analyzes DNA methylation instability (DMI) and generates
# ... |
49160b2fe1bb5e916e825e6b0200ddea22ef451dc647a0f74dde5a88650f1c94 | R | 88,655 | 1,189 | ---
title: "CroCoNet"
output: rmarkdown::html_vignette
bibliography: references.bib
csl: bmc-biology.csl
vignette: >
%\VignetteIndexEntry{CroCoNet}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
editor_options:
chunk_output_type: console
---
<style>
img {
border: 0;
}
p.caption {
font-size: ... |
7c02885ba974038cd8eb1142323b666465d36742f400cd1cf2a7c204945d5129 | R | 88,914 | 2,308 | ##### PREREQUISITES #####
rm(list=ls())
library(tidyverse)
library(ggpubr)
library(phangorn)
library(MCMCglmm)
library(phytools)
library(bbmle)
library(MuMIn)
library(plotly)
library(ggbeeswarm)
library(wesanderson)
library(ggResidpanel)
library(emmeans)
##### #SEX DIFFERENCES (FIGURE S1) #####
se... |
8ee0f1165386559ecaaf829ebd5d544633d32a3927bb51feb3272667b71766f3 | R | 89,950 | 1,423 | #' Plot expression profiles as a heatmap
#'
#' Plots the expression profiles of one or more genes as a heatmap, with the cells ordered by pseudotime or cell type.
#'
#' The function creates a heatmap, with columns corresponding to cells, rows corresponding to genes and colors corresponding to scaled and centered expres... |
f798879526c05a0ec2325669e7dd681a31027149b86b5284149d3f250b039312 | R | 90,155 | 2,371 | #' Create Arrow Files
#'
#' This function will create ArrowFiles from input files. These ArrowFiles are the main constituent for downstream analysis in ArchR.
#'
#' @param inputFiles A character vector containing the paths to the input files to use to generate the ArrowFiles.
#' These files can be in one of the follo... |
409b195cd48e42d955acb7570a917863c1b5e9e53c64da81f960749309f61ff7 | R | 91,759 | 2,402 | [file name]: UMAPHarmony_10samples_ArchR.R
[file content begin]
library(ArchR)
library(ggplot2)
library(Seurat)
addArchRThreads(threads = 16)
addArchRGenome("mm10")
#/histor/sun/wangtao/3_software/anaconda3/envs/R4.0/bin/R
setwd("/histor/sun/wangtao/0_user/3_shixh/singlecell/choline/ATAC/data/d2c/UMAPHarmony_10cholin... |
7fc367bc970be8d462ebca145aeb1f03c3160b0da4567942077a641456cde1ba | R | 91,977 | 2,075 | #' Run SEAHORSE in R
#' Author(s): Enakshi Saha
#' Description:
#' SEAHORSE computes gene-gene coexpression matrix,
#' associations between a set of given phenotypes and each gene,
#' performs gene set enrichment analysis (GSEA) for each phenotype,
#' using the me... |
54293744b1907482f57f9ad2df02012fbce4761ddef97e9efe033a415ed1059d | R | 93,240 | 2,501 | #library(caTools)
#dyn.load("src/bed2vector.so");
#dyn.load("src/wdl.so");
#dyn.load("src/peaks.so");
#dyn.load("src/cdensum.so");
# -------- ROUTINES FOR READING IN THE DATA FILES ------------
# fix.chromosome.names : remove ".fa" suffix from match sequence names
read.eland.tags <- function(filename,read.tag.names=F... |
fafc91b7ee50f484489f21b7f0ae4db52ef2c3d0b9e1a27b64666589831c8ac4 | R | 93,294 | 1,889 | ###########################################
### Compile NBLAST from various sources ###
###########################################
source("banc/banc-startup.R")
message("##### Building BANC NBLAST data files #####")
version <- "elastix_tpsreg_240721"
# Register cores
cl <- setup_parallel()
##########################... |
e1a1fd8793456e17f9f5feeb73001d94a0366aa2e71d4e2e5a8ba25cd4f64c54 | R | 93,321 | 2,097 | #' banc-vnc-type-changes — Detect VNC cell_type changes vs the new VNC typology.
#'
#' Two parts: (A) VNC intrinsic neurons — joins
#' `banc_vnc_cell_type_and_dimorphism.csv` to SeaTable on `root_626` to
#' detect cell_type / hemilineage changes and dimorphism assignments;
#' (B) Effector neurons — joins `banc_to_manc_... |
c7a6e6fccc3d2250c6cfda7c5af9343cf25a3d4aa1f71318fde301e17b13aa36 | R | 93,511 | 2,281 | 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(DropletQC)
library(xlsx)
library(biomaRt)
library(ggbreak)
source('~/SCRIPTS/uti... |
ee7194b37bb414c1f3d662304d99f9078f207b7dab35279a4a36e9af0c55f0d6 | R | 94,445 | 1,923 | library(readxl)
library(dplyr)
library(ComplexHeatmap)
library(circlize)
library(tidyr)
library(ggplot2)
library(cowplot)
library(lmtest)
library(broom)
library(outliers)
library(stringi)
library(plotrix)
library(ggforce)
library(FSA)
library(writexl)
#
#Synapses
#
exp_names <- list.files("AtlasV8... |
a8688eedf691843f64bb23d218ace0feea1011803500372f315b5b9faaf2c899 | R | 94,593 | 1,507 | context("test SEAHORSE result")
test_that("seahorse function works", {
skip_if_not_installed("fgsea")
skip_if_not_installed("matrixTests")
skip_if_not_installed("stats")
skip_if_not_installed("limma")
set.seed(42)
# Simulate expression data
expression_data = data.frame(matrix(rexp(1000, rate=.1), ncol=10... |
cae445f67ca8f638693deb6f1108984d2f06f4bf994f5636494d5a2fd2dcee93 | R | 95,804 | 2,854 | # Load required libraries
library(readr)
library(readxl)
library(sf)
library(dplyr)
library(tidyr)
library(ggplot2)
library(MASS) # For kde2d function
library(igraph)
library(RColorBrewer)
# Set working directory
setwd("C:/Users/huynhk4/Documents/")
#---------------------------------------------
#cell_type=c("Fibro... |
dad8c2010eca68b1c95a8c3f4379e77d9b6c8898f4c1841fa116902f5dc5e9d0 | R | 95,938 | 1,654 | ###################################################################################################################################
## One-Step GSA FET (R piano implementation) WITH USER PARAMETERS
## - by Eric Dammer, Divya Nandakumar
## Nicholas Seyfried Lab Bioinformatics - for the lab -
## 01/07/2026 version 1.4... |
fbab51e6ee42082c0d4760d67d363099b1a03c0fec632f8a57798fbcc9847bfc | R | 96,221 | 2,318 | #' banc-plot — Diagnostic plots for cross-dataset matching + NT predictions.
#'
#' Density / beeswarm / heatmap diagnostics for cross-dataset matching and
#' neurotransmitter prediction sanity checks. Manual exploration script.
#'
#' @section Reads:
#' - `<banc.meta.save.path>/{flywire,manc,fanc}_meta.csv`
#' - Sea... |
4de951f7748559de6bed438c6b30252d33ee77d8bdaa852d775d9b6043ccb02f | R | 96,922 | 3,182 | # modified by pliu
#
# revised on 2-20-10
# - fix error in pass.structure: reverse rank.combined, so that big sig.value
# are ranked with small numbers (1, 2, ...)
# - fix error on get.ez.tt.all: get ez.cutoff from sorted e.z
#
# modified EM procedure to compute empirical CDF more precisely - 09/2009
# this file c... |
313388f1955bf16bae2924e2962143feea472b4bef12ed98e0082be0b8b90e05 | R | 97,648 | 2,175 | #' banc-functions — Shared helper functions for the BANC pipeline.
#'
#' Sourced by `banc/banc-startup.R`. Defines the per-script helpers used
#' across the pipeline: neuron filtering (`filter_valid_neurons`), SeaTable
#' I/O wrappers + retries, status-column append helpers, side-index and
#' laterality helpers, plot p... |
db302b285fff8a230e55dfb8274b43c119770871c6a8f51bd1a0002322eb647e | R | 98,357 | 2,276 | ---
title: "ABCD Sleep Paper MI First"
author: "Emma Devine"
date: "2024-04-21"
output: html_document
---
# Data Management & Set-up
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE) #this line of code is ensuring the code as well as output is being included in the R Markdown html file when rende... |
e576e0ed9ce2167d8db53d0a7b8b1da5d793115630c2331fbbe1d5eed5c0ae39 | R | 98,701 | 1,810 | #############################
### GET MALECNS META DATA ###
#############################
source("banc/banc-startup.R")
library(malecns)
# Franken meta authority
franken.meta <- franken_meta() %>%
dplyr::distinct(neuron_id, .keep_all = TRUE) %>%
dplyr::select(neuron_id,
side,
region... |
d84b9dde7b644646434e78f629d72b78f2b5156d40e1d14b6ed27d0b9af156e1 | R | 100,897 | 2,986 | # Load required libraries
library(readr)
library(readxl)
library(sf)
library(dplyr)
library(tidyr)
library(ggplot2)
library(MASS) # For kde2d function
library(igraph)
library(RColorBrewer)
# Set working directory
setwd("C:/Users/huynhk4/Documents/")
#---------------------------------------------
#cell_type=c("Fibro... |
141cf959346f19746dd12850053c44a72bbf82df4f57ddd33ed2f4dc639478be | R | 109,600 | 2,003 | #' franken-annotations-fix — Standardise franken-brain annotations against published labels.
#'
#' Diff `franken_meta()` cell_types against the published FAFB Supplemental
#' table and apply targeted corrections to the franken-brain CSV (column
#' harmonisation, dataset-specific fix blocks).
#'
#' @section Reads:
#' ... |
f2317d0210966fc00ee913764cefd67d6cdfe5d27f576241467073136a669fb8 | R | 116,724 | 2,957 | GetIndexofCases = function(status, time){
timedata = data.frame(time=time, orgIndex=seq(1,length(time)), status=status)
timedata = timedata[order(timedata$time),]
timedata$newIndex = seq(1,length(time))
caseIndex = which(timedata$status == 1)
caseIndexwithTies = caseIndex
for(i in 2:length(caseIndex)){
... |
0aeb3ad533802452a4086aa2460424653ff984dc72a31b4098121ac607236b12 | R | 132,072 | 3,769 | ####read me####
#Code for drosophila activity monitor analysis, modified for R from python scripts from Vaughen et al 2022
#Reads .txt activity monitor files saved in subfolders for different GAL4 drivers depleting Pex5. Experiments were done in LD except for DD run of cortex glia (GMR77A03)
#Code outputs similar graph... |
f134556d38b503add19ec4f2bfd6e782a966a9763d3d768fcf49d77c230c1d55 | R | 141,727 | 5,096 | ---
title: "gmb_mel_tma_wta"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{gmb_mel_tma_wta}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
# Setup
```{r setup, include = FALSE}
# cran packages
library(ppcor)
library(tidyverse)
library(readxl)
library(writexl)
library(factoe... |
b74e5e2b0bf1941a5dcf9608dd6f86dcc67537ddc9f995624e65f3ad4b9a968c | R | 141,866 | 1,586 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<link rel="dns-prefetch" href="https://github.githubassets.com">
<link rel="dns-prefetch" href="https://avatars.githubusercontent.com">
<link rel="dns-prefetch" href="https://github-cloud.s3.amazonaws.com">
<link rel="dns-prefetch" href=... |
c521a7765dfe6a60fd484c3d29c99a73e08f0b53ebfe41261f6c9ba7c9733761 | R | 151,502 | 2,817 | # Analysis Script for the taste_test TUE008 Depression Study
# Author: Corinna Schulz, corinna.schulz96@googlemail.com
# Created: March 2023
# Edited: July 2024
# Code content:
# (1) SET UP
# (2) LOAD DATA
# (3) VISUALIZE WANTING LIKING CHANGES OVER TIME
# (4) LINEAR MIXED EFFECTS MODELING & DATA VIZ for MDD. VS. H... |
0dc765e140f785563e6feba6ed1756d711b74f2db9130de3b1ab137ee45c9e0d | R | 151,614 | 3,904 | ---
title: "Extensive profiling of transcription factors in postmortem brains defines genomic occupancy in disease-relevant cell types and links TF activities to neuropsychiatric disorders."
date: "5/19/2023"
output:
html_document:
toc: true
---
# Pre-processing
This was run for each tissue/cell type
```{r,... |
8d363a3b0cdb85e4b8d5c76a65ab260e6d7d74824307151cb57142de0fe4f291 | R | 155,000 | 3,782 | # source ~/load_modules.sh
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(ggrepel)
source('~/SCRIPTS/utility_functions.R')
set.... |
d768cb28be4f4fed5a77eecb463d90b540f1c1fbb7f3614130aabe849599fb2b | R | 158,527 | 5,188 | ---
title: "Analysis pipeline for the behavioral and functional MRI data from the semantic Mnemonic Similarity Task"
output: html_document
editor_options:
chunk_output_type: console
---
# Glossary & packages
ENC = Encoding task phase
REC = Recognition task phase
RS = repetition suppression (first presentation - repe... |
9df3818f529c98bb98b525a031491fa67b34b02bc73e7320e1ad526fb54cf591 | R | 168,351 | 2,960 | ---
title: "manuscript"
author: "RC"
date: "`r Sys.Date()`"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
setwd("/Users/corcorri/Documents/Denver/Manuscript")
sessionInfo()
```
``` {r Libraries}
suppressPackageStartupMessages({
library(tidyr)
library(dplyr)
library(gg... |
8c3d2e8b66734fabd5511eecdda0a99090fb05a8fdc3ab5957b8a8002a9596d6 | R | 174,410 | 4,032 | #!/usr/bin/env Rscript
# ============================================================================ #
## 00_mgngtus_functions_regression.R
## MGNG-TUS study: Functions for plotting and fitting regressions to behavioral data.
## Copyright (C) Johannes Algermissen, University of Oxford, Oxford, UK, 2024-2025.
# ======... |
62f6a085176680c327146ecce1b07a22b20f7514bbd56ed31ef1246728805d39 | R | 174,548 | 3,045 | #' @title make_sample_lr_prod_plots
#'
#' @description \code{make_sample_lr_prod_plots} Visualize the scaled product of Ligand-Receptor (pseudobulk) expression per sample, and compare the different groups
#' @usage make_sample_lr_prod_plots(prioritization_tables, prioritized_tbl_oi)
#'
#' @param prioritization_tables ... |
371e297eca7f6777593bb44f20d5301850249746b3ee8e19dc04900a2cd0d199 | R | 179,994 | 4,620 | # STARTUP ####
overall_start_time = Sys.time()
tell_user = function(...) { cat(file=stderr(), paste0(...)); flush.console() }
# DEPENDENCIES ####
tell_user('Loading required packages...')
options(stringsAsFactors=F)
if (interactive()) {
setwd('~/d/sci/src/divalent')
}
suppressPackageStartupMessages({
library(t... |
88a5654dda24a240cceefd17860a6c89b424a58597fab02e7fa89933f40320db | R | 195,224 | 976 | pdf(file='/home/ubuntu/Software/PyRate/example_files/BDNN_examples/Carnivora/pyrate_mcmc_logs/Carnivora_occs_1_G_BDS_BDNN_16_8TVc_contribution_per_species_rates.pdf', width = 7, height = 6, useDingbats = FALSE, pointsize = 7)
ord_by_importance = function(s, consrank, rate_mean) {
imp = consrank**2
s = scale(s)
i... |
77ab2206b0664db4837e62353cd1b72bebea76e7ab7f686c139ab3226e0eade0 | R | 197,901 | 976 | pdf(file='/home/ubuntu/Software/PyRate/example_files/BDNN_examples/Carnivora/pyrate_mcmc_logs/Carnivora_occs_1_time_windows_G_BDS_BDNN_16_8TVc_contribution_per_species_rates.pdf', width = 7, height = 6, useDingbats = FALSE, pointsize = 7)
ord_by_importance = function(s, consrank, rate_mean) {
imp = consrank**2
s =... |
ee40d42749e388ee2c62efffc809f73c3134962a2ddfd8d5c955774d6bdb43a0 | R | 200,000 | 970 | pdf(file='/home/ubuntu/Software/PyRate/example_files/BDNN_examples/Carnivora/pyrate_mcmc_logs/Carnivora_occs_1_taxon_time_tables_G_BDS_BDNN_16_8TVc_contribution_per_species_rates.pdf', width = 7, height = 6, useDingbats = FALSE, pointsize = 7)
ord_by_importance = function(s, consrank, rate_mean) {
imp = consrank**2
... |
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