sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c02ac9092450d3316cbef90288e7b6d2e4c817bdbf0cb861be31a08b3906c626 | R | 32,496 | 1,019 | ---
title: "220606_lung_cancer_signaturesearch"
author: "Jennifer Fisher"
date: "6/6/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Determine disease signatures for all the methods and... |
3c4bc0d205939ce5c42b618e65e1cc1a58fcfc12265a385ecc509e7ae6e58e20 | R | 32,690 | 912 | ---
title: "220503_PRISM_top_candidates_plotting"
author: "Jennifer Fisher"
date: "5/3/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
The DepMap/PRISM’s primary pooled drug screens we... |
7d7ed5e3f2a246a01bc4a9f12f57ac033a7c051705812b316f01d7b27bfdfb64 | R | 33,280 | 1,021 | ---
title: "220601_Liver_SignatureSearch"
author: "Jennifer Fisher"
date: "6/1/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Determine disease signatures for all the methods and condu... |
63d3e5195cb466aa116bc9ffe29ffdbbba243b69890204f3cc651ee243c8bcc4 | R | 33,574 | 769 | ---
title: "Alevin-Fry vs. Cellranger Comparison"
author: "Ally Hawkins for CCDL"
output:
html_notebook:
toc: true
toc_float: true
---
In this notebook, we specifically compare using Alevin-fry with cellranger to quantify both single-cell and single-nuclei RNA seq data.
For cellranger, we are using the de... |
23b4a002e208abcbd8e370bc1f5b13b196877b19d26408ec7a091dda2bfc86b5 | R | 33,625 | 1,192 | ---
title: "Retina ATACseq - Figures for paper"
output:
html_document:
df_print: paged
---
```{r global_options, include=FALSE}
knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE)
```
```{r, libraries}
library(tidyverse)
library(Signac)
library(Seurat)
library(JASPAR2020)
library(GenomeInfoDb)
li... |
f7bb31a16d5bfbe0ef4663fa29a48359da7c5e5251141a3171856cc493c27a0a | R | 33,693 | 760 | ## ---------------------------
##
## This script was created with R version 4.2.1 (2022-06-23)
##
##
## Title: Personalized identification and characterization of genome-wide gene expression differences
## between patient-matched intracranial and extracranial melanoma metastasis pairs
##
## Purpose of script: S... |
487d4aed97c6b893ba3e863dfa5eff9c7e208b8ec5ae768559d94f143d7f2296 | R | 33,813 | 849 | ################################################################################
# functionQuantiSwath.R 2.0.3 #
# Authors: Matthieu Lhotellier & Alexandre Sta (Institut Curie) #
# Contact: myproms@curie.fr ... |
b78c43f9c31726f3ff06dc8697cd10aff87930281134d4ec85faad5650056f57 | R | 33,957 | 657 | # Fit models for the main analysis. Analysis of signal features as as a function
# of age, sex, group, and cortical thickness.
#
# Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M.,
# Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor
# rhy... |
201c7f755b1899d97197a98d3e5ace37b20508386137ecc1e429fefa71d0463b | R | 34,115 | 402 | ######################################################################
#Outcome Variables:
######################################################################
library(mosaic)#for standardizing variables
barkley <- read.csv2('barkley_exec_func01.csv')
cols <- c("bdefs_calm_down_p", "bdefs_consequences_p", "bdefs_dis... |
fd07c4a6fbd61f5355008a65a683c4eef5994661a963346cd0510f2af98fb3d2 | R | 34,173 | 1,050 | ---
title: "220607_PAAD_SignatureSearch"
author: "Jennifer Fisher"
date: "6/7/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Conduct Signature Reversion on PAAD samples with both the ... |
9dacce875e61d1dfe42c21c3d49e0951210030748ba81f092a051a76ebe5e724 | R | 34,235 | 306 | # Rscript build_meco_sentitems.R /fs/project/schuler.77/meco/joint_fix_trimmed.rda ee
# Language codes: "du" "ee" "en" "fi" "ge" "gr" "he" "it" "ko" "no" "ru" "sp" "tr"
args <- commandArgs(trailingOnly=TRUE)
df <- get(load(args[1]))
df <- df[df$lang==args[2],]
# print(table(df$renamed_trial))
# quit()
# MECO needs som... |
fe04c9b6092c5f3d7ab0eff0a80f4decbc24d53ba6238931f94117743fe22834 | R | 34,445 | 1,124 | ---
title: "Connecting gene modules identified within different epilepsy cohorts"
author: "Liesbeth François"
date: "`r format(Sys.time(), '%B %d %Y')`"
output:
html_document:
self_contained: yes
fig_height: 6
fig_width: 8
keep_md: yes
number_sections: yes
theme: cerulean
toc: ye... |
2337388a65d1cae6af4fceb2c46da8a607b6557ed246f6ac8c605e7ff67451c6 | R | 34,567 | 922 | #################################################################################################################
#################################################################################################################
######
###### Title: pqtl_ms_make_fig5_figS5
######
###### Des... |
4451c529852704ba518d8bb6c7bb6f392ec8363689b8c806b18ef0968d4d110d | R | 35,192 | 778 | #
# Add GRN network analysis for either all cell types combined (preferred version) or for one of the dominating cell types (less preferred)
#
# Female GRN (Global nominally significant DEGs; N=758)
DEG_Global_Poisson_F <- read.csv("~/data/DEG_Global_Poisson_Female.csv", header=T, row.names=1)
dim(DEG_Global... |
8c5b60712b078e3193782a397a15c90a5d964946be8f8dd9b85d6a31b22ae11e | R | 35,378 | 914 | #THIS SCRIPT CONTAINS CUSTOM FUNCTIONS FOR THE DATA ANALYSIS (BEHAVIOR AND EPHYS)
#FROM THE PAPER
#KOVLAGINA ET AL. "Freezing responses during prolonged threat memory retrieval reflect trait-like anxiety endophenotypes in female and male inbred mice"
library(ggplot2)
library(emmeans)
library(car)
library(lme4)
librar... |
5f475c5d6395ff0325f737c71144cded01714bd3143528df611b609a011ccfb9 | R | 36,071 | 1,105 | library(sp)
library(rgdal)
library(lubridate)
library(sp)
library(ctmm)
library(sf)
library(rgeos)
load("~/RanSimFFT workspace.RData") #load precomputed OUF models
data=read.csv("C:/Users/salavi/Documents/FFT_Cleaned_Final.csv")
data$timestamp=as.POSIXct(as.character(data$timestamp),format="%Y-%m-%d %H:%M:%S... |
494476ec16f92c79d9c282642f99540ed9729989f7336b1b96074338fb2d2783 | R | 36,099 | 691 | ---
title: "Spatiotemporal immune atlas of the first clinical-grade, gene-edited pig-to-human kidney xenotransplant"
subtitle: "Downstream Analysis of CD45+ immune cells (General analytics pipeline exemplified herein)"
output:
rmdformats::readthedown:
self_contained: true
thumbnails: false
lightbox: true
... |
d0a4a98e314315825f4bdeeede86b113e6a62591940e80c32e59a09e34affa0f | R | 36,813 | 760 | ---
title: "230511_more_gbm_drug_testing_res"
author: "Jennifer Fisher"
date: '2023-05-11'
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Plot the results from the cell titer assay. There wer... |
77f606b843cf90e3bef7842eec08b87f00afb85ddf014703d80d268ebf7cc434 | R | 36,909 | 315 | # Rscript preprocess_meco.R /fs/project/schuler.77/meco/joint_fix_trimmed.rda /fs/project/schuler.77/meco/joint_l1_acc_breakdown.rda en
# Language codes: "du" "ee" "en" "fi" "ge" "gr" "he" "it" "ko" "no" "ru" "sp" "tr"
# library(hash)
args <- commandArgs(trailingOnly=TRUE)
df <- get(load(args[1]))
acc_df <- get(load(ar... |
0a94dd4d310404d30f85a83ffe78fc342dc47eeebe1990b753f2bdaab6eb711c | R | 36,938 | 763 | ################################################################################
# AnalysisDiffLimma.R 4.5.5 #
# Authors: Matthieu Lhotellier & Alexandre Sta & Isabel Brito (Institut Curie) #
# Contact: myproms@curie.fr ... |
48da0cc653d714c4d5aefa6256178a095ea7461be004f19d11bb21e54acdc434 | R | 36,966 | 777 | #!/usr/bin/env Rscript
################################################################################
# aLFQ.R 1.0.5 #
# Authors: Victor Laigle (Institut Curie) #
# Contact: myproms@curie.fr ... |
f7173aa2b01ae4ca8b9c23cfba931697205ac17f84500c48173c24050d300a90 | R | 37,834 | 660 | # Paper : Detecting subtle transcriptomic perturbations induced by lncRNAs Knock-Down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network
# Code : R script to load, manipulate and prepare the count matrices for the SSAE
# Author : Marin Truchi
#------------------------------------... |
fb833b3d4b24fed0b1240675381b2b5a816316879b7b7865adc59cc7c3e67b3f | R | 38,924 | 1,145 | ################################################################################
# motifx-functions.R 1.0.0 #
# Authors: Stephane Liva #
# Contact: myproms@curie.fr #
################################... |
8d795271e8287cc0bdfa5f773e59bf435ef05ba9c82efd661ac3a02b78643d42 | R | 39,439 | 970 | sep_pcf <- function(res){
new <- as.data.frame(t(vapply(seq_len(nrow(res)), function(i)
unlist(strsplit(as.character(res$set[i]), "__")),
FUN.VALUE=character(3))), stringsAsFactors=FALSE)
colnames(new) <- c("pert", "cell", "type")
res <- cbind(new, res[,-1])
return(res)
}
# readHDF5mat... |
acd75db863de27f265d2b25155f4771ba32ae2f67e592afa28f3f01878904c26 | R | 39,543 | 882 | ########################################################
#
# Commonly used methods for LME regressions
#
########################################################
'%ni%' <- Negate('%in%')
# Requires the optparse library
processLMEArgs <- function() {
library(optparse)
opt_list <- list(
make_option(c('-... |
1090d12c6989a9e77d6e52f02f6efea45d814583cfe2aa4966f823959d20abb5 | R | 40,275 | 927 | ########################################################
#
# Commonly used methods for LME regressions
#
########################################################
'%ni%' <- Negate('%in%')
# Requires the optparse library
processLMEArgs <- function() {
library(optparse)
opt_list <- list(
make_option(c('-... |
4cea8fac88bfc4171a0ae3b2374b4f611b836312b816a2c0089a2de3e65fe2db | R | 40,456 | 994 |
figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\figures_structure_manipulations\\", base_output_path)
dir.create(base_output_path)
dir.cre... |
fddfe38cdf6edb51ffd624c0a57862560c36ecef7d6b33390fa55af2ea268e2b | R | 42,893 | 996 | ---
title: "220728_plier_recount3_wo_gtex_tcga"
author: "Jennifer Fisher"
date: "7/28/2022"
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Conducting Dimension reduction for Transfer learnin... |
47374154fbb9a708d948deac7c0daf10b8cfdb3c8bce37d0d5bfaf8debd655c1 | R | 43,111 | 1,331 | ---
title: "Pipeline_For GeoMX_Data_Analysis"
author: "Thomas Goralski"
date: '2022-07-22'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
This pipeline is intended for expedient analysis of raw data from Nanostring's GeoMx spatial transcriptomics platform.
The followin... |
4889f27062170e8f5396847cfdcb3eae724d1a2282457b3ec5c2ffe44b2c0a9c | R | 43,374 | 971 | # exploring hemispheric age predictions
# updated: 02.11.2023 adding sex stratification
## PREP ####
# packages
#install.packages("afex")
#install.packages("tidyquant")
library(tidyquant)
#install.packages("FSA")
library(FSA)
library(afex)
library(effects)
library(dplyr)
library(reshape)
library(ggplot2)
library(tidy... |
8e58114b2d63b89cd7c06812a7699cac3c3d6c471c29d936608b31147247423b | R | 43,538 | 1,366 | ---
title: "Exploratory analysis of principal sensory trigeminal nucleus and ventrobasal thalamus"
author: "Evgenii O. Tretiakov"
date: "`r Sys.Date()`"
output:
workflowr::wflow_html:
toc: true
toc_float: yes
theme: cosmo
highlight: textmate
code_folding: hide
df_print: paged
---
```{r setup,... |
28c06bd381dae37a5dea4d6b09dbf019d36271aa293500708679db0019756de7 | R | 43,788 | 766 | library("Seurat")
library("infercnv")
library("dplyr")
library("ggplot2")
library("RColorBrewer")
library("ggrepel")
####################################################################################
############ copy number variation for single cells ####################
#######################... |
7be2d8694d7a7e08c4f945bcb18fb843bf9ad914e156ad0e9cedb1614f838514 | R | 43,873 | 1,834 | ---
output:
word_document: default
pdf_document: default
html_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r}
library(EnvStats)
require(ggplot2)
require(car)
require(ggeffects)
require(emmeans)
require(lme4)
require(MuMIn)
require(coefplot)
require(nortest)
requir... |
16168ecf74d2f1da17add3a97e6495f0b354c9d2097d0d1608dbf856360b382e | R | 44,525 | 922 | ###################neurons#############################
rm(list = ls())
options(stringsAsFactors = F)
library(dplyr)
library(DESeq2)
library(umap)
library(ggplot2)
setwd("~/Documents/Virginia Tech/Project_4_VCU_postmortem_SCZ/RNA_DEseq/UCSD_gtf/")
factors = read.csv('metadata_RNA_neuron.csv')
row.names(factors) = facto... |
4b86a37606d8869c1979a2668e9d450faf23b68c6de281064cebedf32d535436 | R | 45,963 | 1,311 | ---
title: "Brain Heatmap Shiny Interface"
author: "Daniella DeWeerd, Noah Lubben, and Zach Madaj"
output:
html_document:
code_folding: hide
code_download: no
toc: yes
toc_float: yes
runtime: shiny
resource_files:
- Raw_data.rds
- data_1.fst
- data_2.fst
- data_3.fst
- data_4.fst
- data_5.fst
- data... |
8c0fb3032704fc6c13bf88cee1231390ba9cea6f919b2c56d93a2df4c7ada867 | R | 46,950 | 1,028 | ---
title: "Script Cytokines Metadata"
output: html_notebook
---
# Setup
## Load packages
```{r setup}
library(ggplot2)
library(Cairo)
library(ggsci)
library(ggsignif)
library(googlesheets4)
library(googledrive)
library(gtools)
library(tidyverse)
library(readxl)
library(lubridate)
library(pheatmap)
library(RC... |
7269a1adf2f04b9c8d483bd1c3671d35cb83570d4fef9abc9b290d07407978a7 | R | 47,731 | 919 | # The gene expression components are calculated and validated, and correlations between gene expressions and g-morphometry profiles are calculated.
R
library(ggplot2)
library(caret)
library(tidyverse)
library(psych)
library(tidyverse)
library(readr)
library(readxl)
library(ggplot2)
library(factoextra)
library(ggseg3d)... |
7f0a0cd308c22693c3bc5cde1cb9798d149a50d779cf3b55a03a65b15fc75f03 | R | 49,200 | 1,072 | ##############################neuron###########
############preparation##############
library(dplyr)
library(DESeq2)
library(umap)
library(ggplot2)
rm(list = ls())
options(stringsAsFactors = F)
setwd("~/Documents/Virginia Tech/Project_4_VCU_postmortem_SCZ/ChIP-seq_differential/enhancer_count/cofactors/")
factors = read... |
84290a032ecb472ee4a89df6a8faf30c24ba776fd71c8aa868f652e72e034faa | R | 49,211 | 1,069 | ##############################neuron###########
############preparation##############
library(dplyr)
library(DESeq2)
library(umap)
library(ggplot2)
rm(list = ls())
options(stringsAsFactors = F)
setwd("~/Documents/Virginia Tech/Project_4_VCU_postmortem_SCZ/ChIP-seq_differential/promoter_count/cofactors/")
factors = read... |
17acb1b908cd5b895182c08c57b84027a399fd14a5bc79792493daa769ca068c | R | 49,640 | 1,536 | library("philentropy")
library("RColorBrewer")
library("tidyverse")
library("intRinsic")
library("dbscan")
library("cowplot")
library("pheatmap")
library("reticulate")
library("testit")
library("dplyr")
library("plyr")
library("OneR")
library("stringr")
library("R.matlab")
library("ggplot2")
library('latex2exp')
librar... |
778f63de55af0a840abd7a6cc01219116d36c70dbfd2fabf449ce02818f4701a | R | 52,084 | 995 | ---
title: "FC Development Main Figures"
author: "Audrey Luo"
output:
html_document:
highlight: haddock
code_folding: hide
number_sections: no
theme: lumen
toc: yes
toc_depth: 4
toc_float: yes
pdf_document:
number_sections: no
toc: yes
toc_depth: '4'
word_document:
toc... |
21b6acb3d24728a0c4b2b2333c5966d955fa393b023ca9dec39a765cc1dac084 | R | 52,300 | 1,383 | #################################################################################################################
#################################################################################################################
######
###### Title: pqtl_ms_make_fig4_figS4
######
###### Des... |
bbfd5d153d02ea05a725a22080eecd52394501d90fff3114d056c72448c54497 | R | 54,240 | 1,151 | setwd("~/VASC/GerritsSmith/NicheNet_wPVMAstro/")
library(nichenetr)
library(Seurat)
library(tidyverse)
seuratObj<-qs::qread( '../vasc_PVM_Astro_NicheNet.qs')
############ ############ ############ ############ ############ ############ ############
############ ############ ############ ############ ##########... |
8b3c5f5cfb049835e2b814c3cefcd7a5b112c701a5858bbefa7c5de059deaaed | R | 54,309 | 969 | library(Seurat)
library(ggplot2)
library(clustree)
library(RColorBrewer)
library(dplyr)
library(scCustomize)
#######################################################################################
############## Merge snRNA profiles from all samples #######################
#########################... |
c2d859e1cacd406ceb698f84bd96f630eb6853d1c2b066fa326f1c01216bda2a | R | 56,084 | 949 | ---
title: "221130_gbm_drug_testing_res"
author: "Jennifer Fisher"
date: '2022-11-30'
output:
html_document:
toc: true
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# START
Goal/Purpose of operations:
Plot the results from the cell titer assay. There were tw... |
5c1e1c682f02b99b9923f4a4a71c1f58f38fa89801f0a2aab3288f447a4be399 | R | 56,723 | 1,382 | library(SingleCellExperiment)
library(Seurat)
library(ggplot2)
setwd("~/VASC/GerritsSmith")
GerritsSmith<-qs::qread('GerritsSmith_seurat.qs')
DimPlot(GerritsSmith, reduction = "UMAP_Liger", group.by = "clusters",label = F)+NoLegend()+
theme(axis.text.x = element_text(size = 15),axis.text.y = element_text(size = 1... |
90074b196a937dcd154f0e47c019d96a8dbf0a0eb04edfa88f9bc4c4cda495d1 | R | 57,814 | 1,213 | #' Check and Prepare the input data
#'
#' This function checks that the input data satisfy all the criteria for being used by the method.
#' It creates an object list that includes all the checked, normalized and prepared data.
#'
#' @param info Dataframe, two character columns, first has sample's IDs (have to match wi... |
d00c89d45d51b57abaa56942bbdc1fdb7f2782218296738a7b080a65589ef3df | R | 57,944 | 1,199 | ---
title: "Bap1 Analysis Separate Datasets"
author: "Sabine Schneider"
date: "June 09, 2023"
output: html_document
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(eval = FALSE)
```
Loading the necessary libraries
```{r load library, include=FALSE}
library(dplyr)
library(Matrix)
library(ggplot2)
library(Seur... |
5260368491e9172bcc34725500e61995bb3f82814d53e73eda4fac9c8e1cc4bb | R | 58,166 | 1,098 | setwd("/home/eteleeb/projects")
#library("iCluster")
library("iClusterPlus")
library(ggplot2)
library(gridExtra)
library(parallel)
library(reshape2)
library(data.table)
library(gplots)
library(ggsignif)
library(RColorBrewer)
library(lattice)
library(enrichR)
library(DESeq2)
library(edgeR)
#### run icluster on rosmap
... |
8e0bb6a2f4e2f223cec03e0d6b81698d0970820f14a6391985759e03bb77c4d7 | R | 58,382 | 470 | # The Desikan-Killiany regional-g associations are found for each cohort: UKB, STRADL and LBC1936, and then meta-analysed.
library(lavaan)
library(tidyverse)
library(ggplot2)
library(ggdist)
library(tidyquant)
library(reshape2)
library(gapminder)
library(patchwork)
library(gridExtra)
library(cowplot)
source("https://... |
d58658395419baab273112550a48f24833a01d483b4e85e03bfa8ed30caa221e | R | 58,732 | 564 | ######################################################################
######################################################################
#Age at TBI
######################################################################
######################################################################
Measures_agedummy <- le... |
cc42dd1bcd33ba32f1621ac9a96f8a2c6f543687d5cf9f5431935232d9f8005c | R | 62,538 | 1,881 | ---
title: "Helper_Functions_Pipeline"
author: "Thomas Goralski"
date: '2022-07-26'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
You must ensure that DCC files are the correct version, the following function will make that conversion. Only run if you need to. Must be... |
ff6ba5b8158e46f7e9ecc73ee653803020604fe1f869cb4155135ff2e6cf74fa | R | 63,384 | 1,073 | ### daily test data
DailyFFT <- read.csv("Daily_stats_for_Ben_2023_updated.csv")
EQ <- read.csv("EQ.csv")
Trackback <- read.csv("Trackback.csv")
fruit <- read.csv("Ro_fruitfall.csv")
DailyFFT2h=read.csv("Daily_stats_for_Ben_2023_2_hour_updated.csv")
DailyFFT4h=read.csv("Daily_stats_for_Ben_2023_4_hour_updated.csv... |
947e267704fd6a13ae03ab56eaa58eac14910ad63efd2aac483e4838729d4aeb | R | 64,069 | 1,817 | library(shiny)
library(readr)
library(stringr)
library(ggplot2)
library(dplyr)
library(pheatmap)
library(viridis)
library(tidyverse)
library(colourpicker)
library(grid)
library(gridExtra)
library(data.tree)
options(shiny.maxRequestSize = 300 * 1024^2)
#You shouldn't have to touch this
##### PAGE LAYOUT #####
ui <- ... |
b4aee74ec24b17763f725383bbcafdf6a9113780115b04e5df7a6e31358173b6 | R | 65,593 | 1,902 | ---
title: "COVID Microglia deepseq Analysis"
output:
html_document:
df_print: paged
---
# Setup
## Goals
1. Perform more final analysis with Seurat and SCVI integration to identify key COVID-associated clusters of microglia (and potentially CD8+ T cells)
## Import packages
```{r setup}
libra... |
83beeee4fa78844091a9a2df298ce7cd8c257319d38dfd2c0e0050573ade675c | R | 67,905 | 1,353 | ---
title: "E1 Lit review"
output: html_notebook
---
This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code.
Try executing this chunk by clicking the *Run* button within the chunk or by placing your cursor inside it and pressing ... |
8e2ebdcfef436e493e71c743df59e2400c3af452463d932bd95cb366ea7a0c65 | R | 69,676 | 1,286 | setwd("/home/eteleeb/projects")
#library("iCluster")
library("iClusterPlus")
library(ggplot2)
library(gridExtra)
library(parallel)
library(reshape2)
library(data.table)
library(gplots)
library(ggsignif)
library(lattice)
#### run icluster on MSBB region BM36
r <- 'BM36'
dir.create('omics_integration/MSBB')
dir.create(p... |
c5afc002d75271025912b217f57775a82254aebf2a18c1cd213c723544f58978 | R | 69,682 | 1,257 | library(rtracklayer)
library(readr)
library(dplyr)
library(cowplot)
library(stringr)
library(scico)
library(dplyr)
library(ggplot2)
library(tensorflow)
library(reticulate)
library(keras)
library(abind)
devtools::load_all('breaktools/')
source("00-utils.R")
# 1. Connect small gaps
# 2. Adjust using lower line of repli... |
2c2864c6ef35b533c6d50f7ad951c14a450b51cfe0fbed68e0428e81e8acf4a1 | R | 70,953 | 2,081 | ---
title: "Helper_Functions_Pipeline"
author: "Thomas Goralski"
date: '2022-07-26'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
You must ensure that DCC files are the correct version, the following function will make that conversion. Only run if you need to
```{r}
... |
ae370f6f091df0ef201415f6a9a6f4c2b6db50a7f9db0fa1b9b16e42f985ed51 | R | 71,357 | 2,120 | ---
title: "Systematic transcriptional investigation of epilepsy associated structural abnormalities: towards the identification of novel treatment targets"
subtitle: "Coregulated gene modules identification in mTORopathies (TSC, FCD 2a, FCD 2b)"
author: "Liesbeth François"
date: "`r format(Sys.time(), '%B %d %Y')`"
ou... |
b617d535856c40a255149edc4b0bc7b8269eb330db632ba1df8f52012e2fa97f | R | 71,447 | 1,761 |
figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\figures_structure_reward_anticipation\\", base_output_path)
dir.create(base_output_path)
d... |
f4db79c3608e1df72eab94aefa5ef42b5e4485d5afad20908b6e570468d84367 | R | 72,689 | 1,520 | #
# Check Marker Genes
#
library(Seurat) # Seurat_4.3.0
library(ggplot2) # ggplot2_3.4.2
library(cluster) # cluster_2.1.4
library(tidyverse) # tidyverse_2.0.0
library(dplyr) # dplyr_1.1.2
library(HGNChelper) # HGNChelper_0.8.1
library(openxlsx) # openxlsx_4.2.5.2
set.seed(1)
load("~/data/sctrans2.RData")
Default... |
cb0eab9572edaaa9c99ebe1a249f9826a3567b7f4bd0357587bebde80ea38fcf | R | 73,328 | 1,680 | #####################################################################################################
# #
# DIFFERENTIAL EXPRESSION ANALYSIS OF MALE AND FEMALE PHASIC AND SUSTAINED RESPONDERS #
# ... |
a8ede7c4760f2caf3bf43e21fb061f8ee594386db69ac1194add1b3a3b3fbcdb | R | 73,731 | 2,267 | ---
title: "Pipeline_For GeoMX_Data_Analysis"
author: "Thomas Goralski"
date: '2022-07-22'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
This pipeline is intended for expedient analysis of raw data from Nanostring's GeoMx spatial transcriptomics platform.
The followin... |
8c04ec04682b590c7ecd5fedd2c8de2eb0724247743b706ca3286f94f5ddec58 | R | 74,437 | 2,146 | ---
title: "Systematic transcriptional investigation of epilepsy associated structural abnormalities: towards the identification of novel treatment targets"
subtitle: "Coregulated gene modules identification in TSC"
author: "Liesbeth François"
date: "`r format(Sys.time(), '%B %d %Y')`"
output:
html_document:
... |
15f3bf2cc13fcf2c79841945af5a6a6fd4e96d2b77145fa515d62eb9326cbd5c | R | 76,468 | 1,525 | ---
title: "FC Development Supplementary Figures"
author: "Audrey Luo"
output:
html_document:
highlight: haddock
code_folding: hide
number_sections: no
theme: lumen
toc: yes
toc_depth: 4
toc_float: yes
pdf_document:
number_sections: no
toc: yes
toc_depth: '4'
word_document... |
a1f1bf57b7434c76fb9d4676d9a830133aea717a7c2824d5b83367193b141da6 | R | 78,696 | 1,754 | ############################################################################
# This script contains the code necessary for plotting behavioural and ephys data
#Reported in the manuscript "Freezing responses during prolonged threat memory retrieval reflect trait-like anxiety endophenotypes in female and male inbred mic... |
d3a0bfefa27b23fc325673b9f69a283ac51d912871c200a1cc3f685597aa92e7 | R | 78,947 | 2,207 | ---
title: "Systematic transcriptional investigation of epilepsy associated structural abnormalities: towards the identification of novel treatment targets"
subtitle: "Coregulated gene modules identification in FCD 2b"
author: "Liesbeth François"
date: "`r format(Sys.time(), '%B %d %Y')`"
output:
html_document:
... |
6bb576a4d9c27cf8aea4b6a3afb34383d511cb382c7eeca8943d49d4cf9447ce | R | 79,094 | 1,162 | #### ANALYSIS OF DATA FOR MANUSCRIPT: Becker, Fischer et al., 2022 ########
## last update: 08.2022 (almaxi@gmail.com)
#### Library
library(lme4)
library(lmerTest)
library(corrplot)
library(sjPlot)
library(sjmisc)
library(knitr)
library(magrittr)
library(sjlabelled)
library(sjmisc) ... |
e2eb3163e45a209c9895a88daa03e3c62478851a9be93b4ee73cf25e9813b971 | R | 79,603 | 1,993 | ---
title: "Longitudinal cytokine analysis"
output: html_notebook
---
# Setup
## Import packages
```{r setup}
library(tidyverse)
library(ggplot2)
library(ggsci)
library(ggsignif)
library(ggExtra)
library(ComplexHeatmap)
library(viridis)
library(broom)
library(Cairo)
library(rstatix)
library(ggrepel)
library(tidy... |
dd14e148c9bb478d340df9ab39461ee076fa62915f31187ee0bc7a76ea2b69d2 | R | 79,713 | 2,226 | ---
title: "Systematic transcriptional investigation of epilepsy associated structural abnormalities: towards the identification of novel treatment targets"
subtitle: "Coregulated gene modules identification in hippocampal sclerosis"
author: "Liesbeth François"
date: "`r format(Sys.time(), '%B %d %Y')`"
output:
htm... |
25f19462bdbfd584d8862f659f45f9a139f864ea65945a0e6a651b7ddd8efc20 | R | 80,186 | 1,743 |
figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\figures_structure_parameterization\\", base_output_path)
dir.create(base_output_path)
dir... |
1d45386968345639ca13e56097cb2dd49d43b58fba955eda2973e07407c29590 | R | 81,218 | 2,034 | ---
title: "Cytokine data import and cleaning (final)"
output:
html_document:
df_print: paged
---
# Setup
## Load packages
```{r setup, message=FALSE, warning=FALSE}
library(tidyverse, warn.conflicts = F)
library(ggplot2)
library(readxl)
library(ComplexHeatmap)
library(RColorBrewer)
library(ggsci)
library(... |
acd50560b70e507903430e43fad3ff8b3d0fc381473fee3dfc5788a2226a1bcd | R | 82,288 | 1,787 | ################################################################################
# FunctionLimma.R 5.3.0 #
# Authors: Matthieu Lhotellier & Alexandre Sta & Isabel Brito (Institut Curie) #
# Contact: myproms@curie.fr ... |
74b0677e61461275d766464aab4fd5ac24085d89c910cfd7ee6f29807724d6ab | R | 86,435 | 1,695 | ---
title: "Fitness assay"
output: html_notebook
---
This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code.
Try executing this chunk by clicking the *Run* button within the chunk or by placing your cursor inside it and pressing ... |
a58a11bc0abc5bf5789d3b0f9196e0344d61465f1f9118d01bef503f0361a21f | R | 91,832 | 2,389 | #' 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... |
46d88ebc67ef1c517bafba445f80750fed23cd56719d1136f719f65d96c96dbb | R | 97,875 | 2,212 | ##########################################################################################
# Gruffi - finding stressed cells.
##########################################################################################
# _____________________________________________________________________________________________ ---... |
cf46f81fe83b66e35de64011f11f10b3f313d1c2a688ed17049d3d70872ad49f | R | 107,121 | 2,466 |
figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\figures_structure_dynamics\\", base_output_path)
dir.create(base_output_path)
dir.create(o... |
38e0cbbfa2736082e7e509580046ed69787a6dbe62e69d4104ed48b7a87a72bc | R | 115,890 | 3,216 | library(shiny)
library(readr)
library(stringr)
library(ggplot2)
library(dplyr)
library(pheatmap)
library(viridis)
library(tidyverse)
library(colourpicker)
library(grid)
library(gridExtra)
library(data.tree)
options(shiny.maxRequestSize = 300 * 1024^2)
#You shouldn't have to touch this
##### PAGE LAYOUT #####
ui <- f... |
652b4c9487cdc85d13024204c99e3c5d64e1eb90eec3c5d066a5363882f1800e | R | 119,117 | 3,171 | figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\figures_structure_comparision\\", base_output_path)
dir.create(base_output_path)
dir.create... |
0db7799501d1b33c972bacca5f4f834305671f9841aeab9d1943c8004b02f576 | R | 123,419 | 2,692 | #functions for cancer signature reversion paper
# Jennifer Fisher
# jfisher7@uab.edu
# the following function was from the MultiPLIER paper and github. I just added a few print statements in function for updates during run
PLIERNewData_JLF <- function(exprs.mat, seed = 12345) {
# A wrapper function for applying PL... |
3d753cb8beb0c3e68d1556f2249cf012b8c14bc237ed05a3725d9af393592a9c | R | 130,477 | 2,322 | setwd("/home/eteleeb/projects")
#library("iCluster")
library("iClusterPlus")
library("lattice")
library("gplots")
library(ggplot2)
library(GenomicRanges)
library(gridExtra)
library(parallel)
library(reshape2)
library(data.table)
library(gplots)
library(ggsignif)
library(dplyr)
library(VennDiagram)
library(RColorBrewer)... |
67788dbdb4b2bb4aec0f9a430cec5aa622d23e1f2f7500446104ed74b8b49677 | R | 135,869 | 3,503 |
figures_base_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\figures\\"
base_output_path = "Y:\\livneh\\itayta\\Itay_group_meeting_dfs\\code_base_for_paper\\final_figures\\"
output_path <- sprintf("%s\\supplemental_figrures\\", base_output_path)
dir.create(output_path)
metadata_TT <- across_... |
71ca7979b9e35048b254b220fbc1d07d304694db49a0d44899321e2338d72b93 | R | 162,180 | 2,616 | #######################################################################
## PREPARE DATASET AND CREATE FOLDER IN WORKING DIRECTORY ###
#######################################################################
# used libraries
{
library(nlme)
library(data.table)
library(emmeans)
library(lmerTest)
li... |
9a626f21ae3c3881e7d8d958065cf72039ff55ea69a2c0e07ba4472718ac128d | R | 172,474 | 3,897 | ---
title: "ERphagy_FigureGeneration1"
author: "Ian Smith"
date: "2023-02-15"
output: html_document
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## iNeuron Autophagy
### Package load
```{r}
library(tidyverse)
library(ggpubr)
library(pheatmap)
... |
634d4a470d500cfd83eda80fe26b6b2f8601b96add68d5cb5651394259cc5988 | R | 192,978 | 3,704 | #! /usr/bin/env Rscript
# library -----------------------------------------------------------------
library(ggplot2)
library(Seurat)
library(scater)
library(Matrix)
library(cowplot)
library(SingleCellExperiment)
library(scater)
library(destiny)
library(umap)
library(ggthemes)
library(dplyr)
library(patchwork)
library(m... |
1eba376e0e761e9ddb24ab9f5a6e3aaca78b0c4054536388e5cac2c7fbe809d0 | R | 200,000 | 4,735 | ---
title: "ERphagy_FigureGeneration2"
author: "Ian Smith" "Melissa Hoyer"
date: "2023-07-07"
output: html_document
editor_options:
chunk_output_type: console
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## iNeuron Autophagy
### Package load
```{r}
library(tidyverse)
library(ggpubr)
li... |
2dd39e9159e74e588ccba64841697106ddac722c4568007d9fd2d38dec89a644 | Rust | 331 | 13 |
use std::io::{Read, Seek, SeekFrom};
use std::fs;
const FRAMERATE_OFFSET :u64 = 0x0054;
pub fn get_framerate(file :&mut fs::File) -> Option<u16> {
file.seek(SeekFrom::Start(FRAMERATE_OFFSET)).ok()?;
let mut bytes :[u8;2] = [0u8, 0u8];
file.read_exact(&mut bytes).ok()?;
let out :u16 = u16::from_le_bytes(bytes);
... |
fb5b81e8b4876556ae3f76d87a0e8097117bbb6f7e0754f0654f11fff32ad01a | Rust | 838 | 40 | const BINS: usize = 256;
pub struct Histogram {
count: u32,
value_counts: [u32; BINS],
}
impl Histogram {
pub fn new() -> Histogram {
Histogram {
count: 0,
value_counts: [0u32; BINS],
}
}
pub fn update(&mut self, value: u8) {
self.count += 1;
... |
fdac91a3ca9d8df7754f925a69ea0848fc1accc2749f452294e0023fd292de31 | Rust | 3,924 | 155 | use std::fs;
use std::io::{Read, Seek, SeekFrom};
use std::mem;
#[derive(Copy, Clone, Debug)]
#[repr(C)]
pub struct CineHead {
_kind: u16,
_headersize: u16,
_compression: u16,
_version: u16,
_first_movie_image: i32,
_total_image_count: u32,
_first_image_no: u32,
_image_count: u32,
_... |
a29882b774b9884e24b1413313c098b870b20aad7076efdc4a22b8c3a91995ef | Rust | 7,954 | 298 | #[cfg(test)]
mod tests {
use super::*;
use std::os::unix::io::IntoRawFd;
#[test]
fn it_works() {
let result = 2 + 2;
assert_eq!(result, 4);
}
#[test]
fn counts_images() {
let mut file = fs::File::open("/home/tomas/Projects/DrinkMoth2/data2/moth22_2022-01-26.cine").... |
e5498ec26f3d41a97af48101cea65ffd7bc70c6665aadf5946672f14492f9396 | Shell | 18 | 1 | python model.py 1
|
54e27c0843bb8170733001d24713bac446ec925f7ecd9d82ece673bbd09b54b5 | Shell | 20 | 1 | export PYTHONPATH=./ |
b4cfbd8189f5534442204812b3215cfeac82910e256b9e4fbcdd24e4c4430304 | Shell | 31 | 1 | time -p 2> time.txt sh ctrl.sh
|
1db433977df756a27add6acdcdb824ee76807ca8fcf03d22fb58eccc8cc15b52 | Shell | 40 | 3 | #!/bin/bash
python test.py -m resnet50
|
47c7bc991f5707b742b0969a4a7e523597b8b8629d86499db44cbf1b61eb7caa | Shell | 47 | 3 | #!/bin/bash
vimdiff <(nl -ba $1) <(nl -ba $2)
|
b67f64d428d5aecbcddcbdedf60143ecc73e2ac71982c96bfc526dec0c75b2e8 | Shell | 47 | 1 | java -Xmx5G -jar Aracne.jar -o . --consolidate
|
cac4b3fd9bca96869a8106585734a67131a59ff4915a06fee4c340e2689d4786 | Shell | 53 | 3 | #!/bin/bash
jobId=`cat $1`
sacct -P -o ALL -j $jobId
|
8cdeeecbcd05f871e8757419c26e78e05910786484dd2e685ea8b61af0ddf8f7 | Shell | 54 | 2 | #!/bin/bash
lftp -f reports/00-upload_ncbi/upload.ftp
|
bca4cc5ca7b38943b4343936d096d14b25f9397b2e45d339eacf3954127b4a55 | Shell | 56 | 7 | #!/bin/bash
for pbs in "$@"
do
sbatch "$pbs"
done
|
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