sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
922d897f696165ffb437ac7f5e1568fc89838460b5830d352e51f92f3cb18e45 | R | 51,152 | 847 |
Testing the preservation of co-expression across the different primary tissue brain regions
Really can only do this across the Bhaduri and Braun datasets, since they sample numerous brain regions
Exclude a dataset
Learn MetaMarkers from the rest
Aggregate the co-expression networks
Compute the preserved co-express... |
362cd5f9098d6856a35fa0130c4bdec85e93acb1190289da6f6b60bca9c54066 | R | 51,397 | 1,561 | ---
title: "Frailty index and the brain: analyses using `r prep_title`"
output:
html_document:
toc: true
theme: united
---
To compute frailty index (FI) and check for association between this general health metric and other variable of interests.
```{r setup, include=FALSE}
knitr::opts_chunk$set(ec... |
ba958dbae195c2e1b7dbfa154a7e384c48584d28b81aeb841693c2ae4f475080 | R | 51,667 | 1,566 | # Load packages
library(tidyr)
library(readr)
library(lubridate)
library(stringi)
library(forcats)
library(dplyr)
library(purrr)
# Functions
longer_by_instance <- function(data) {
pivot_longer(
data = data,
cols = matches(".+_f.+_0"),
names_to = c(".value", "instance"),
names_pattern = "(.+)_(.)_0... |
3ef31ae6a091cbe95b7719655dca56002379c599c2f254ac7ab6f3a5e58bc27c | R | 51,727 | 1,566 | # Load packages
library(tidyr)
library(readr)
library(lubridate)
library(stringi)
library(forcats)
library(dplyr)
library(purrr)
# Functions
longer_by_instance <- function(data) {
pivot_longer(
data = data,
cols = matches(".+_f.+_0"),
names_to = c(".value", "instance"),
names_pattern = "(.+)_(.)_0... |
592806b646999876504b7c26479b5563df856b8ad1e75cba0ac6e7ad05417007 | R | 51,866 | 1,500 | ---
title: "DAOY-2D_Seurat_EXPLORE1_50K"
author: "JJ"
date: "2023-01-26"
output: html_document
---
***scRNA-seq of DAOY 2D sample***
This file was written to check gene expression in the DAOY-2D sample and to prepare the sample for downstream integration
```{r graphical_output}
options(bitmapType='cairo-png') # this l... |
1e9db160731c647877849c12e1b50723329abb7a6d677af8692e2c6c224ea3f9 | R | 52,248 | 923 | # Load packages ----
require(shiny)
require(shinydashboard)
require(shinyWidgets)
require(shinyjs)
library(shinyBS)
require(visNetwork)
require(DT)
require(plotly)
#library(googleAuthR)
# Credit to https://stackoverflow.com/questions/50368690/change-backdrop-for-a-bsmodal-in-shiny-app#answer-50570420
# for this solut... |
16eaa78cfb15561d00a7b6dc585401d43c07a546a1d89680299d550c227a039c | R | 52,331 | 938 | #### CORRELATION ################
##################################
setwd("~/openchr/noack")
cortex.atac <- readRDS('~/openchr/noack/cortex_atac_imputed_expression.RDS')
atac_counts<- readRDS('~/openchr/noack/mypeaks_featurematrix.RDS')
metadata<-cortex.atac@meta.data
barcodes<-rownames(metadata)
sct_expression<-cor... |
913a7eeaeeb0f9c8e152d237c2368122b4ba43eb8d58f7c50fe3b28e17bbe619 | R | 52,939 | 1,665 | ---
title: "cropDiffusionR: How Maize Farmers in the US Southwest Grew and Prospered under El Niño but Suffered under La Niña"
author: "Andrew Gillreath-Brown"
date: "`r format(Sys.time(), '%d %B %Y')`"
html_document:
toc: yes
toc_depth: 2
toc_float: yes
number_sections: no
code_folding: hide
output:
html_document:... |
488b4d91d8c1e35a27107e395ffa520e09b42215acbb6f1d2b5ce228f2df6adb | R | 53,343 | 1,396 | ---
title: "Estimating group onsets using change point detection and hierarchical bootstrap: an example"
author: "Guillaume A. Rousselet"
date: "`r Sys.Date()`"
output:
# pdf_document:
# fig_caption: no
# number_sections: no
# toc: yes
# toc_depth: 2
github_document:
html_preview: yes
toc:... |
e9312cb47a78005a155377b5a92e437ab4b5f8ea70ec1521c17b9b4876854925 | R | 54,209 | 1,374 | ---
# 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 --------------------... |
cd260469cab56d34aec71134302337cb31d28d3149a447f4c6ad6ce23386c760 | R | 54,523 | 1,508 | ---
title: "Figure 1 and related supplement tables and figures"
author: "Meng-Ching Ko (MaggieMCKO)"
date: "07/17/2024"
output:
html_document:
df_print: paged
pdf_document: default
editor_options:
chunk_output_type: console
---
This [R Markdown](http://rmarkdown.rstudio.com) Notebook contain codes for repro... |
cf8cb749c74d65501227b7880f454eeb0af6c52312d9786c3751471a6228638a | R | 54,808 | 1,618 | #' Meta-analysis of single proportions
#'
#' @description
#' Calculation of an overall proportion from studies reporting a
#' single proportion. Inverse variance method and generalised linear
#' mixed model (GLMM) are available for pooling. For GLMMs, the
#' \code{\link[metafor]{rma.glmm}} function from R package
#' \b... |
3c5b3454c7fabfbc36fda4978cc16c841610100d01c111a8be9924a2d3ecf270 | R | 56,146 | 1,179 | # ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# ------------------------------------------------------------------------------------------------------------------... |
46aabf3897d35043f50628a6b4e91b2c6a87d064466c8187c47b3da7a14d23ad | R | 56,422 | 1,733 | #' Meta-analysis of incidence rates
#'
#' @description
#' Calculation of common effect and random effects estimates (incidence
#' rate ratio or incidence rate difference) for meta-analyses with
#' event counts. Mantel-Haenszel, Cochran, inverse variance method,
#' and generalised linear mixed model (GLMM) are availabl... |
24e56a24d7aadad28466c35485e81507316ab028fc6ecd4898caf9ca0d918fd8 | R | 56,721 | 1,375 | ---
title: "Descriptives - Session Models"
author: "<h3>by Michael Demidenko</h3>"
date: "`r format(Sys.time(), '%B %Y')`"
output:
html_document:
theme: united
highlight: tango
toc: yes
number_sections: yes
toc_depth: 2
toc_float:
collapsed: yes
smooth_scroll: yes
code_folding:... |
b7b78b95d9ef97633736d68fc37a65d5ca59796c2d4af2cb3a5878a37491e022 | R | 57,984 | 1,364 |
The organoid atlas from the arlotta lab with celltype annotations
```{r}
library(Seurat)
library(data.table)
library(ggplot2)
library(MetaMarkers)
library(dplyr)
library(MetBrewer)
library(parallel)
```
Original data from the Arlotta lab
Load it in and match the preprocessing steps from the rest of the analysis
... |
4395d5c0e3bf11810e825591a0f91765f7468633ae8d7482479929e54ff799bd | R | 57,993 | 702 | # load CellWalkR library
library("CellWalkR")
# load scATAC from Ziffra et al
x.sp <- readRDS("/data/AllPrimary_Sub_PCgenes.rds")
# load labeling data from Polioudakis et al
Polioudakis_markers <- fread("/data/Polioudakis_cluster_enriched_genes.csv")
# build network for CellWalk
Polioudakis_markers <- Polioudakis_ma... |
db5e39a34fb938838ad026cce7e7276bfd13e606da1523b18be587548080e3a3 | R | 58,057 | 1,014 | #### Control package versions ####
#renv::init()
BiocManager::install(version="3.13", force=TRUE)
renv::restore() # Restore CRAN package versions specified in conda environment
BiocManager::install(c("edgeR","limma","GOstats","org.Dr.eg.db"), force=TRUE)
BiocManager::install(
c("KEGGREST","genefilter","Category","RB... |
953108bba987159cec368b104dacca5e82d5d83789c02a75510faa650e11e33b | R | 58,119 | 1,435 | #================================================================================================================================#
#
# Author: James M Roe, PhD.
# Center for Lifespan Changes in Brain and Cognition, University of Oslo
# Purpose: run ML analysis in AD-control data (ADNI)
# apply AD-control weig... |
a620fbfc8c7dbda6526c1fdca64e1d6c0a05f25a843bee804a97cfe1b43b81dd | R | 58,871 | 980 | # plot for each organ (*6) (heart??)
# plot for forebrian & hindbrain combined (done)
# plot for all organs (done)
results_table_sig <- do.call(rbind, list(read.table("Figure_OrganDevelopment_R1/20240214_allsigtables/SigDiffEditSites_scriptv5_testis_prenatalVSpostnatal_60per_ADAR1ADAR2.txt", sep = "," ,quote = "", ro... |
69c43ee08f6b0594bfa6cde39645c05dd82fa4cd331ecaaed273fb01e8cdd5bf | R | 59,780 | 1,569 |
Notes on bulk dowload of GEO data for the organoid human single cell RNA-seq datasets
Initial exploration of cell numbers and metadata
Thinking of starting with just the 10X datasets, usually have the .barcodes, .features, .matrix files available all in the same format.
Additionally just start with the datasets ... |
cdbcfcfbccd1bf1a7d4515c84749f1e0f0b62be7c00eb803ecec0c162b5ba390 | R | 59,841 | 1,500 | #### Garner, Kind et al. 2024 ####
msh_tolerance <- 5000
aotu_bb_x_min = 160500
aotu_bb_x_max = 174300
aotu_bb_y_min = 39000
aotu_bb_y_max = 47500
aotu_bb_z_min = 1300
aotu_bb_z_max = 2200
# load required packages --------------------------------------------------
library(tidyverse)
library(natverse)
library(fafb... |
6f059fd73063d3562fdfa5992d3ad9d390c67fda2e460ca460626ab3bfce2324 | R | 60,521 | 1,940 |
isp=read.csv("8.27.24_Wailupe.csv")
#isp$Collection.Time<-format(as.POSIXct(isp$Collection.Time,format='%I:%M %p'),format="%H:%M:%S")
par(mfrow=c(1,1))
#format date as a date
isp$Date <- as.Date(isp$Date, "%m/%d/%y")
isp[which(isp$Site == ''),]
#something called NEWSPRING, looks like should be excluded
isp2 <- isp[-... |
7e3ed75a68e6ddb6f83c29bcdd693f91468676538d8af29e959949738269a12d | R | 61,253 | 2,094 | # Auxiliary functions for forest.meta()
#
# Package: meta
# Author: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>
# License: GPL (>= 2)
#
add.label <- function(x, column,
xpos, ypos, just, fs.lr, ff.lr, col,
fontfamily,
...) {
#
pushViewpo... |
896a3e31ecaed244af836f7243ba96de9af7c6f667ab8d77329004a99789598b | R | 61,507 | 1,316 | ---
title: "Figure 1 BC, Github Figure 2, Github Figure 3 C, Github Figure S4 D, Extended Data DEP, Extended Data GSE"
author:
- name: "Emir Turkes and Stephanie Fowler"
date: '`r strftime(Sys.time(), format = "%B %d, %Y")`'
link-citations: true
output:
html_document:
code_folding: show
number_sections: tru... |
6344c1a27da811871ff40475ac2bff155e3a7ad8f4750b55db8ab5dc14d4d481 | R | 61,859 | 1,465 | ---
title: "Descriptives - Run Models"
author: "<h3>by Michael Demidenko</h3>"
date: "`r format(Sys.time(), '%B %Y')`"
output:
html_document:
theme: united
highlight: tango
toc: yes
number_sections: yes
toc_depth: 2
toc_float:
collapsed: yes
smooth_scroll: yes
code_folding: hid... |
06fefde618264a75ed96053f005bcb86993daa7b10eedbf12066b046b3af68f5 | R | 62,752 | 1,460 | Single dataset coexpression
Starting with the fetal data
Get markers from all the other datasets
Get Coexpression
```{r}
library(Seurat)
library(knitr)
library(matrixStats)
library(data.table)
library(ggplot2)
library(MetaMarkers)
library(dplyr)
library(MetBrewer)
library(ComplexHeatmap)
library(circlize)
Sys.set... |
eff8f4d88dbf2b5cbcd1523218c268a67ffd5725147dfef3595432fb2d140bec | R | 63,899 | 1,713 | #' Print meta-analysis results
#'
#' @description
#' Print method for objects of class \code{meta}.
#'
#' R function cilayout can be utilised to change the layout to print
#' confidence intervals (both in printout from print.meta and
#' print.summary.meta function as well as in forest plots). The
#' default layout is ... |
50ba0b7abc5cc1f2e335eb09c721b8cdba64680e24a8516f3bc6d954bcb51bc6 | R | 63,970 | 1,383 |
```{r}
library(Seurat)
library(data.table)
library(ggplot2)
library(ggrepel)
library(MetaMarkers)
library(dplyr)
library(ggridges)
library(gridExtra)
library(MetBrewer)
library(parallel)
library(ggExtra)
```
Get an AUC for a gene's expression
```{r}
gene_auc = function(gene_expression, label){
label = as.logic... |
2f6109477b429f6c9d9436279b68ab2484581f987cd66c678e1b5814e3e32e47 | R | 65,574 | 1,834 | #' Print and change default meta-analysis settings in R package \bold{meta}
#'
#' @description
#' Print and change default settings to conduct and print or plot
#' meta-analyses in R package \bold{meta}. The following general
#' settings are available: \emph{Review Manager 5}, \emph{Journal of
#' the American Medical ... |
69099c650db0be983f8f84d35e8573d056cb3e2336ce970d50ed568fbecbf3c6 | R | 65,632 | 1,402 | ```{r}
setwd('path')
library(readxl)
library(tidyr)
library(ggplot2)
library(ggsignif)
library(ggpubr)
library(rstatix)
library(dplyr)
library(broom)
library(Kendall)
library(lme4)
library(reshape2)
library(exact2x2)
library(multcompView)
library(rcompanion)
library(RVAideMemoire)
library(coin)
libr... |
cbc1b330236146aa20beed5eac867cbf6d72ec01e1bbba18f3a61a824a5ce38d | R | 65,675 | 1,753 | ---
title: "Riemondy_NeurOncol_2022_seurat_QC_analysis"
author: "JJ"
date: "2023-12-29"
output: html_document
---
```{r graphical_output}
options(bitmapType='cairo-png') # this line of code needed BEFORE knitr code in chunk below
```
```{r setup, include=FALSE}
knitr::opts_chunk$set(dev = "png",
... |
cb6ca073e7b4ef77aa2e5256f65f538653dfcefe6e04550bcdc6e2d6aa362c4e | R | 68,492 | 2,412 | # Load packages ----
# Annotation
library(parallel)
library(BiocGenerics)
library(Biobase)
library(stats4)
library(IRanges)
library(S4Vectors)
library(AnnotationDbi)
library(GenomeInfoDb)
library(GenomicRanges)
# Plotting/UI
library(heatmaply)
require(ggplot2)
require(ggrepel)
require(RColorBrewer)
require(factoextra... |
28c17ec23fdaf1f38307c680f3c59a190c1daa90ac412dcb579ff3b2874c3df6 | R | 69,406 | 1,904 | ---
# For vignette ---------------------------------------------------------------
title: Introduction to Package "hyperSpec"
subtitle: 'The Main Manual of Package "hyperSpec"'
description: "Introduction: hyperSpec's main manual."
# Authors -------------------------------------------------------------------... |
58fd7c324525bff0b25b5a8c0ef7c6b6e199b5588a74bc2669cdb7b40bb7b1e1 | R | 69,959 | 1,222 | #####Spearman Analyses
#### Coded: Benjamin Saef
#### Date as of commenting and documentation - 05/28/2024
library(tidyr)
library(data.table)
library(RVAideMemoire)
library(pROC)
library(RColorBrewer)
library(MuMIn)
source("./Functions_for_Analysis.R")
#NO YEARS OF EDUCATION
#Make partial comparisons to top compar... |
cbb17d77c3b771e2701da44dd55083181a6c8355a2d34b0eaedf9e5e1d74780c | R | 71,186 | 363 | ---
output: word_document
bibliography: doc/references.bib
csl: doc/nature.csl
link-citations: true
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)
```
```{r}
library(data.table)
library(flextable)
```
# Title page
**Title**
Genome-wide association study of mul... |
263ace784cc5665b93d8773449b5a1159e7b2688d06812703a729d43a4f81940 | R | 73,044 | 2,251 | #' Meta-analysis of continuous outcome data
#'
#' @description
#' Calculation of common and random effects estimates for meta-analyses
#' with continuous outcome data; inverse variance weighting is used
#' for pooling.
#'
#' @param n.e Number of observations in experimental group or an R object
#' created with \code{... |
901d54d55fb8f7015a3db05890e3d8143d5284856231e1f6c7f6190679f6287e | R | 75,546 | 1,727 | # Note, many of the functions below are implemented in the microbiomer-package.
# See here: https://github.com/wsteenhu/microbiomer
# Save/load function for 'heavy' objects
sl <- function(name, ..., overwrite = FALSE, dir_path = here::here("results", "RData", subdir_name)) {
# Possibility to add name as name or lite... |
9f3709d03df2397e272259b279019053dd517b3c01efb09be3108b8866869eb2 | R | 76,703 | 2,380 | #' Uncover gene modules and their regulatory programs from single-cell data
#'
#' Use the scRegClust algorithm to determine gene modules and their
#' regulatory programs from single-cell data.
#'
#' @param expression `p x n` matrix of pre-processed single cell expression
#' data with `p` rows of genes... |
5d0f89ac2e9d9fc1cbc440e60f4d74bf5d1c222769581fb511b44408144d902b | R | 78,466 | 1,141 | ---
title: "Plasma p-Tau181 and GFAP track 7T MR-based changes in Alzheimer’s disease"
author: "Laura Göschel"
date: "29.11.2023"
output:
pdf_document:
toc: yes
word_document:
toc: yes
html_document:
toc: yes
toc_float: yes
number_sections: yes
theme: paper
code_folding: ... |
a2245c3c44c61d909353799f7674e7a56e110736c5387a9e2db720226a587af5 | R | 78,700 | 2,074 | #' Update a meta-analysis object
#'
#' @description
#' Update an existing meta-analysis object.
#'
#' @param object An object of class \code{meta}.
#' @param data Dataset.
#' @param subset Subset.
#' @param studlab Study label.
#' @param exclude An optional vector specifying studies to exclude
#' from meta-analysis... |
ae47646f57e4e66b5704119b384d6a38aac889f7b11cead2f6c0a2348815d5a6 | R | 79,971 | 2,361 | #' Meta-analysis of binary outcome data
#'
#' @description
#' Calculation of common effect and random effects estimates (risk
#' ratio, odds ratio, risk difference, arcsine difference, or
#' diagnostic odds ratio) for meta-analyses with binary outcome
#' data. Mantel-Haenszel, inverse variance, Peto method, generalised... |
e9c2b2147c0292e5220c30485d1a92e7ad7e3f18e7e3fb293870c4912d856849 | R | 80,012 | 1,502 |
Cross validation of the fetal metamarkers
leave one out, generate fetal metamarkers, get accuracy for class annotations as num markers increases
Save list of top 200? genes, gene jaccard of all the gene lists, pairwise comparison. Trying to show the metamarkers are not changing
```{r}
library(Seurat)
library(dat... |
26d62a86dd32eb9745db8ae4f8e13a57fc593be2fd3a787dd98417c0af2591d8 | R | 80,136 | 1,949 | ---
title: "hovestadt_nature_2019_smartSeq2_QC_and_analysis"
author: "JJ"
date: "2023-03-02"
output: html_document
---
```{r graphical_output}
options(bitmapType='cairo-png') # this line of code needed BEFORE knitr code in chunk below
```
```{r setup, include=FALSE}
knitr::opts_chunk$set(dev = "png",
... |
ea392be8538121cdca37d59954d70105b6ca7c9b62c7eddc83ac62d9036653bb | R | 80,770 | 1,605 |
Generating organoid co-expression networks
```{r, setup, include=FALSE}
knitr::opts_knit$set(root.dir = '/home/werner/projects/meta_qc_organoid/code')
```
```{r}
library(Seurat)
library(reticulate)
library(knitr)
library(matrixStats)
library(data.table)
library(ggplot2)
library(MetaMarkers)
library(dplyr)
library(M... |
68c133899b396af703a969704c4f835b67817501f33d727b7531845d86e442df | R | 82,908 | 1,775 | if (!require(pacman)) {install.packages("pacman")}
pacman::p_load('this.path','arrow','magrittr','glue', 'scales', 'aqm',
'lme4', 'MASS', 'segmented', 'umap', 'Rtsne', 'rstatix',
'xtable','janitor','officer', 'gt', 'lemon', 'sjPlot',
'colorspace', 'ggeasy', 'ggforce', 'ggh4x... |
2a5c372e4516a9a061f7fccd6bd49ff3940af48dfd8ad42f03b2a8d9d2d35bb4 | R | 85,439 | 2,006 | #' Reads labels from a folder containing one or multiple CSVs with label data. rows correspond to frames of the recording and column(s) to label(s). for each sample a separate file is needed. headers of the columns correspond to label names used downstream.
#'
#' @param path a character with the path to the folder ... |
c4b4d4a4d03760c0555e16ecad77e8d7ace3eb3f77604e01a65262214317efd4 | R | 86,087 | 2,480 | #' Transform meta-analysis data from two arm-based formats into contrast-based
#' format
#'
#' @description
#' This function transforms data that are given in wide or long arm-based
#' format (e.g. input format for WinBUGS) to a contrast-based format that is
#' needed as input to R functions \code{\link{metabin}}, \co... |
f83ebe555b347541689137321f2fbebc37b009ef0b9249a235faaded534ccb2a | R | 87,194 | 1,981 |
preprocessing of the linnarsson first trimester single cell data
1.6 million cells
https://github.com/linnarsson-lab/developing-human-brain/
Supp table 2 for cluster level metadata
```{r}
library(rhdf5)
library(Seurat)
library(matrixStats)
library(dplyr)
library(ggplot2)
library(MetaMarkers)
```
```{r}
data_file = ... |
5e62644905b1776ae0992fc9dc20e6b7aa3cc1d86aa670e894a3fb6b40552bd7 | R | 89,479 | 1,167 | ---
title: "Efficacy of disease-modifying treatment on spinal cord lesion formation in relapse-onset multiple sclerosis. An MSBase registry study."
author: "Daniel Kreiter, Tomas Kalincik, Raymond Hupperts, Francesco Patti, Daniele Spitaleri, Matteo Foschi, Andrea Surcinelle, Davide Maimome, Bassem Yamout, Samia J. Kho... |
e7c934b37248bf34d398ade73580dffce42c9d33b65c7d9f0d69e6fad1562331 | R | 92,929 | 2,463 | # Filename: adni_ver2.R
# setwd("/wynton/group/andrews/users/evelasquez/CAIDE_APOE/scripts/ADNI")
setwd("~/gitcode/CAIDE_APOE")
library("tidyverse")
library("missForest")
library("glue")
library("dplyr")
library("readxl")
library("readr")
library("webshot2")
library("ggplot2")
library("gtsummary")
library("broom")
lib... |
94dd89a0659ab785c4bda04ce8774d10541fcbba8b20b0258ed057e6d727b7b4 | R | 97,504 | 2,328 | #' Reads labels from a folder containing one or multiple CSVs with label data. rows correspond to frames of the recording and column(s) to label(s). for each sample a separate file is needed. headers of the columns correspond to label names used downstream.
#'
#' @param path a character with the path to the folder ... |
c75083597d308bad10591c845f41a92b8dbebb8ee87709d85ff7ffbcfa6d78fe | R | 99,427 | 2,642 | ---
title: "INTEGRATE_ONS76-CBO_ONS76-2D_ONS76-SPHER_CBO_seurat_50K"
author: "JJ"
date: "29/08/2022"
output: html_document
---
```{r graphical_output}
options(bitmapType='cairo-png') # this line of code needed BEFORE knitr code in chunk below
```
```{r setup, include=FALSE}
knitr::opts_chunk$set(dev = "png",
... |
c5e710c986310a04c65d98426d03c525f26a1e49649eac713fc7dd65a60c43ad | R | 100,206 | 2,091 | Sys.which("make")
#Step 1 Load All packages first
rm(list=ls())
# ## Loading library
library("readxl")
library(dplyr)
library(metafor)
NDDx_comparision_Rawdata <- read_excel ("DataExtraction_NDDx_Pairs.xlsx")
View(NDDx_comparision_Rawdata)
## converting EF direction column from string to numeric type, and save data ... |
0da4309a04905122cd6003b249fb7ba487b3a9bed1ebe8c275437530e47710e6 | R | 101,461 | 2,179 | Sys.which("make")
#Step 1 Load All packages first
rm(list=ls())
## Loading library
library(robumeta)
library("readxl")
library(stringr)
library(dplyr)
library(metafor)
library(effsize)
library("writexl")
# library("xlsx")
library(fishmethods)
library(here)
library(janitor)
library(purrr)
#load other libraries if ne... |
35825efbb6ca8902ec48c9b704e3c18372e76ff87d8345bf170e5490c409dedb | R | 107,991 | 2,232 | ---
title: "QC and decontam for TEBC faecal microbiome data"
author:
- "Kadi Vaher"
- "Based on QC script used in the Malawi microbiota workshop"
date: '`r Sys.Date()`'
output: html_document
---
```{r setup, include=F, message=F}
library(tidyverse)
library(here)
library(phyloseq)
library(decontam)
library(RCol... |
ee9d99f5f4fb44c897197d87f5925829d2ea7a9fff60eee4c1c80b2a3885d397 | R | 108,438 | 2,054 |
Testing the fetal conservation of fetal data
First look at the unannotated datasets
Then do the annotated, leave one out and reaggregate the coexpression, then test
```{r}
library(Seurat)
library(data.table)
library(ggplot2)
library(MetaMarkers)
library(dplyr)
library(MetBrewer)
library(ComplexHeatmap)
library(cir... |
a4d31df6e02b2ddffc26264a6aa682c184637a32b01a903a7be555a4b1d83a03 | R | 108,501 | 1,594 | ---
title: "Plasma p-Tau181 and GFAP track 7T MR-based changes in Alzheimer’s disease"
author: "Laura Göschel"
date: "14.08.2024"
output:
pdf_document:
toc: yes
word_document:
toc: yes
html_document:
toc: yes
toc_float: yes
number_sections: yes
theme: paper
code_folding: ... |
a889133e6d2d126c1ca74254ed5117d557c5d96e16a4450fd077b7ca9e4120e4 | R | 113,571 | 3,216 | #' Generic inverse variance meta-analysis
#'
#' @description
#' Common effect and random effects meta-analysis based on estimates
#' (e.g. log hazard ratios) and their standard errors. The inverse
#' variance method is used for pooling.
#'
#' Three-level random effects meta-analysis (Van den Noortgate et al., 2013) is
... |
968116f080553486948455a91ce7339bbdddd469825ec4b2a820e48d21be5464 | R | 115,825 | 1,724 | library(ggplot2)
library(limma)
library(edgeR)
input_dir <- "/media/Scratch_SSD_Voyager/sammi/RNA_editing/edit_output_OD_v1/"
edit_table <- list()
all_edit_table <- list.files(input_dir)
for (i in all_edit_table){
edit_table_tmp <- read.table(paste0(input_dir,i), header = 1)
edit_table_tmp$Subject <- sapply(... |
480b7788e90f77a9fe8ecbf42ade45b09a2ecd9da8efc5e9463aae00043eac91 | R | 116,249 | 3,409 |
#' Title
#'
#' @param net
#' @param folder
#'
#' @return
#' @export
#'
#' @examples
milkNet = function(net,folder){
netName = NULL
if(typeof(net) == "character"){
netName = gsub(".rds","",basename(net))
stopifnot(file.exists(net))
net = readRDS(net)
}
if(is.null(netName))
netName = gsub(".rds... |
e0256efe43915516238a6936865d0b334c7f12af060b3bc92ba67bf323789491 | R | 117,403 | 1,758 | # read in sc and sn site specific editing
# carry out a bunch of qc
# benchmark # of sites by repeat and genic location for each cell type
# v2 adds in some normalization: norm by cell count, norm by reads, norm by cell count & reads
# for i in /media/NAS1/Sammi_NAS1/RNA_editing_Archive/dedupped_bam/dedupped_bam_H1_2... |
74a362362e43e120724affa3b8e4be90e359df1817b0de81203bec728aa012ba | R | 122,044 | 3,221 | #' Reads DLC Tracking data from a csv file and returns a TrackingData object
#'
#' @param file path to a DLC tracking .csv file
#' @param fps frames per second of the recording. required to enable time resolved metrics
#' @return An object of type TrackingData
#' @examples
#' ReadDLCDataFromCSV("DLCData/Data.csv... |
4f44263464cd51fb43aeec083ad9792d66bafe2366c672ce2c702d7bc71d367f | R | 125,528 | 2,202 | ---
title: "Attention EF Paper"
author: "CarterSun"
date: "`r Sys.Date()`"
output:
html_document: default
word_document: default
pdf_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE,message=FALSE,warning=FALSE)
```
# - - - - - - - - - - - - - - -
# - PREPARE WORKSPACE ---
# ... |
147ef39b307b9e8cfbb80db981e848c3a7d5dba90e83886300c68cf9a9c8f5e4 | R | 125,820 | 3,297 | #' Reads DLC Tracking data from a csv file and returns a TrackingData object
#'
#' @param file path to a DLC tracking .csv file
#' @param fps frames per second of the recording. required to enable time resolved metrics
#' @return An object of type TrackingData
#' @examples
#' ReadDLCDataFromCSV("DLCData/Data.csv... |
b80930a846c4e3f5cb5c8e86f9e9411485b6cb0a16820880614cdfddfdf9b6e6 | R | 126,193 | 2,464 |
conservation of fetal co-expression within neural organoids
```{r}
library(Seurat)
library(data.table)
library(ggplot2)
library(MetaMarkers)
library(dplyr)
library(MetBrewer)
library(ComplexHeatmap)
library(circlize)
library(EGAD)
library(parallel)
```
Fetal data
```{r}
human_fetal_dataset_names = c( 'linnarsson... |
bf65d0fcfe614e332680791498dce5add621b58efc5524c6b26db68c54e4bf7f | R | 133,879 | 3,524 | # Internal helper: collect parameters from one or more nn_module instances into a
# flat unnamed list of tensors, skipping NULL entries and modules with no params.
.collect_params <- function(...) {
params <- list()
for (mod in list(...)) {
if (!is.null(mod)) {
p <- unname(mod$parameters)
if (length... |
f27f9c850e991dd1bfe8893d2cd3650332fa3d3e55ac4332810c19a1dc9b0303 | R | 140,567 | 4,630 | ---
title: "`r analysis_title`"
subtitle: "`r analysis_subtitle`"
output:
html_document:
toc: true
toc_float: true
number_sections: true
theme: united
---
```{r setup, echo=FALSE, warning=FALSE, message=FALSE}
# create subfolder for ML tables
dir.create(file.path(results_dir, chosen_FI... |
79f5ccd479b94e128efcf5d53388882e839674c273f68dadfe16fe989aab10bd | R | 157,247 | 2,760 | ---
title: "Werner and Gillis 2024 figure plots and code"
author: "Jonathan Werner"
date: "2024-08-27"
output: github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = T)
```
This markdown file contains the code for generating all plots for the publication: Werner and Gillis, Meta-analysis of scR... |
9a8e9fdf030730bc92bf83e5060edadc6619090ebecfb2009f09b1180d8a1ad8 | R | 167,871 | 3,552 | ##################################################################
# README #
#
# Helper functions to streamline the QC and covariate analysis
#
# can be used with the output from step2 or step3
#
# I STRONGLY RECOMMEND RUNNING THIS TO AN EMPTY DIR AS
# IT ISN'T GUARRANTEED THAT OLD RESULTS ARE OVERWRITTEN
#
# If you ... |
b60204d78b45336dc95ad0ff15b8cefedd323f0f802fd15faab797318d62ad19 | R | 169,554 | 3,583 | ##################################################################
# README
#
# Helper functions to streamline the QC and covariate analysis
#
# can be used with the output from step2 or step3
#
# I STRONGLY RECOMMEND RUNNING THIS TO AN EMPTY DIR AS
# IT ISN'T GUARRANTEED THAT OLD RESULTS ARE OVERWRITTEN
#
# If you ge... |
b934516767750dd77a4dc21c0e3d59bc0deffed78561396a24d0fd3bc15d504d | R | 200,000 | 3,714 | #-----------------------------------SETUP------------------------------
#Study 1 Figures
#HCP, HCPD, and NSD datasets
#Written by M. Peterson under MIT License 2023
#Nielsen Brain and Behavior Lab
#load libraries
library(mosaic)
library(dplyr)
library(ggpubr)
library(broom)
library(tidyverse)
library(rst... |
c50698d438355cd7a33564a04eb9b5af477dd20e69277a83d80c1fb87acf4c7d | R | 200,000 | 5,726 | #' Forest plot to display the result of a meta-analysis
#'
#' @description
#' Draw a forest plot (using grid graphics system) in the active
#' graphics window or store the forest plot in a file.
#'
#' @aliases forest forest.meta
#'
#' @param x An object of class \code{meta}.
#' @param sortvar An optional vector used t... |
c8614d7a1943ce58849b791584fa2d71cab161d5a1ee983384f6b1a52e3fc8bf | R | 200,000 | 7,433 | #####headwidth comparison of OW and S bees ####
rm(list=ls())
##set wd where inputs are
setwd("directory")
getwd()
#import data of headwidth of each bee
##sample indicates whether they are OW or S
##ID= nest their id
##3 with W020 id all came from same nest
hw <- read.csv("headwidth.csv", header=T)
hw
#compare headw... |
1c9dd879db87ea7d8febd99ea3bf01a30c0762df30a71fffec88129e65dc7dd4 | Rust | 44 | 3 | pub mod scene;
pub mod ssim;
pub mod train;
|
1856b872f9246ba77afa4cbcc26aef36ce187bf46a2e70e5bd246b508c76ba85 | Rust | 107 | 6 | //! HTTP transport for coglet using axum.
mod routes;
mod server;
pub use server::{ServerConfig, serve};
|
c687a6b44b6dee7f119c3697baa3e03b9864558732b7d4ecad22affc7b173364 | Rust | 210 | 8 | //! Transport layer for coglet.
//!
//! Currently provides HTTP transport via axum. Future transports
//! (gRPC, bnet) will be added as separate submodules.
pub mod http;
pub use http::{ServerConfig, serve};
|
3e07b2f3559d9e4f41f9e967b7413dce91bc86d2923f8c2dc51474dd559ade9c | Rust | 225 | 11 | use miette::IntoDiagnostic;
fn main() -> miette::Result<()> {
brush_wgsl::build_modules(
&["src/shaders/wg.wgsl"],
&[],
"src/shaders",
"src/shaders/mod.rs",
)
.into_diagnostic()
}
|
c3726d57fe8fa44127cd8fc81b7a5c15afd37d44ca99076db388abd40df5007e | Rust | 240 | 13 | #![allow(dead_code)]
#![allow(clippy::too_many_arguments)]
#![allow(clippy::single_range_in_vec_init)]
mod burn_texture;
mod orbit_controls;
mod splat_import;
#[cfg(feature = "rerun")]
mod visualize;
pub mod viewer;
pub mod wgpu_config;
|
3ba32d24fc171029b6dd409fdd6eab4afaabf5d3cbaa9a36f8137c0b17580879 | Rust | 382 | 11 | //! `bam2nuc` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::bam2nuc::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimalloc::MiMall... |
c0ea278617236da9ff57ca87a3b66d78a074f45ecdcd1100d91d8ac5a08de015 | Rust | 382 | 11 | //! `bismark` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::aligner::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimalloc::MiMall... |
2e7bf68fb30c809e887a1a46a72c7eafd220e6951fbf88d5ad74608f11a11be4 | Rust | 388 | 11 | //! `bismark2report` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::report::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimalloc::... |
196f4dba370f617b0ba7e93a1154d21ec1695df58e53163a3da7bf4b049cd631 | Rust | 390 | 11 | //! `bismark2summary` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::summary::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimalloc... |
c2598f21b4a646134d8d06d7c3776e3b0f29bf7e010acb556f40c40336418fe7 | Rust | 392 | 11 | //! `deduplicate_bismark` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::dedup::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimall... |
d4d6a8a8ddd7c45b0564639c8858f2dce58736fefb88cb59886a22da118a51e0 | Rust | 392 | 11 | //! `bismark2bedGraph` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::bedgraph::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mimall... |
ac36a0ead7a919b79480370031431712f0ee4d76ca830c437a203a5ed75446e2 | Rust | 396 | 11 | //! `NOMe_filtering` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::nome_filtering::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMalloc = mi... |
de175464f48ff07b76f937d62158cd856d560b864afa2323b4418986ad545cb5 | Rust | 402 | 11 | //! `coverage2cytosine` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::coverage2cytosine::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMallo... |
3c95294df4f24ecfa28e30e6ac440f10953780111aebd84709359c5dede7398d | Rust | 405 | 11 | //! `bismark_genome_preparation` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::genome_prep::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiMa... |
0318ffc21d5559bd7595cb3b5905b901253aa5e0bdaa46ad82b8a0b3de0502eb | Rust | 406 | 11 | //! `bismark_methylation_extractor` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::extractor::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::MiM... |
0af654a6cf01342b44af8e3653c34842502890c2d57bfb728987c2f7ac366aa9 | Rust | 409 | 11 | //! `filter_non_conversion` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::filter_nonconversion::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimalloc::... |
a518926c3b85bebd31268d0e6014a51c44ac2c819de10b6f8c91c17323e2d5fe | Rust | 411 | 15 | use miette::IntoDiagnostic;
fn main() -> miette::Result<()> {
brush_wgsl::build_modules(
&[
"src/shaders/prefix_sum_add_scanned_sums.wgsl",
"src/shaders/prefix_sum_scan_sums.wgsl",
"src/shaders/prefix_sum_scan.wgsl",
],
&["src/shaders/prefix_sum_helpers.w... |
ada3e1f4b3be8c1f0e00f648e0e5ea6b01b5b48097bc5395cc867e12770bbda1 | Rust | 414 | 11 | //! `methylation_consistency` — one of the binaries installed by `cargo install bismark`.
//! Thin wrapper over [`bismark::methylation_consistency::run_main`]; byte-identical to that tool's own
//! binary (each sets the same multithreaded allocator).
use std::process::ExitCode;
#[global_allocator]
static GLOBAL: mimal... |
32e6ce606420884982a307c1f3f061f05f442e89b7115c38297e8e984921c8ef | Rust | 421 | 13 | //! IPC bridge for coglet parent-worker communication.
//!
//! This module provides the wire protocol and codec for communication between
//! the coglet orchestrator (parent) and worker subprocess.
//!
//! # Architecture
//!
//! - **protocol**: Message types (ControlRequest/Response, SlotRequest/Response)
//! - **codec... |
7930bfbc709bb5bb35990c1f0a77c8fd930e064b4ef9b1ce91292f028434d341 | Rust | 459 | 17 | use miette::IntoDiagnostic;
fn main() -> miette::Result<()> {
brush_wgsl::build_modules(
&[
"src/shaders/sort_count.wgsl",
"src/shaders/sort_reduce.wgsl",
"src/shaders/sort_scan_add.wgsl",
"src/shaders/sort_scan.wgsl",
"src/shaders/sort_scatter.wg... |
ca187915a66c3bfc4d7a71a375fa309ea4091752412e41f2301778b3067e0ada | Rust | 517 | 18 | // TODO: This is rather gnarly, must be an easier way to do this.
use burn::{
prelude::Backend,
tensor::{Float, Tensor, TensorData},
};
use safetensors::tensor::TensorView;
fn float_from_u8(data: &[u8]) -> Vec<f32> {
bytemuck::cast_slice(data).to_vec()
}
pub(crate) fn safetensor_to_burn<B: Backend, const ... |
d53c8e030bfe6b1090218b1f0c1874aaf198cf7da9beccb63495b3b004bac2c8 | Rust | 558 | 16 | use eframe::egui_wgpu::WgpuConfiguration;
use std::sync::Arc;
pub fn get_config() -> WgpuConfiguration {
WgpuConfiguration {
device_descriptor: Arc::new(|adapter| wgpu::DeviceDescriptor {
label: Some("egui+burn wgpu device"),
required_features: adapter.features(),
requir... |
c5b8e666312cbf82ea9bb952efd1b1a85d46c00e853463a5f59bd77bfe6102ad | Rust | 582 | 20 | //! Phase A sanity checks: crate builds, version string + error Display work.
use bismark::bam2nuc::error::BismarkBam2nucError;
use bismark::bam2nuc::version_string;
#[test]
fn version_string_has_binary_name_and_platform() {
let v = version_string();
assert!(
v.starts_with("bam2nuc (Bismark Rust suite... |
6a66fb425421fb4730a214f26e5743e22c991573d4192f21b6c603a2ccd1fa03 | Rust | 634 | 20 | use miette::IntoDiagnostic;
fn main() -> miette::Result<()> {
brush_wgsl::build_modules(
&[
"src/shaders/project_forward.wgsl",
"src/shaders/project_visible.wgsl",
"src/shaders/map_gaussian_to_intersects.wgsl",
"src/shaders/get_tile_bin_edges.wgsl",
... |
3cdc70076aae08d93fb3bb5a271180d573a763ee30495ca17913bd3738d51186 | Rust | 728 | 15 | use super::shaders::{
get_tile_bin_edges, map_gaussian_to_intersects, project_backwards, project_forward,
project_visible, rasterize, rasterize_backwards,
};
use crate::shaders::gather_grads;
use brush_kernel::kernel_source_gen;
kernel_source_gen!(ProjectSplats {}, project_forward);
kernel_source_gen!(ProjectV... |
a79af1adb9e26bac9a5040cf6261c5cb5751bf7f6e53c98e8efb36f05434c045 | Rust | 747 | 28 | //! Minimal STDERR logger. Diagnostics are never part of the byte-identity
//! gate; `--verbose` gates the extra detail.
/// Tiny logger: `note` always prints (Perl `warn`-level); `info` only with
/// `--verbose` (Perl `$verbose and print`).
#[derive(Debug, Clone, Copy)]
pub struct Logger {
verbose: bool,
}
impl ... |
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