sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3b6f79906b6d17a1c36326be1bcc16e1c803fd4c2d03f228a02acc67426e819a | R | 36,789 | 953 | #!/usr/bin/env Rscript
# Helper script to plot per-sample SV benchmarking vs. an external dataset
###Set master parameters
options(stringsAsFactors=F,scipen=1000)
rare.max.freq <- 0.01
uncommon.max.freq <- 0.1
common.max.freq <- 0.5
major.max.freq <- 1
tiny.max.size <- 100
small.max.size <- 500
medium.max.size <- 25... |
bed2aede60e120c32595421925366836ccf76a943780553814bdab385043f6b8 | R | 37,086 | 902 | ---
title: "Triploid paper analysis"
output:
html_document: default
pdf_document: default
word_document: default
date: "2023-12-20"
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(include = TRUE, warning = FALSE, echo=TRUE, message=FALSE)
```
... |
69a75f56d28569fd2f6d40728d3a2cf69412098c03d3189a2b41fc39eb99344e | R | 37,239 | 968 |
basepath = "/net/trapnell/vol1/home/readdf/trapLabDir/hubmap/results/2021_07_15_Greg_ATAC_Code_nobackup/"
# dir.create(paste0(basepath, "archr/results/NB6/"))
out_dir = paste0(basepath, "archr/results/NB6/")
setwd(out_dir)
# load requirements
suppressPackageStartupMessages({
library(ArchR)
library(monocle3)
lib... |
aeb7f087edaa0102d27c13e6342349e712997d33856840a8d639def3fdb95cb7 | R | 37,359 | 1,029 | ---
title: "scRNA-Seq Analysis of Embryos dataset from Xu et al 2023"
output: html_notebook
---
## Intro
```{r}
## Load libraries
library(Seurat)
library(harmony)
library(ggplot2)
library(SingleR)
library(dplyr)
library(patchwork)
library(RColorBrewer)
library(SingleCellExperiment)
library(tidyverse)
library(sctransf... |
23ed11353975c16699a6ea4961198e83a524d704cbc806d53948c7de83c22fc0 | R | 37,718 | 994 | #!/usr/bin/R
# -----------------------------------------------------------
# Aggregate and plot chunked runs of MAST + RE for DGE
# Plot the comparison between regressions on different pathologies.
# Updated: 02/11/2021
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
s... |
a505ff5d8a16b7c406ff816a1f8f3f9ba8d127613d09dc2142cc211fcb2301cc | R | 37,977 | 1,210 | ---
title: "Vertical Analysis MPA: Ctrl+Saline, NTI, Nalozone (hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type... |
258c8e6586162bf94587c16230b20b204b7a68e9a5af8e662dfaf13db6f6673b | R | 38,097 | 919 | #' Interactive function to build an l2 model specification for setup_glm_pipeline
#'
#' @param gpa a \code{glm_pipeline_arguments} object containing an analysis pipeline to which $l2_models
#' should be added. If $l2_models is already present, these will be amended.
#' @param from_spec_file optional YAML or JSON file... |
0e12578e2d6fb0ebf904d0596a1fc5a3faa7f4bde387e86a82a41f14cda4c60d | R | 38,127 | 1,385 | ---
title: "Vertical Analysis Pa: Ctrl, Saline (L, R; hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
... |
0a3f8cd55a1a03e41dc45bc38c4cdafd57f0da96b18ac8f5511f8dae53547921 | R | 39,015 | 864 |
basepath = "/net/trapnell/vol1/home/readdf/trapLabDir/hubmap/results/2021_07_15_Greg_ATAC_Code_nobackup/"
dir.create(paste0(basepath, "archr/results/NB9/"))
out_dir = paste0(basepath, "archr/results/NB9/")
setwd(out_dir)
set.seed(7)
# load requirements
suppressPackageStartupMessages({
# library(ArchR)
library(mon... |
9877cbd0c2c55633fd8807a1a3d22f93f69364baf119c55d08121c3d4be0827e | R | 39,287 | 1,157 |
#' selectAppearanceRatio - It represents, per ratio of appearance, the number of hubs included in the model together with the train and
#' test performance of the model (Accuracy/R2).
#'
#' @param hubGenes the output of getHubGenes function containing both LASSO models and linear regression models
#' @return a list co... |
052a8d2bfe18099007897db4931ce6a997de5668de1c3186a2170a1de259415c | R | 39,338 | 1,171 | #' @include zzz.R
#'
#' @importFrom DT DTOutput
#' @importFrom htmltools div h3 h4 HTML includeCSS p tagList tags
#' @importFrom shinyjs disabled useShinyjs
#' @importFrom shiny actionButton checkboxInput column downloadButton fileInput
#' fluidRow htmlOutput icon numericInput plotOutput radioButtons selectizeInput
#' ... |
8b3aafd7001043161ccec82b64fa422bdd1f6a9d5f35afe6be10d3810868d1ca | R | 39,735 | 854 | # register bg_ custom classes so that DBI writeTable works with this as a formal (S4?) class
setOldClass(c("bg_subject_data", "data.frame"))
setOldClass(c("bg_run_data", "data.frame"))
setOldClass(c("bg_session_data", "data.frame"))
setOldClass(c("bg_block_data", "data.frame"))
setOldClass(c("bg_trial_data", "data.fram... |
a924c12e6f2e9410e686175d33289fbcc67946666b9f9f42abbf6513ef2e19b3 | R | 40,211 | 1,164 | # Load packages ----
require(shiny)
require(readr)
require(DT)
library(shinyhelper)
require(stringr)
require(dplyr)
library(shinyalert)
library(progressr)
library(networkD3)
library(rsconnect)
library(RCurl)
library(shiny)
library(ASySD)
library(shinythemes)
library(knitr)
library(shinycssloaders)
library(htmlwidgets)
... |
0cc74360cd7cd87217dd50dba014153a5228477dcac5b4bf0bdf08267d69f361 | R | 40,251 | 1,041 | #!/usr/bin/env Rscript
# Helper script to plot per-sample VCF stats output from collectQC.sh
###Set master parameters
options(stringsAsFactors=F,scipen=1000)
rare.max.freq <- 0.01
uncommon.max.freq <- 0.1
common.max.freq <- 0.5
major.max.freq <- 1
tiny.max.size <- 100
small.max.size <- 500
medium.max.size <- 2500
me... |
ea971847aab529a1a16f4edd0f3a735b78157cde439aca5d0380ebe799a17b8f | R | 40,510 | 1,013 | #!/usr/bin/env Rscript
# Helper script to plot VCF benchmarking against external dataset
###Set master parameters
options(stringsAsFactors=F,scipen=1000)
rare.max.freq <- 0.01
uncommon.max.freq <- 0.1
common.max.freq <- 0.5
major.max.freq <- 1
tiny.max.size <- 100
small.max.size <- 500
medium.max.size <- 2500
medlar... |
f309598fd94f8683dd5450a3abb2904d113c5d38f872ac8087e120618c04e14e | R | 40,912 | 829 | ############################################################################################################
# Reads in important libraries for downstream analysis
library(tidyverse)
library(Seurat)
library(SeuratDisk)
library(SeuratWrappers)
library(SoupX)
library(pcaMethods)
library(hdf5r)
library(harmony)
library... |
ad5edf6c39585f9722af5b35d6c0690fa643e7e6cffafa03c87f7cdb3d096e29 | R | 41,098 | 1,446 | ---
# For vignette ---------------------------------------------------------------
title: Plotting Functions in "hyperSpec"
sutitle: "Manual of hyperSpec's Plotting Functions"
description: "plotting: Manual of hyperSpec's plotting functions"
# Authors ----------------------------------------------------------... |
2f7c1a976ffbc13a4fbc30143518f59bdb5667356b4172eb7df2186e3cc02657 | R | 42,320 | 1,039 | rm(list = ls())
# the code we are using is an amended version of radarchart function from fmsb library:
# install
# install.packages("fmsb")
#install.packages("ggpubr")
#install.packages("scales")
#install.packages("stringr")
# Library
library(fmsb)
library(ggplot2)
library(ggpubr)
library(scales)
library(stringr)
# ... |
8ec65f1363d6836b04704dc7d59fa4529a9e3f16f80c719935be58956246e20b | R | 42,371 | 1,009 | #!/usr/bin/R
# -----------------------------------------------------------
# Use the pathology to run some tests on linear mixed models:
# Experiments on EC + methodology
# Test: Ex-TOX3-TTC6 and Mic
# Updated: 01/20/2021
# -----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')... |
9178da65258ebdabfde7d2aa2a228268c726a1f8ec5980a9516a66d779f9a3b0 | R | 42,520 | 1,144 | library(testthat)
library(dplyr)
library(tidyr)
library(sccomp)
# Per-slot RE design (see prepare_replicate_data(X_random_effect_slots = ))
re_slots_from_mi <- function(mi) {
lapply(seq_len(sccomp:::N_RE_SLOTS), function(k) mi[[paste0("X_random_effect_", k)]])
}
test_that("replicate_data works correctly", {
skip_... |
c1062cd83a7dc705ae84d50d4b66e6e452451e46b4d3019fdd01cd3d6e7098b7 | R | 42,567 | 731 | #' Run Monocle3 from Seurat object.
#'
#' Run monocle3 from Seurat object, performing its own clustering, partitioning
#' and then creating a pseudotime trajectory and plots.
#'
#' @param input_files Character vector with paths to Seurat .qs files.
#' @param input_names Character vector with sample names of input files... |
b8ffe6f8d8848079bb5bc9ac67ececa6acb1ef7d72116ef03fd2be272a467fda | R | 42,613 | 1,311 |
library(Seurat)
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
##########################################################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Ast_integrated_batch_5000_le... |
0ec70b5ee4d123e7cc17a4b1616cbd131a40db46e53ea67970c8efc6906b25f7 | R | 42,681 | 1,189 | #' This function generates the inputs for level 3 analyses, where multi-subject data are analyzed
#' in group analyses.
#'
#' @param gpa a \code{glm_pipeline_arguments} object containing analysis speecification
#' @param l3_model_names a subset of L3 models to be setup by this function. If not specified,
#' all mod... |
7f79f09d2d1332995ff9fdfc688efcb82624d01df51a1bedd731e25b98fb297f | R | 42,789 | 1,311 |
library(Seurat)
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
##########################################################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Ast_integrated_batch_5000_le... |
28d42aa458d2d60dbf4cb39925252790d12ee250dba9367736a7cc32235c95fc | R | 42,877 | 1,311 |
library(Seurat)
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
##########################################################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Ast_integrated_batch_5000_le... |
b7bed146d9665cebe94d4521eae93b5de9498890fe7e63b61b72ac5b3efe565a | R | 42,965 | 1,311 |
library(Seurat)
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
##########################################################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Ast_integrated_batch_5000_le... |
fb04c398c093617c4e92bede05ef0d335206992ae05e71b3a95bb41063324f9e | R | 43,005 | 1,410 | # Unit tests for sccomp_proportional_fold_change function
# Testing from simple models to interaction models
library(testthat)
library(sccomp)
library(dplyr)
library(stringr)
# Helper function to skip tests if cmdstan is not available
skip_cmdstan <- function() {
if (!instantiate::stan_cmdstan_exists()) {
skip(... |
4e34eb488e2a10575dc8a5f04954eb11787afd4e63671f7b4bd24c50b7f91381 | R | 43,176 | 648 | rm(list = ls())
#############################
## Load Relevant Libraries ##
#############################
require(ggplot2)
require(Hmisc)
require(MASS)
require(mgcv)
require(ppcor)
require(stringr)
require(visreg)
require(parallel)
require(multilevel)
require(stats)
require(Formula)
require(lavaan)
require(lme4)
requi... |
64756493eab9dbe8f582e1506ecd6d2ee08a60f23afba01fd1605909b1b83325 | R | 43,229 | 894 | library(tidyr)
library(mgcv)
library(gratia)
library(tidyverse)
library(dplyr)
library(lme4)
library(pbkrtest)
#### RESIDUAL PLOT FOR GAMM INTERACTION, WITH SPAGHETTI LINES ####
# Reworked from code from Dr. Bart Larsen
resid_plot_int <- function(modobj,term,int.term=NULL,add.intercept=FALSE, group.var="modid", low_co... |
036b8309a12a3a9edf25204c1d25b9d7f5c4e78c9a36ca80e583125d06b8c88c | R | 43,360 | 1,174 | #!/usr/bin/R
# ----------------------------------------------------------
# Plot the average gene expression for markers for clusters:
# Script used (pre-Sept 2020) for annotating clusters and removing doublets
# ----------------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
source(past... |
5f01cd6462c0955819e7ff33945df83db9512efd97329d81376ba183101e6b5f | R | 43,474 | 1,096 | #!/usr/bin/R
# -----------------------------------------------------
# Investigate selective vulnerability of the EC neurons
# NOTE: taking chunks out of this to split up and clean analysis.
# Updated: 03/08/2021
# Cleaned: 12/06/2021 +
# -----------------------------------------------------
library(cbrbase)
set_proj(... |
5c8bfcfd33651c16d1688e6dbc0d7ce8d79c9caa4db78f53f5e9f89d65c6a346 | R | 43,707 | 974 | .mixed_by_normalize_pairs_args <- function(pairs_args, field_name) {
if (is.null(pairs_args) || identical(pairs_args, FALSE)) {
return(NULL)
}
if (isTRUE(pairs_args)) {
return(list())
}
if (is.character(pairs_args) && length(pairs_args) == 1L) {
return(list(adjust = pairs_args))
}
if (!is.list... |
9096de66303859e9164c60416c401bc7addea7523f73c543ebddc8b99f482c48 | R | 44,020 | 801 | #!/usr/bin/env Rscript
# run like
# ./ROI_TempCorr.R -ts /Volumes/Phillips/WorkingMemory/11155/20130418/SpatialWM_v1_run1_768x720.5/nfswkmtd_functional.nii.gz -brainmask /Volumes/Phillips/gm_50mask.nii
printHelp <- function() {
cat("ROI_TempCorr is a script that computes temporal correlations among ROIs defined b... |
a92baf411fe1660055f7cbfe6b154280f5f574d504e19570f5b6cedab40dc6e6 | R | 44,027 | 1,240 | #' @include zzz.R
#' @include helpers.R
#' @include ui.R
#'
NULL
#' @inheritParams RunAzimuth
#' @param reference Name of reference to map to or a path to a directory containing ref.Rds and idx.annoy
#' @param annotation.levels list of annotation levels to map. If not specified, all will be mapped.
#' @param umap.name... |
8cded5821648bb24deb435f3e289bcde379ffb0d3ef2ff5a01e0213f01560226 | R | 44,138 | 1,278 | ---
title: "_Cardinal 3_: User guide for mass spectrometry imaging analysis"
author: "Kylie Ariel Bemis"
date: "Revised: 1 September 2024"
output:
BiocStyle::html_document:
toc: true
vignette: >
%\VignetteIndexEntry{1. Cardinal 3: User guide for mass spectrometry imaging analysis}
%\VignetteEngine{knitr::rmarkd... |
edb6308ddd32ce0b697cb997577a08c980731443a8ad4d77295f79cdac491bbb | R | 44,991 | 971 | ---
title: "scvi_analysis"
output: html_document
---
# Load libraries
```{r}
library(tidyverse)
library(DeepComBat)
library(neuroCombat)
library(CovBat)
library(latex2exp)
library(DescTools)
library(GGally)
library(ggfortify)
library(ggpubr)
library(umap)
library(caret)
library(matrixStats)
library(twosamples)
libr... |
a00a263bd36922f18363fc5cac09e5fd23295b8dcbdb347bfe7aaf7c37f3cd00 | R | 45,032 | 890 |
library(data.table)
library(dplyr)
library(survival)
library(survminer)
library(ggplot2)
library(broom)
source("../00_read_prs.R")
######## Pre-defined functions
pretty_number <- function(x, n_digit){
return(prettyNum(round(x, n_digit), big.mark=",", scientific=FALSE, drop0trailing=FALSE))
}
######## Make d... |
461bd7af755d050b73ca2ba2646babc72c0609a7e759f90dc4fffe05cea4c4ac | R | 45,087 | 827 | ---
title: "Considerations for Longitudinal fMRI Analysis in fmri.pipeline"
author: "Michael Hallquist"
date: "`r Sys.Date()`"
output:
rmarkdown::html_vignette:
toc: true
toc_depth: 3
vignette: >
%\VignetteIndexEntry{Considerations for Longitudinal fMRI Analysis in fmri.pipeline}
%\VignetteEngine{knitr::r... |
3aa6015d3bad47726e21f92c968b384166e8d8d5550cf778f0d65658161feab8 | R | 45,517 | 1,130 | library(tidyverse)
library(broom)
library(quickpsy)
library(glmnet)
library(rstatix)
###########################################################################
# Load and preprocess data ------------------------------------------------
###########################################################################
data ... |
2620349ebdc682612b70f6c5f44bbbac2235d9fbeff6d0eac7e2d4d511ee4b8e | R | 45,904 | 1,128 | # SPM design, estimation, and timing helpers
normalize_spm_estimation_method <- function(estimation_method) {
if (is.null(estimation_method) || !is.character(estimation_method) || length(estimation_method) != 1L) {
stop("estimation_method must be a single non-empty string.")
}
if (!nzchar(estimation_method))... |
9110d37a025c7db515e9bac28a05d61fb46ed99558c3749d0c498c9596921b12 | R | 46,604 | 1,182 |
#' getSamplingIndex - It splits samples into different folds for bootstrapped LASSO
#'
#' @param seed the seed number to ensure the reproducibility of the results
#' @param exprData a data frame representing a gene expression matrix with genes as rows and samples as columns
#' @param train.split the proportion of samp... |
a7adc637deda2e1f86cbb85f06ef3fb8fb21c9102f1148f7036e694653540123 | R | 47,119 | 553 | # Setup -------------------------------------------------------------------
library(raincloudplots)
library(tidyverse)
library(stats)
library(parallel)
library(lm.beta)
library(summarytools)
library(psych)
library(GGally)
library(cifti)
library(ciftiTools)
library(ggseg)
library(ggsegGordon)
library(visreg)
library(mgc... |
d4cb0225e64b137ff9ce5cc1d6f3dec88c6a3edcc27b4002a45bb5926ac8be67 | R | 47,398 | 1,380 | #' Converts gene names of query to match type/species of reference names (human
#' or mouse).
#'
#' @param object Object to convert, must contain only RNA counts matrix
#' @param reference.names Gene names of reference
#' @param homolog.table Location of file (or URL) containing table with
#' human/mouse homologies
#' ... |
104734029617f98c1fcbf054013c540c75c24a3755fe23d93fbe955dd25b8cd5 | R | 47,653 | 1,160 | #' Interactive function to build an l1 model specification for setup_glm_pipeline
#'
#' @param gpa a \code{glm_pipeline_arguments} object containing an analysis pipeline to which $l1_models
#' should be added. If $l1_models is already present, these will be amended.
#' @param trial_data a data.frame containing trial-... |
66bffef946b9140e54a8bf94a7e9206d513e22db3a69019442abedbb16302cf9 | R | 48,568 | 1,276 | #!/usr/bin/env Rscript
# Script to analyze a matrix of coverage (binCov) values per contig per sample.
# Performs the following:
# 1) copy number estimation per contig per sample (with visualization options)
# 2) sex assignment (with visualization options)
# 3) [optional] PCA & k-means based sample batching (with visu... |
4973f8ced872c2494fededb4dd9e28b1f7606eb348ca0291d60c6b3700807502 | R | 49,058 | 1,341 | #' Helper functions for build_design_matrix
#'
#' These functions are internal helpers that implement specific stages of the
#' design matrix construction pipeline. They are split out from the main function
#' to improve testability, maintainability, and clarity.
#'
#' @name build_design_matrix_helpers
#' @keywords int... |
852ae13e8c870bc5385b863c050052ef76458d5e708581c3232910a48d89611e | R | 49,237 | 1,609 | ---
title: "Vertical Analysis MPA: Ctrl, Saline (L, R; hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline... |
f758e4c53680b638625d1d680253acb0ae57fbe6490fd0eb24ad1b4e415894fb | R | 49,349 | 1,156 | osama_main <- readRDS("bulk_rna_mat.rds")
library(readr)
library(tidyverse)
expression_matrix <- osama_main@assays@data$counts
dim(expression_matrix) #20276 genes #76 samples
phenotype_data <- as.data.frame(osama_main@colData)
View(phenotype_data)
all(colnames(expression_matrix) %in% phenotype_data$Sample) # FALSE
su... |
c5c9e63f365bfa120ae5dc6bc2bc456924b1b956a44fb708c43b61abee80e117 | R | 49,488 | 1,619 | ---
title: "Vertical Analysis MPA: Ctrl, Saline (L, R; hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline... |
4724fb9ebf5bbc8b7d0f5228212d465d4d91accd7d531d479fa4d663122c77d2 | R | 50,565 | 1,417 | library(ArchR)
library(Seurat)
library(dplyr)
setwd('/ArchR/subprojects')
library(Seurat)
library(ArchR)
library(dplyr)
library(tidyr)
setwd('/ArchR/subprojects')
library(stringr)
addArchRGenome("mm10")
## BE SURE TO SET FORCE = FALSE TO NOT OVERWRITE ARROW FILES
inputFiles <- c('/scATAC/finalWorkflow/clusters/clust... |
1a3d1e87b86069c428682c5c9696a8659d6658a397ebb229fbe873e2958fda24 | R | 50,635 | 1,542 | # Unit tests for setup_l1_models, setup_l2_models, setup_l3_models
# ==================================================================
# These tests focus on input validation and helper functions that can be
# tested in isolation without requiring external data or cluster resources.
library(testthat)
# =============... |
24507e275e3ca9e10cb3ed583aa72dd0ffb776a8d5611554a4d3d69ee5038726 | R | 50,915 | 1,224 | ---
title: "RNA-seq analysis"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# RNA-seq analysis
```{r, warning=FALSE, message=FALSE}
# Load libraries and custom functions -----------------------------------------
library(easypackages)
libraries("here","ggplot2","WGCNA","... |
e9e87c64df97a4555adc8b9f721baaa0e2869f0c159f248210e281200ded7836 | R | 51,077 | 1,286 |
#' getSamplingIndex - It splits samples into different folds for bootstrapped LASSO
#'
#' @param seed the seed number to ensure the reproducibility of the results
#' @param exprData a data frame representing a gene expression matrix with genes as rows and samples as columns
#' @param train.split the proportion of samp... |
286f937288d44aefc9f7f38fe9aa7d7eef8072113bb92a786700d36f00fa64c9 | R | 52,179 | 973 | #' Creates an fmri design matrix, including timing files for for AFNI or FSL.
#'
#' @param events a data.frame that includes a column for the event type (e.g. outcome vs. cue),
#' run number (1:n), trial number (nested within run, 1:x), onset, duration of event
#' @param signals expects a list of list. The fi... |
4428256693cbc3569d624cc4813e60e3d4058d8af94297d9b035bf3fa63ca074 | R | 53,436 | 1,100 | #' Helper function to append baseline regressors to the convolved design matrix.
#' These are especially useful for GLMs that use concatenated data for multiple runs,
#' where run-specific intercepts and drift terms are needed.
#'
#' @param dmat_convolved The design matrix containing convolved regressors for all ev... |
3bf9ad5e168d2fae90e62990ced6d76e6be69e32216f58433e824022a7ff15c9 | R | 53,547 | 1,510 | ---
title: "scRNA-Seq Analysis of Brain Organoid dataset from Testa et al 2020"
output: html_notebook
---
## Intro
```{r}
## Load libraries
library(Seurat)
library(harmony)
library(ggplot2)
library(SingleR)
library(dplyr)
library(patchwork)
#library(celldex)
library(RColorBrewer)
library(SingleCellExperiment)
#library... |
63a629e82b9a976b0deeb70209a4cd836eb27252abe0eca5b577d8dd86d0e2a3 | R | 53,869 | 1,318 | #!/usr/bin/env Rscript
# Helper script to plot VCF summary stats output from clean_vcf2bed_output.R
###Set master parameters
options(stringsAsFactors=F,scipen=1000)
rare.max.freq <- 0.01
uncommon.max.freq <- 0.1
common.max.freq <- 0.5
major.max.freq <- 1
tiny.max.size <- 100
small.max.size <- 500
medium.max.size <- ... |
ffdca7f86247f0f29eea34bf68f99738933f2d7537f51c50073c03ac01904a0f | R | 54,245 | 1,291 | ##HOUSE KEEPING##
#Clear all variables to start from scratch
rm(list = ls())
# IMPORTANT!!!!! If DEBUG is TRUE then you will not be able to get user input,
# and groups will always unblind to A=Het, B=Mut, C=WT.
DEBUG <- FALSE
library(tcltk)
setwd(tclvalue(tkchooseDirectory()))
options(warn = 0)
#Load appropriate ... |
050f4652608ffd24a721340b89375c7406707967390e22d14a5668b7ccc726e2 | R | 54,296 | 1,376 | ---
# For vignette ---------------------------------------------------------------
title: Import and Export Files with Spectra
subtitle: 'Tutorial on Spectra File Import and Export for "hyperSpec"'
description: 'fileio: Tutorial on spectra file import and export for "hyperSpec".'
# Authors --------------------... |
846776f8988a13232742da9aedddb1bcdddb8663f2dd6a36718af018466a9dbd | R | 54,708 | 837 |
#' Runs CSIDE in intercept-only mode
#' @export
run.CSIDE.intercept <- function(myRCTD, barcodes = NULL, cell_types = NULL, cell_type_threshold = 125,
gene_threshold = 5e-5, doublet_mode = T, weight_threshold = NULL,
sigma_gene = T, PRECISION.THRESHOLD = ... |
6ee1ef9f8b445acc79b8fcbad6c263185d960b9d3b87a17928b97b56ceda325b | R | 56,138 | 737 | # Setup -------------------------------------------------------------------
library(tidyverse)
library(stats)
library(parallel)
library(lm.beta)
library(summarytools)
library(psych)
library(GGally)
library(cifti)
library(ciftiTools)
library(ggseg)
library(ggsegGordon)
library(visreg)
library(mgcv)
library(broom)
librar... |
af33d2cbdcca6cb61f62b170b8661d2032ff646defa94741a3a83679bb8635b9 | R | 56,263 | 1,224 | #' Main Function for SCCOMP Estimate
#'
#' @description
#' The `sccomp_estimate` function performs linear modeling on a table of cell counts or proportions,
#' which includes a cell-group identifier, sample identifier, abundance (counts or proportions), and factors
#' (continuous or discrete). The user can define a lin... |
a911d841588fd11f5a9e2c096926c8921de9102cfed05a3af6db90a7174f47e8 | R | 57,100 | 1,143 | #!/usr/bin/Rscript --slave
# by_example_participants_all_tracts_linear_Blackman_piecewise_w_plots.R
# Richard G. Carson: 4th March 2024
# revised: 4th March 2024
# store the current directory
initial.dir<-getwd()
# Specify the root directory
root.dir <- getwd()
# Specify the directory path for the output file
outp... |
1f9aca0adf5d5af6940bf8897ff4ace02c6427e8c76efb0a882b647e89b112a7 | R | 57,106 | 1,201 |
#' Getting GeneEffects matrices
#'
#' This function randomly generates the effect size of each evf on the dynamic expression parameters
#' @param ngenes number of genes
#' @param nevf number of evfs
#' @param randomseed (should produce same result if ngenes, nevf and randseed are all the same)
#' @param prob the pro... |
505c2255b439a031bc301e669d4ea03d9a914283bed8e53c93c8b5b7bdcc5bb3 | R | 57,784 | 1,284 | #' wrapper class for 3dClusterize
#' @importFrom tidyselect everything
#' @importFrom tidyr nest
#' @importFrom RNifti readNifti writeNifti
#' @export
afni_3dclusterize <- R6::R6Class("afni_3dclusterize",
private = list(
# private fields
pvt_input_file = NULL, # internal record of the input file to be passed... |
01958aef9413d0291f2128522fdea2e935ab2b587a93ae8e471e5f5df67d2378 | R | 59,337 | 1,459 | #!/usr/bin/env Rscript
# Helper script to perform family-based VCF QC & plot results
###Set master parameters
options(stringsAsFactors=F, scipen=1000)
rare.max.freq <- 0.01
uncommon.max.freq <- 0.1
common.max.freq <- 0.5
major.max.freq <- 1
tiny.max.size <- 100
small.max.size <- 500
medium.max.size <- 2500
medlarge.... |
386689755439d9296f860e74d8fef382c6ec9a431a20303c9575a9fc1abb19bd | R | 60,416 | 1,365 | #########################
########Licensing########
#########################
# Breathe Easy - an automated waveform analysis pipeline
# Copyright (C) 2022
# Savannah Lusk, Andersen Chang,
# Avery Twitchell-Heyne, Shaun Fattig,
# Christopher Scott Ward, Russell Ray.
#
# This program is free software: you can redis... |
553d0421c4552782c02a6c017a7bef96d75223c0028aa47da0df98c0e9ac8b42 | R | 60,548 | 798 | # Setup -------------------------------------------------------------------
library(raincloudplots)
library(tidyverse)
library(stats)
library(parallel)
library(lm.beta)
library(summarytools)
library(psych)
library(GGally)
library(cifti)
library(ciftiTools)
library(ggseg)
library(ggsegGordon)
library(visreg)
library(mgc... |
4d7bdcf6a520d7f42a98176f6507765dc6c701d45f4afb0d0cc6d952df01352c | R | 61,151 | 2,014 |
library(Seurat)
library(dplyr)
library(ggplot2)
library(limma)
library(muscat)
library(purrr)
library(scater)
##########################################################################################################
setwd("G:/PFC_429_final_Spring2021/Data")
pbmc=readRDS("Ast_integrated_batch_5000_le... |
bdc4dc28aca88b759a236f024b490a9bb882267e822a26731c8ed1b0a0191668 | R | 61,407 | 2,102 | ---
title: "Bilateral adrenalectomy: Pa (Pre, after adx, ADX+UBI, hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "10/22/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FAL... |
c543f2c424a63ddb4e03b425ef112ee3f05c3588ea998535a7ae1c8f76618a56 | R | 61,628 | 1,506 |
source("../../../sharedProjectCode/utility/singleCellUtilFuncs.R")
modStatus <- loadMonoclePackages()
print(modStatus)
# sessionInfo()
source("../../../sharedProjectCode/scRNA_Seq_Background_Code/backgroundMethods.R")
processingNote = "DanaRulaTest_6-7-21"
useScrublet = FALSE
writeMatrixForScrub = TRUE
scrubCutoff... |
51003bb51577562865e256131441e004431eb55ae11c912b93e566ae2139e1a5 | R | 61,788 | 580 | # This script performs the Bayes Factor analysis
# Written by Rotem Botvinik-Nezer
library(BayesFactor)
library(dplyr)
# clear workspace
rm(list=ls())
# read the data
use_z_scored_data = FALSE
if (use_z_scored_data) {
print("Using z scored data")
data = read.csv("pain_evoked_brain_measures_z.csv")
} else {
pri... |
6f4968a64fd78816232115698646df4759310a0e89bedb49f1f66b5c55360eb8 | R | 63,206 | 1,408 | #!/usr/bin/env Rscript
#---------------------------
# Batch CNV Interval Genotyping
# Talkowski Laboratory
#
# Harrison Brand, Ryan Collins, and Joseph Glessner
# Update May 2017 (implementation for SV-pipeline)
# Update June 2016 (clean modules, smaller windows, multiallelic binning, denovo visual)
# Update October 2... |
ff4c7eac5dcf689817b0a1622076c4fe105be95642aaff37a534cab63ddea139 | R | 65,071 | 1,425 | ---
title: "scvi_analysis"
output: html_document
---
# Preprocessing
```{r}
source("~/Documents/nnbatch/code/load_packages.R")
library(DescTools)
# all_raw <- read.csv("./data/raw.csv", header = F)
all_cov <- read.csv("./data/covariates.csv")
all_cov$SEX <- as.factor(all_cov$SEX)
all_cov$DIAGNOSIS <- as.factor(all_cov... |
9d841b985e04f3ec8f2e38bffca258a9fd7bb1c5cbc90a6c4924f92c4e5fc11f | R | 67,954 | 1,305 | #########################
########Licensing########
#########################
# Breathe Easy - an automated waveform analysis pipeline
# Copyright (C) 2022
# Savannah Lusk, Andersen Chang,
# Avery Twitchell-Heyne, Shaun Fattig,
# Christopher Scott Ward, Russell Ray.
#
# This program is free software: you can redis... |
d966cc0ce449df7b910a6c7b89be35337eabc2da943276e4d4c11dd698efe61e | R | 69,269 | 1,547 | #!/usr/bin/env Rscript
#---------------------------
# Batch CNV Interval Genotyping
# Talkowski Laboratory
#
# Harrison Brand, Ryan Collins, and Joseph Glessner
# Update May 2017 (implementation for SV-pipeline)
# Update June 2016 (clean modules, smaller windows, multiallelic binning, denovo visual)
# Update October 2... |
7392384a7a92c614180904d20ebd4d30bf47247f4b8aa1e5f7da29be8d993a6c | R | 69,375 | 1,750 | #!/usr/bin/R
# -----------------------------------------------------
# Investigate selective vulnerability of the EC neurons
# Updated 03/08/2021
# -----------------------------------------------------
library(cbrbase)
set_proj('DEVTRAJ')
source(paste0(bindir, 'multiRegion/load_metadata.R'))
library(tidyr)
library(lm... |
87718329b667ce116ca0caba4f897a6a99af0a020e2172714343eb56436ca791 | R | 69,897 | 1,923 | ---
# For vignette ---------------------------------------------------------------
title: Introduction to Package "hyperSpec"
subtitle: 'The Main Manual of Package "hyperSpec"'
description: "Introduction: hyperSpec's main manual."
# Authors -------------------------------------------------------------------... |
861758220a8f37ca04b2d7ca78b8ef0a66a25ceea3db3a3b666ee5df01303f39 | R | 71,009 | 2,036 | # Define global variable
# sccomp_stan_models_cache_dir = file.path(path.expand("~"), ".sccomp_models", packageVersion("sccomp"))
# Define global variable (without version - version will be added in load_model when needed)
#' Default cache directory for Stan models
#'
#' A global variable that defines the default c... |
0dbd23e0087771e19059c56cf523229b22481b5d06024f1fcbc04e7c18d1a87a | R | 72,216 | 2,121 | # For the specified k, conduct PLSC where X = frequency metrics and Y = 10 cognitive
# tests of interest. Do PLSC to find direction of loadings to flip, conduct
# permutation testing on singular values, investigate bivariate normality and
# outliers for significant latent variable pairs and correlate,
# conduct boo... |
a624c2d9fae26e1960c2aa1d8e474602b0c7d52689727d2e726b8180757196e7 | R | 72,263 | 1,514 | library(data.table)
library(survival)
library(survminer)
library(tableone)
library(ggplot2)
library(GGally)
library(patchwork)
library(gtools)
library(plyr)
library(Hmisc)
library(mltools)
library(RColorBrewer)
library(ResourceSelection)
library(pROC)
library(corrplot)
absolute_risk <- function(coxmodel,data){
cum... |
c2d2c1b4ddadc9f07d6e185b8d726dbc092ac11ff25d48931a3e1722c1d6896a | R | 72,428 | 2,126 | # For the specified k, conduct PLSC where X = distance metrics and Y = 10 cognitive
# tests of interest. Do PLSC to find direction of loadings to flip, conduct
# permutation testing on singular values, investigate bivariate normality and
# outliers for significant latent variable pairs and correlate,
# conduct boot... |
73d8b375d31adfe75104448349d13fc03a3ab7f4306094093b501fe574a9d8b5 | R | 72,756 | 2,131 | # For the specified k, conduct PLSC where X = network
# reconfiguration metrics and Y = 10 cognitive tests of interest. Do PLSC to find
# direction of loadings to flip, conduct permutation testing on singular values,
# investigate bivariate normality and outliers for significant latent variable pairs and correlate,
# ... |
ac1c8badda4ce70cfadbc41ae3d0c3301f792714016d0e981051e20c821c16a1 | R | 72,779 | 2,142 | #' The application server-side
#'
#' @param input,output,session Internal parameters for {shiny}.
#' DO NOT REMOVE.
#' @import shiny
#' @importFrom rlang .data
#' @import data.table
#' @import statmod
#'
#' @noRd
app_server <- function(input, output, session) {
# PERFORMANCE SETTINGS
n_cores <- getShinyOption(... |
6db5ec8aa597be492ccec100e737189ff9692b416a6e0c3fd52578b2c1a7106c | R | 76,075 | 1,957 | #!/usr/bin/R
# ----------------------------------------------------------------------------
# Investigate the co-variation of selective vulnerability in EC/HC and others:
# TODO: Neurons alone and neurons + glia
# Updated 05/10/2021
# -----------------------------------------------------
library(cbrbase)
set_proj('DEV... |
17d08e7ccba693059470b4e792dd704d239ea4683d74c471c71fd58278aa794d | R | 76,779 | 2,368 | ---
title: "Bilateral adrenalectomy: MPA (Pre, after adx, ADX+UBI, hand, machine)"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "9/23/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FAL... |
119b9a1c749c322a92b49c5def2b3acc9ca6b28eeb589533c0b88a21fdff5f6a | R | 82,487 | 1,051 | # This script creates plots for the paingen fmri placebo paper
# Written by Rotem Botvinik-Nezer
################
# PREPERATIONS #
################
# load libraries
library(ggplot2)
library(tidyverse)
library(ggpubr)
library(Rmisc)
library(Hmisc)
library(png, include.only = 'readPNG')
library(gridExtra)
## Clear wor... |
2c1419030b1c9cc9676bd840ffc5e018c974273e2bd8f4712cb3501c65841c60 | R | 84,263 | 2,798 | # Unit tests for build_design_matrix and all helper functions
# These tests focus on individual function behavior rather than integration testing
# ==============================================================================
# Test fixtures and helpers
# ==============================================================... |
015984a0f156775191aafe982275412f8538a1ebf1db3499432a03eb8d2d6bd3 | R | 86,578 | 2,684 | ---
title: "SF, CI Variances"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "12/30/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_output_type: inline
---
```{r setup, include=FALSE}
#
# rm(list = ls())
# gc()
source("../Bayesian... |
0403ba59106c338ed2e10cfd73d021ff21aee1f1a2c79130926a48e60478c2da | R | 86,835 | 2,067 | ---
title: "Testing empathy hypothesis in pair bonding _Ranitomeya imitator_ males"
author: "by Camilo Rodríguez"
subtitle: "Statistical analyses Noteboook"
date: "`r Sys.Date()`"
output: pdf_document
editor_options:
markdown:
wrap: sentence
chunk_output_type: console
---
# **Description**
This is the deta... |
b24c0987a1bad7cb662236d287033147f2687995d1aa17e263541787003b4f83 | R | 88,894 | 1,017 | # Setup -------------------------------------------------------------------
library(raincloudplots)
library(tidyverse)
library(stats)
library(parallel)
library(lm.beta)
library(summarytools)
library(psych)
library(GGally)
library(cifti)
library(ciftiTools)
library(ggseg)
library(ggsegGordon)
library(visreg)
library(mgc... |
9385ce0acb76f2340b17df94fec41644f97789dfac32d179ef303edc934b0b57 | R | 97,156 | 922 | ---
title: "Longitudinal RSI~AP by Sex"
author: "Devyn Cotter"
date: '2022-04-28'
output:
html_document:
fig_caption: yes
toc: yes
toc_depth: 4
toc_float:
collapsed: no
word_document:
toc: yes
toc_depth: '4'
pdf_document:
toc: yes
toc_depth: '4'
editor_options:
chunk_output... |
68decbda039814bf8b0f300fd209a1ebd27494386313bde38f96df780660522f | R | 99,430 | 2,723 | ---
title: "Lung-brain axis"
author: "Mark Ziemann"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
toc_float: true
code_folding: hide
fig_width: 7
fig_height: 7
theme: cosmo
---
Source: https://github.com/markziemann/lungbrain
# Introduction
Eslam’s Summary of RNA seq
* Project title... |
6467553d1d2ebc350fef79c123462728045d46def1165aea7cbc7ce9c974436f | R | 104,116 | 2,642 | #' Wrapper for running an AFNI command safely within R
#'
#' @param args AFNI command string to be run
#' @param afnidir Location of AFNI installation. If NULL, the function will search the environment for AFNIDIR or afni on PATH
#' @param stdout File target for redirecting stdout. If NULL, stdout will not be written t... |
ef02a748310a61a004893eba62eb8192080dfd9015892fa77043b8ef7224b789 | R | 113,304 | 3,269 | #load the packages
library(edgeR)
library(DESeq2)
library(limma)
library(org.Hs.eg.db)
library(tximport)
library(csaw)
library(readr)
library(ggplot2)
library(ggrepel)
library(WGCNA)
library(ggpubr)
library(bestNormalize)
library(ComplexHeatmap)
library(reshape2)
library(tidyverse)
library(caret)
library(MASS)
library(... |
f7d66ef4fd339175b67b6b13160e42eae1b31a61bc4f15c46f3ca7910f6e610a | R | 116,955 | 3,584 | ---
title: "SF, LR AI (Ctrl, BNI, FNA): Bayesian regression of smoothed stretch forces"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "Date: `r format(Sys.time(), '%d/%m/%Y')`"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options:
chunk_ou... |
fa3d2d163ea3c2b24354b6924be8737edb93fd14a42acb1813aa80ed557a20ff | R | 133,613 | 3,977 | ---
# title: "SF, CI AI: Bayesian regression of smoothed stretch forces"
title: "SF, LR AI: Bayesian regression of smoothed stretch forces"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "12/27/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options... |
9888ddb54f813ca4b4fa677f544945b02d27b934669d19d48a65d659c45a9eb8 | R | 133,802 | 3,961 | ---
# title: "SF, CI dW: Bayesian regression of smoothed stretch forces"
title: "SF, LR dW: Bayesian regression of smoothed stretch forces"
author: "Yaromir Kobikov <kobikov.yaromir@gmail.com>"
date: "12/14/2021"
output:
word_document: default
html_document:
toc: true
toc_float:
collapsed: false
editor_options... |
6a30412a1fca935bf409a18f9edc66aa8256dd4277000af86eb2261c5329d06f | R | 145,178 | 3,845 | #' @include zzz.R
#' @include helpers.R
NULL
#' Server function for the mapping app
#'
#' @param input,output,session Required Shiny app server parameters
#'
#' @return The shiny server logic
#'
#' @importFrom BiocGenerics width
#' @importFrom BSgenome.Hsapiens.UCSC.hg38 BSgenome.Hsapiens.UCSC.hg38
#' @importFrom data... |
f94316794e7b3b05e0c5e0a24773f380a0581642cb4d222f0bf88c6367e1b239 | R | 149,921 | 2,696 | ---
title: "NeuralSpatial: Statistics for Distinct neural mechanisms for heading retrieval and context recognition in the hippocampus during spatial reorientation"
author: "Manuel Miguel Ramos Álvarez and the Muzzio Lab"
date: "`r format(Sys.time(), '%B %d, %Y')`"
format:
html:
code_download: true
toc: true
... |
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