sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
f54fae0f9e2c273b680f2355b98205e2b309e3dcc3a3d711e892f266ecf763f3 | R | 83,130 | 1,377 | # In this file, I store ependymoma project specific functions (used for analysis of xenium data).
# set up the global vars of the epn project, without any sample_specific variables
# home_dir: where the code, and light weight files, like metadata etc are stored
# data_dir: where the heavy files, like raw and processed... |
9c90230301f254fe2c80f25a4138c3f7db2477a1e3210519137bb0535d8d90a1 | R | 91,074 | 2,045 | #neurogenomicslab/magma.celltyping
Sys.setenv(GITHUB_PAT="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")
install.packages("piggyback")
Sys.setenv('R_MAX_VSIZE'=64000000000)
# if(!require("remotes")) install.packages("remotes")
# for figure 7
# face_ctd <- EWCE::load_r... |
401b863dc1b5660a1f91d202dc6214879851d9e9a10670c3ca5714744f299d4c | R | 91,146 | 2,056 | ---
title: "Craniofacial-scRNAseq-manuscript"
output: html_document
date: "2025-03-31"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir = "/scr1/users/manchela/Data")
library(Seurat)
library(SeuratDisk)
library(tidyverse)
library(harmony)
library(dplyr)
library(patchwor... |
5f8ca0ba65a662b28f61d6d707883e8e1f279f8c56ecb20fdffb510131e54e03 | R | 96,896 | 1,745 | #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#~~~~~~~~~~~~~~~~~~~~~~~~BASIC UTILITY FUNCTIONS~~~~~~~~~~~~~~~~~~~~~~~~
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# This file contains all the functions which I have most frequently accessed directly (during first ... |
80ab2e58ad9a519c92ae01270bb740d047035824cf5d7b6105b2be8c95731154 | R | 103,003 | 2,375 | #####################################################################################################################
#
#####################################################################################################################
#Only all cells except ugly ones
#Idents(combined_seurat) <- "integrated_snn_res... |
aba70ccb29e1fc8186354980c0e44790ed1ab6313d10bde069a56b061b60c83a | R | 122,907 | 2,357 | Sys.setenv('R_MAX_VSIZE'=64000000000)
library(Seurat)
library(tidyverse)
library(harmony)
library(dplyr)
library(patchwork)
library(viridis)
library(ggforce)
library(gghalves)
library(ggridges)
library(scCustomize)
initial <- readRDS("Initial_data.rds")
cds1 <- readRDS("~/Desktop/scRNA-Seq_GWAS/cds_face_human_temp.rds... |
ed466c8f08d1811ed10ccf8963d27c3b1d58de5f8bb6160810bfbcef02e37ba4 | R | 132,893 | 5,566 | ```{r}
source(here::here("src/init.R"))
```
<!----------------------------------------------------------------------------->
<!----------------------------------------------------------------------------->
# I. Data
```{r}
data_dict <- load_data_dict()
supplementary_data <- load_supplementary_data()
clearing_respon... |
794331e99958f0e9da41b45cd04be5c4db2bb4218513453faabafe8192f7c13e | R | 140,918 | 3,046 | install.packages("circular")
install.packages("ggplot2")
install.packages("units")
install.packages("reshape2")
install.packages("circlize")
install.packages("ggthemes")
install.packages("lemon")
install.packages("egg")
install.packages("readxl")
install.packages('Rcpp')
install.packages("equatiomatic")
install.package... |
46ebfa0ef51205102855b4b492fb6c663aaf64b6db06339dc6f3b202d16bcfa3 | R | 147,657 | 3,194 | install.packages("circular")
install.packages("ggplot2")
install.packages("units")
install.packages("reshape2")
install.packages("circlize")
install.packages("ggthemes")
install.packages("lemon")
install.packages("egg")
install.packages("readxl")
install.packages('Rcpp')
install.packages("equatiomatic")
install.package... |
b57e467789b10efdd4c093912943e612af1b360199acba41ffb0d18818aabbb8 | R | 180,250 | 4,098 | data 'icns' (-16455) {
$"6963 6E73 0000 FFFB 6838 6D6B 0000 0908"
$"0000 0054 AFAD A69F 9891 8B84 7D76 6F69"
$"625B 544D 4740 3932 2B17 0000 0001 0100"
$"0000 0000 0000 0000 0000 0000 0000 0000"
$"0027 BFF9 F5F7 F7F8 F8F9 F9F9 F9FA FAFA"
$"FAFA FBFB FAF9 F8F8 F9F5 98B3 D7F5 F4EE"
$"E9E2 DBD4 CDC6 BFB9 B2AB A39C ... |
fd21ce0aaad772af507a469c75c7ae2a8fa6e2e597f089c970f3af5c3b2bea5b | R | 200,004 | 5,960 | # 20230922_rat_retina_with_GEO.R
#### SETUP ####
#### Samples and path variables ####
# Rat retina treated with human cells
# WT rat retina samples from GEO GSE209872
# ALIGNED to RAT ref rnor
# samples used:
#
# rnor_08182_P90_Treated_rat_human_cells_outs
# rnor_13933_P60_Treated_rat_cells_outs
# rnor_13933_P60_Unt... |
76396bf556211f679e7a4fb548d42b80c90a4722e187c5dd90fc278799b42a60 | R | 200,008 | 3,970 | ###########################
# Prepare environment
set.seed(1234567)
options(stringsAsFactors = FALSE)
# DLLs controls
length(getLoadedDLLs())
###########################
# LOAD -> Libraries & Functions
###########################
source("seurat_melanoma_timeseries_libraries.R")
source("seurat_melanoma_timeseries_fun... |
ef4a0bee2bbbf0c5fcaec5c6c363d4ba12a490d315cdbfe452f2441f7549fbf4 | R | 200,008 | 4,577 | rm(list=ls())
library(tidyverse)
library(readxl)
library(vegan)
library(pairwiseAdonis)
library(pheatmap)
library(ggpubr)
library(dplyr)
library(RColorBrewer)
library(FSA)
library(viridis)
#setwd("/media/gfaraci/model-AD/TREM2")
setwd("C:/Users/Gina Faraci/Documents/R/model-AD/TREM2 metabolome/From Juli... |
b120e86aef36b2f4f4eea4f96de9bdb45b19be4e322d6ca1978077acd322bc2f | Shell | 51 | 3 | #!/usr/bin/sh
python setup.py build_ext --inplace
|
12f3c825ffa3f4829dfabfcf5b66307ab8be8a7e5193442bee682d6bf258bc69 | Shell | 55 | 1 | /home/sxh/anaconda3/envs/kekulescope2/bin/python run.py |
affce0ee97caba52bbdb51d7cab723d15ec4de4ac864d9211a7df1aa3c95d924 | Shell | 69 | 5 | #!/bin/bash
./run_baseline.sh
./run_tradition.sh
./run_multitask.sh
|
1f85f2a63ec925cac2627b63babb844364a8d0717ae8db0098d0daafe78031ca | Shell | 71 | 2 | # run yass using the neural network detector
yass sort config_nnet.yaml |
58be03510e5315794ced2130044e38e9983096b2a0e67e597dd42e043585b4d4 | Shell | 72 | 2 | # export threshold results to phy
yass export config_threshold_49ch.yaml |
f673cb4ee01f64fa8371644836b5970417b65ca654805881ae130e5cbcd35ccc | Shell | 73 | 2 | # run yass using threshold detection
yass sort config_threshold_49ch.yaml |
5ac021a1306d2a8a0ad369a8dbe48a60fbb7103531b1c6efe899d281c2a16f83 | Shell | 78 | 6 | #!/bin/bash
set -ex
mkdir -p /usr/local/include
cp jni.h /usr/local/include
|
f2b1ca56a3cfafd09ba93bb3ea157f3bbbcee5ce705e7d0b0fd88046ce3d260f | Shell | 85 | 5 | rm -r ./build
rm -r ./dist
rm -r molmap.egg-info
#python setup.py sdist bdist_wheel
|
a70727236591d43e3d20e1148f221768a65624d9d8628350050b5620cdd4c687 | Shell | 101 | 7 | #!/bin/bash
/usr/local/bin/python3 -m virtualenv .venv
source .venv/bin/activate
pip install -e .
|
9b759b014a6e333f29aeb137876e6dea2b1f4b4d5d8a78c1641602b38aab926d | Shell | 102 | 5 |
INPUT=input.csv
OUTPUT=output.csv
python main.py --input $INPUT --output $OUTPUT --images ./images/
|
93a2305f114c4873eb447e14156aa49e994854cf62994050491ba3dae4513690 | Shell | 110 | 1 | python ../../../src/CRUST_yfsheng/CRUST.py ./data/SS200000108BR_A3A4_scgem.Cardiomyocyte.csv ./results/ Mouse
|
20cf5819dbe0fda9a04ef85548203dd1a8af59a4637ca3b084794772c8b05578 | Shell | 120 | 7 | #! /bin/sh
ls /Library/Receipts/astimfit* > /dev/null
if [ $? -eq 0 ]; then
sudo rm /Library/Receipts/stimfit*
fi
|
7e459ddf7a8b3996affd6cbd5c766bd8286d40def59ce18a341a028610d85a71 | Shell | 120 | 3 | #! /bin/bash
/usr/bin/python setup.py install --prefix=dummy-install WXPORT=osx_cocoa WX_CONFIG=~/wxbin/bin/wx-config
|
cccc64a71ac80e37b56f5c5106e39dd0749b22ca095aed73e7708352ca8ee179 | Shell | 122 | 6 | #!/bin/bash
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
docker build -t pytorch .
|
a4b6a1c21d87aedf7d0000370a3a101109b13709973d85e2befea187113af639 | Shell | 134 | 6 | #!/bin/bash -e
# Allows this script to be invoked from any directory:
cd "$(dirname "$0")"
python3 scripts/generate_ci_workflows.py
|
87070a00f18bcc03f211a3369b5647bf4872ea1d8482075ceee8fe381fc561f2 | Shell | 138 | 3 | #! /bin/bash
ln -sf /Applications/stimfit.app/Contents/libs/libstf.0.dylib /Applications/stimfit.app/Contents/Frameworks/stimfit/_stf.so
|
4a93e055a8484f5258c02775150946a6eda39aa8a7655f10dd91cf846cc9ce59 | Shell | 148 | 8 | #!/usr/bin/env bash
TOKEN_FILE=$1
TOKEN_PIPE=$2
rm "${TOKEN_PIPE}" 2>/dev/null ||:
mkfifo "${TOKEN_PIPE}"
cat "${TOKEN_FILE}" > "${TOKEN_PIPE}" &
|
a4e05810a5e5fd616a8865d8a58acd4d9246404f3ea7686616542ae70a5dffeb | Shell | 155 | 6 | #!/usr/bin/env bash
conda install -c conda-forge ase
conda install -c conda-forge/label/gcc7 apsw
conda install -c psi4 psi4
conda install -c torch torch
|
0f95b7f955fd2da715a6a40c86bff2fc3be282aa5f344d6b85c4acb8d9518a9f | Shell | 157 | 9 | #!/bin/bash
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Testing pytorch docs"
cd docs
TERM=vt100 make doctest
|
d290f27315a5d7ccb2238531ec3750c7ead4d5a75627b47377890897d72928a6 | Shell | 160 | 1 | /usr/bin/python2.6 build-wxpython.py --build_dir=../bld --prefix=/Users/cs/wxbin --osx_cocoa --mac_universal_binary --install --wxpy_installdir=/Users/cs/wxbin
|
6349e183f9feb229f7966114747b3e6fe8c8729107b2e43e275de34827f7de10 | Shell | 166 | 2 | nohup /home/sxh/anaconda3/envs/rdkit2020/bin/python ./01_FreeSolv.py &> FreeSolv.out &
nohup /home/sxh/anaconda3/envs/rdkit2020/bin/python ./02_ESOL.py &> ESOL.out &
|
fb85574e7f40ab87f0f0c89a57a03a5b36a1cab0aa0d44190215debcc028d424 | Shell | 166 | 6 | #!/bin/bash
python data_process/data_split_dti.py
python data_process/data_split_dta.py
python data_process/data_split_moa.py
python data_process/extract_feature.py
|
acb1797b9fe9276a554b458c3fb72199317d37fb650541d26798aed88fb979bc | Shell | 170 | 5 | featureCounts -p \
-a GCF_011386835.1_ASM1138683v2_genomic.gtf \
-o brain.featureCounts.txt \
-T 16 \
*.sorted.bam |
dc1f95174de0dacf914454a371a2334a9fcde31d29f2a12c7da8acee27f4e945 | Shell | 170 | 4 | #!/bin/bash
# container name suffix determined by most recent tag and number of subsequent commits
cV=$(git describe --tags --abbrev=1) # container version
echo ${cV}
|
2842d0f97d4e07118f6a0412a9a8cc19913ebd7359999f20787dcb3109dc3311 | Shell | 173 | 8 | #!/bin/bash
set -ex
git clone --branch v1.15 https://github.com/linux-test-project/lcov.git
pushd lcov
sudo make install # will be installed in /usr/local/bin/lcov
popd
|
b95c8c5cf04d789b0a5b3bddda4941527668dd7ad4db15ef9723098d552a01c8 | Shell | 173 | 4 | fastp -i ${sample}_1.fastq.gz -I ${sample}_2.fastq.gz \
-o ${sample}_1.fp.fastq.gz -O ${sample}_2.fp.fastq.gz \
-j ${sample}.json -h ${sample}.html \
-w 16 |
28467916f48bbfff1f4d7092e31ee12891e931c9d09fd6d6829013109c7e068e | Shell | 178 | 5 | #!/bin/bash
python training_validation.py dti yamanishi_08 warm_start
python training_validation.py dta davis warm_start
python training_validation.py moa activation warm_start
|
700c60a3dde7d2ff0e44ba25b7d98c282fe3ce04cea737c6c01bbc5265405742 | Shell | 178 | 5 | #!/bin/bash
# container name suffix determined by most recent tag and number of subsequent commits
cV=$(./version.sh) # container version
pkexec docker rm -f fil_physicsc_${cV}
|
2095bb879f02e040ab2b32a28b026de8bc0a4602751ede406624243cae580377 | Shell | 187 | 10 | #! /bin/sh
result=`python -c "import sys, string; ver = string.split(sys.version)[0]; print (ver >= '2.5.0' and ver < '2.6.0')"`
if [ $result="True" ]
then
exit 0
else
exit 1
fi |
de0ab4e7062ddb9d85d1057fcf86a0a306b12054c8cf3410d94e22ff413ea8ca | Shell | 187 | 3 | # using the results from the threshold-based spike sort, train a neural
# network detector
yass train /Users/Edu/data/yass/tmp/spike_train.npy config_train.yaml config_threshold_49ch.yaml |
601ebd3a6f7d0bf22909db61934ec5d4a471430eb38563068df8ac5a45a30638 | Shell | 188 | 5 | #!/bin/bash
# container name suffix determined by most recent tag and number of subsequent commits
cV=$(./version.sh) # container version
pkexec docker exec -it fil_physicsc_${cV} bash
|
c39c8f2bdaa3cc5f3bdf653c0290cecd677127c21e02ed91447eeca63e4e551f | Shell | 201 | 11 | #!/usr/bin/env bash
set -e
echo "Starting EvoAge FastAPI backend..."
exec poetry run gunicorn \
-w 1 \
--timeout 300 \
-k uvicorn.workers.UvicornWorker \
app.main:app \
--bind 0.0.0.0:1026
|
3ac5ad6cf22e49c67c63a09c529c3413ed8842f2704324a9648e2a1267b4e692 | Shell | 203 | 2 | /home/sxh/anaconda3/envs/rdkit2020/bin/python ./02_fp_on_classification.py &> fp_on_classification.log &
/home/sxh/anaconda3/envs/rdkit2020/bin/python ./01_fp_on_regression.py &> fp_on_regression.log & |
336374aa9412d419e73f21aae6fad38f15c9f75ecdde3943256da056cd9a5924 | Shell | 204 | 3 | while IFS=, read -r SampleName SampleDeidName; do
sh /n/scratch/users/s/sad167/EPN/scRNAseq/scripts/7b-NMF_rank-batch.sh $SampleName
done </n/scratch/users/s/sad167/EPN/scRNAseq/scripts/metadata_NMF.csv |
4e621fd7957a76831a5a5da4ebc94dc85b8647c2a187e38c950353328e770974 | Shell | 205 | 9 | #!/usr/bin/env bash
set -eux
CHANGES=$(git status --porcelain "$1")
echo "$CHANGES"
# NB: Use --no-pager here to avoid git diff asking for a prompt to continue
git --no-pager diff "$1"
[ -z "$CHANGES" ]
|
33a01dfc5de4cf9e226f1e239c44ae08ab66d4dc4a625a915ff535574a0102c3 | Shell | 211 | 5 | wget -r ftp://ftp.ncbi.nlm.nih.gov/pubchem/Compound/Extras/CID-SMILES.gz .
cd ./ftp.ncbi.nlm.nih.gov/pubchem/Compound/Extras/
gzip -d *.gz
cd -
mv ./ftp.ncbi.nlm.nih.gov/pubchem/Compound/Extras/CID-SMILES ./data |
bd8e6979774ddb66600263661a62a05146ad3d62317151cd1bfee9bcdf5172b2 | Shell | 223 | 10 | #!/bin/bash
set -ex
# Install MinGW-w64 for Windows cross-compilation
apt-get update
apt-get install -y g++-mingw-w64-x86-64-posix mingw-w64-tools
echo "MinGW-w64 installed successfully"
x86_64-w64-mingw32-g++ --version
|
516402145293b782261f5dcb62900c94ea9ee0118a13ddc46e1a0f72af67b29d | Shell | 231 | 8 | #!/bin/bash
# Compile the socket wrapper.
javac ./gadgetron/external/SocketWrapper.java
# Build a simple jar file containing the wrapper.
jar -cf ../gadgetron.external.SocketWrapper.jar ./gadgetron/external/SocketWrapper.class
|
220c493fada305f3f98c262eb3c13bce4fd4cd7086980859567981302f2324b4 | Shell | 234 | 14 | #! /bin/sh
# input should be a directory
path=$1
# for loop all the files and check the license
for file in $path/*
do
echo $file
sh $CBIG_CODE_DIR/setup/check_license/CBIG_check_license_matlab_file.sh $file
clear
done
exit 0;
|
301a70ab267ba85515ab484b98e572aa2fac186629ec215a1dfd5cc54fabe795 | Shell | 235 | 4 | #!/bin/bash
./run.R -wd $maindir/res/DWLS_res -sc $maindir/data/comp/synthetic/validation*cnt_data.tsv -mt $maindir/data/comp/synthetic/validation.*.mta_data.tsv -st $maindir/data/comp/synthetic/counts*.tsv -o $maindir/res/comp-DWLS
|
ecae92661144f40180e2098a91e9ede7981c21d49674240b44243ba7796cddc6 | Shell | 242 | 7 | hisat2-build -p 24 <ref.fna> {ref}
hisat2 -t -p 20 --summary-file ${sample}.log --new-summary \
-x ${ref} \
-1 ${sample}_1.fp.fastq.gz \
-2 ${sample}_2.fp.fastq.gz | \
samtools sort -@ 12 -o ${sample}.sorted.bam - |
68209cc66ae6a01de7285f9068da01031ab202489a97140a59a471f91bc159fc | Shell | 248 | 4 | #!/bin/bash
idat-tools mix -r 0.5 GSM6379997_203927450093_R01C01_Grn.idat GSM3024450_200392810022_R04C01_Grn.idat /tmp/rmme.idat
#idat-tools mix -r 0.5 GSM6379997_203927450093_R01C01_Grn.idat GSM6379997_203927450093_R01C01_Grn.idat /tmp/rmme.idat
|
06c37086888a449c3e76d05fd3b5ba51b77f9853860d656de455385046efff49 | Shell | 250 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussG.o
#SBATCH -J GaussG
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beo_gauss_G.R
|
18d24b0356c076b0761ca3e49922549d76eeb9ed520927b274e93163819c6290 | Shell | 250 | 7 | python trainer.py \
--train_corpus_path ../data/pubchem1K_train.corpus \
--val_corpus_path ../data/pubchem1K_val.corpus \
--vocab_path ../data/pubchem1K.vocab \
--bermol_path ../checkpoints/bermol_pubchem10M_0725/ \
--epochs 100 \
--device cuda:0 \
|
edb89b6d471cafdc001e03b81e72172042922b376b23216dc1ce5c916facc62d | Shell | 250 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussW.o
#SBATCH -J GaussW
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beo_gauss_W.R
|
f36e860ce4bf85eba11c433d574c8e890b395eb06825b5cf1fc031bf39da013c | Shell | 250 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussS.o
#SBATCH -J GaussS
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beo_gauss_S.R
|
1cf1dd9b878b3a8d5330c183e75b2979094dc4355d8308f061f3e3c0cbc7ccdf | Shell | 251 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepG.o
#SBATCH -J DeepG
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/03a.beo_deep_G.R
|
35bb4c9cc73fdcaf3156e3f351422fb9360ba34fccbb859564f6070d71e95d8f | Shell | 251 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepW.o
#SBATCH -J DeepW
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/05a.beo_deep_W.R
|
5f50de8483618d8f93eda6f27902a0209b4670432494bbbfb37256681e4b77d4 | Shell | 251 | 15 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepS.o
#SBATCH -J DeepS
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/04a.beo_deep_S.R
|
dc304c28d56475156d155e18224c3dd436738dc618d19c1ebe89eb5bf6ea7314 | Shell | 262 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussGWint.o
#SBATCH -J GaussGWint
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beo_gauss_GWint.R
|
10bae0fce998fa14fe7a0cc6cc29587664288a3025ef44916010cf2576e6167e | Shell | 266 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepGSWint.o
#SBATCH -J DeepGSWint
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/06a.beo_deep_GSWint.R
|
38bb82558c4b6a82aceaa140403770896783f581fa2b84254e8180a190aa3149 | Shell | 272 | 8 | #!/bin/sh
# matlab_exec=/usr/local/matlab/bin/matlab
matlab_exec=/usr/local/MATLAB/R2018a/bin/matlab
X="addpath('/data/code/grab/2009.washu/_macros/generic'); getTrajectory(${1})"
echo ${X}
echo ${X} | ${matlab_exec} -nojvm -nodisplay -nosplash
#rm matlab_command_${1}.m
|
e10f35b39d830827a0062daca946fd6d095b415eb9fef774c2fd4d46ce9295ab | Shell | 277 | 8 | set -e
for exp_id in attention_network_task dot_pattern_expectancy motor_selective_stop_signal stop_signal stroop twobytwo ward_and_allport
do
for index in 1 2
do
sed -e "s/{EXP_ID}/$exp_id/g" -e "s/{INDEX}/$index/g" get_experiment_designs.batch | sbatch -p russpold
done
done
|
15d70c154f292fcc0a0251f9bc72bbc8b7c3422218ca31b9070b3ddab986b67e | Shell | 281 | 15 | #!/bin/sh
#!/bin/sh -xv
f=/tmp/atend$$
trap "rm -f $f;exit" 0 1 2 3 15
cat >$f
bb=`awk '/^%%BoundingBox: [0-9]/{print}' <$f`
if [ -n "${bb}" ]; then
awk "\
\$1~/%%BoundingBox:/{if(\$2~/atend/) print \"${bb}\";}\
\$1!~/%%BoundingBox:/{print;}\
" <$f
else
cat $f
fi
/bin/rm -rf $f
|
a2445b7f957e53f8f20be9b39a29d63de33b0db88704e95bdc75f8423c99cd43 | Shell | 289 | 15 | #!/bin/bash
set -e
rm -rf MolMM/data/split/*/sub*
rm -rf MolMM/data/split/*/inh*
rm -rf results/* ckpt/*
./scripts/001_run_baseline.sh
./scripts/002_run_multitask.sh
./scripts/003_run_meta.sh
./scripts/004_run_ablation.sh
./scripts/001_run_baseline_DNN.sh
./scripts/003_run_meta_DNN.sh |
76cdaaf56aafee758c0406a864134bd7aa5957ab41eb660451a1c6827855d55f | Shell | 293 | 10 | #!/usr/bin/env bash
SCRIPT_DIR=$(dirname "$0")
APP_ID=$1
INSTALL_ID=$2
APP_PRIVATE_KEY=$3
DST_FILE="$4"
ACCESS_TOKEN="$(APP_ID="$(<"${APP_ID}")" INSTALL_ID="$(<"${INSTALL_ID}")" APP_PRIVATE_KEY="$(<"${APP_PRIVATE_KEY}")" "${SCRIPT_DIR}/app_token.sh")"
echo "${ACCESS_TOKEN}" > "${DST_FILE}"
|
4077ba5dafdd8549e6f913c2827956e727f2863ba154be9a91b338124d26cdd2 | Shell | 296 | 2 | #! /bin/bash
../configure --enable-python --with-wx-config=/Users/Stoffel/wxbin/bin/wx-config CXXFLAGS='-I/Users/Stoffel/wxPython-svn/include -I/opt/local/include' LDFLAGS='-headerpad_max_install_names -L/Users/Stoffel/wxbin/lib -L/opt/local/lib -L/usr/lib -lsz -lz' PYTHON=/opt/local/bin/python
|
4eaf8adcaca9fee12fe3191c1cc630d4c72ee1c26f7e4457b2e1532d09693b5e | Shell | 299 | 15 | #!/bin/sh
cat >&2 <<'MSG'
autotools support has been deprecated in this repository.
Do not run ./autogen.sh for current builds.
Use the CMake build instructions in BUILDING.md instead.
Primary entry points:
./build_linux_cmake.sh
./build_macos_cmake.sh
./build_windows_msvc.ps1
MSG
exit 1
|
f1a6cf091113edeb5e09c63cffa2370fe1d671a8675af6e29408c95b7d7b4639 | Shell | 300 | 17 | #!/bin/bash
ASHS_TSE_ISO_FACTOR="100x100x250%"
ASHS_TEMPLATE_ANTS_ITER="40x10"
ASHS_TEMPLATE_ROI_DILATION="3x3x3vox"
ASHS_TEMPLATE_ROI_MARGIN="2x2x2vox"
ASHS_TEMPLATE_TARGET_RESOLUTION="1.5625x1.5625x1.5625mm"
ASHS_PAIRWISE_ANTS_ITER="60x20"
ASHS_EC_ITERATIONS=200
ASHS_EC_PATCH_RADIUS=3x3x0
|
ff28af003e1228f92a25848c2edc94e7946990fc9028ce36a92981b6d7f526f4 | Shell | 304 | 14 | PLINK="YOUR/PATH/TO/plink"
OUT="gene"
SCTOBJ="./sct.rds"
FINAL_OUT1="./RPL13"
GNAME="RPL13"
## Run scTWAS to train STAGE 1 GReX model
Rscript ./scTWAS_IRLS.R \
--bfile $OUT --tmp ${OUT}.tmp --out ${FINAL_OUT1}_PRWGT --verbose 0 --PATH_plink $PLINK --sctobj ${SCTOBJ} --gene $GNAME --niter 3
|
1e9344a4c714840416ce49a7e274940d3246962b842c3a235ca0f61829b68115 | Shell | 307 | 13 | #!/bin/bash
# Script used only in CD pipeline
set -ex
mkdir -p /usr/local/mnist/
cd /usr/local/mnist
for img in train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz; do
wget -q https://ossci-datasets.s3.amazonaws.com/mnist/$img
gzip -d $img
done
|
7093cdfc99eed3c6b5d49524e453a1924e6665253d4189bfe0f7087516841b36 | Shell | 310 | 23 | #!/bin/bash
# Script used only in CD pipeline
set -ex
LIBPNG_VERSION=1.6.37
mkdir -p libpng
pushd libpng
wget http://download.sourceforge.net/libpng/libpng-$LIBPNG_VERSION.tar.gz
tar -xvzf libpng-$LIBPNG_VERSION.tar.gz
pushd libpng-$LIBPNG_VERSION
./configure
make
make install
popd
popd
rm -rf libpng
|
7993d57bc4eccc01e893bd2e053207cfadeec8cbbcc699be3fdc00fbb9928e0b | Shell | 314 | 22 | #!/bin/bash
grep -n math maths3.txt > test.txt
#for i in $list_line
while read i
do
echo $i
idx=`expr index "$i" :`
line1=${i:0:idx-1}
num=$((line1 + 1))
idx2=`expr index "$i" .`
dif=$((idx2-1-idx))
fname=${i:idx:dif}
fname=${fname}.txt
line2=`sed -n ${num}p maths3.txt`
echo $line2 > $fname
done < test.txt
|
71e333d8bb58ca0e75afb1ad4e166143ce57bcf757413b9824f1e8d80b70ff3a | Shell | 315 | 15 | #!/bin/bash
echo "ASHS_ROOT: ${ASHS_ROOT?}"
echo "Output Dir: ${1?}"
OUTDIR=${1?}
$ASHS_ROOT/bin/ashs_train.sh \
-D config/manifest.txt \
-L config/snaplabels.txt \
-w $OUTDIR \
-d -Q \
-r config/rules.txt \
-x config/xval.txt \
-C config/ashs_config_test.sh | tee $OUTDIR/ashs_train_stdout.txt
|
bb8e99c4a385a6f5e354ea011dcc1aa87904996595e75a8f03e467141d8d5756 | Shell | 318 | 6 | #!/bin/bash
set -e
# rm -rf results/baseline_*/DNN* ckpt/baseline_*/DNN*
python 000_run_multi.py -n DNN_pH_kfold_val_pure -d results/baseline_sub -c1 ckpt/baseline_sub -l 1 -t substrates_classes
python 000_run_multi.py -n DNN_pH_kfold_nval_pure -d results/baseline_inh -c1 ckpt/baseline_inh -l 1 -t inhibitors_classes |
5dab0725213af16cf1cb2e84373a4c7d57e3297ae7b226f56910daf9e92ed8d4 | Shell | 321 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepA-%A_%a.o
#SBATCH -J DeepA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/05a.deepA.R --seed $SLURM_ARRAY_TASK_ID... |
46e8d1cdbbbf19bdfad9704690fc4a321d3affed1bdcfb3b49d8636f51369c00 | Shell | 323 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=2:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepAD-%A_%a.o
#SBATCH -J DeepAD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/05c.deepAD.R --seed $SLURM_ARRAY_TASK_... |
6503cb6546c447f45a54591e4577afb11cce52f94dc21f0f3a3dc1ecd3487c19 | Shell | 324 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=12:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussA-%A_%a.o
#SBATCH -J GaussA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/04a.gaussA.R --seed $SLURM_ARRAY_TASK... |
725b6c835f3a677bdcd9de8ba91c022e7d2062b30586069ccd5f323d6c787727 | Shell | 326 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=2:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=LinearA-%A_%a.o
#SBATCH -J LinearA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/03a.linearA.R --seed $SLURM_ARRAY_TA... |
5162aef1f680512cb9baa683b8979e887d01f0a4d264a8afaf5e0828e18a1b6c | Shell | 327 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussAD-%A_%a.o
#SBATCH -J GaussAD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/04c.gaussAD.R --seed $SLURM_ARRAY_T... |
c4ee28b618d5cde22364a27f209f8130ec034f8e226e5573f3d177904a1892b4 | Shell | 327 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepASW-%A_%a.o
#SBATCH -J DeepASW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/05e.deepASW.R --seed $SLURM_ARRAY_T... |
6a26b9728d441df19239d12fc2fe64291f463809d52921198b1b401405a1cb5b | Shell | 330 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=12G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=LinearAD-%A_%a.o
#SBATCH -J LinearAD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/03c.linearAD.R --seed $SLURM_ARRA... |
890b6ea220f9037a08f6eb43afc5c760f72894892ba71a70cdb324fbe17f5447 | Shell | 330 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussASW-%A_%a.o
#SBATCH -J GaussASW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/04e.gaussASW.R --seed $SLURM_ARRA... |
c800ffb3bc71ddb02b9a67725f3dd99b858a76fa78b3a8024cac2ec2f23f2622 | Shell | 330 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepADSW-%A_%a.o
#SBATCH -J DeepADSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/05g.deepADSW.R --seed $SLURM_ARRA... |
6cfffd79494f5df5d354caad40b98c8b5b4be10f87f196c1766eaa824f05b0b7 | Shell | 331 | 5 | #!/bin/bash
# -s defines port on which storage server is run
# -D defines where the storage server database is located (workaround when no permisions to access default database)
# grep -v DEBUG - is to suppress over-verbose FIRE scaling messages
gadgetron -p9888 -s 9111 -D "/root/.gadgetron/storage/database-FIL" | gre... |
a07516f3cd09d3e5806c97222c276881f12e9fd8f26c97751653d81d1189bdef | Shell | 331 | 11 | ## Preprocessing
Rscript --no-save --no-restore --verbose 1-preprocess.R > out.txt 2>&1
mv out.txt SCP1184/out.txt
## DE test
Rscript --no-save --no-restore --verbose 2-DE.R > out.txt 2>&1
mv out.txt results/DE/out.txt
## GO analysis
Rscript --no-save --no-restore --verbose 3-GO.R > out.txt 2>&1
mv out.txt results... |
29cdd95c392d37c944a8a7f12481981737d67d762c2ae6327258284eac3a28a1 | Shell | 333 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=LinearASW-%A_%a.o
#SBATCH -J LinearASW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/03e.linearASW.R --seed $SLURM_A... |
da9ab25f133310b79fed928cc9ce0ca1a115735eaf070115a883929e3e1d0841 | Shell | 333 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussADSW-%A_%a.o
#SBATCH -J GaussADSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/04g.gaussADSW.R --seed $SLURM_A... |
ec01fee3316e3dc6fe5d17ed0b22310e82210bbfda83e3c02cfdf69ffe1f34e3 | Shell | 333 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=DeepHSW-%A_%a.o
#SBATCH -J DeepHSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/13c.deep_H_models.R --seed $SLURM_A... |
ae56a9df0da8885c66172925050e8bfb0f4d4b83289a7f7a6ceeae2779f7c935 | Shell | 336 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=GaussHSW-%A_%a.o
#SBATCH -J GaussHSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/12c.gauss_H_models.R --seed $SLUR... |
f0005ed6e26992e961ac0cf778eaffbd354fc8a3617dc89b8cd3cd150f274462 | Shell | 336 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=LinearADSW-%A_%a.o
#SBATCH -J LinearADSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/03g.linearADSW.R --seed $SLUR... |
3d87fc24a53c24aec02139ff22dd250f989daaa6b0bb127e9934e3c3d3228c46 | Shell | 339 | 17 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem=48G
#SBATCH --time=72:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=LinearHSW-%A_%a.o
#SBATCH -J LinearHSW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/11c.linear_H_models.R --seed $S... |
805aa57ce033d04fccabbb2ae8eb4152125a596413653342212335a2e13a2518 | Shell | 349 | 3 | #!/bin/bash
zcat data/overlap.bed.gz | head -n1000 > data/overlap.1000.bed
chrombpnet_predict_to_bigwig -bm outputs/models/bias_model/bias.h5 -cm outputs/models/chrombpnet_model/chrombpnet.h5 -cmb outputs/models/chrombpnet_model/chrombpnet_wo_bias.h5 -r data/overlap.1000.bed -g data/hg38.fa -c data/hg38.chrom.sizes -... |
041a801c0d9b5c3e2f8ce673d28540b3ed57c18f96f0ffc660e00ee627d1f814 | Shell | 351 | 16 | #!/bin/bash
# Script used only in CD pipeline
set -ex
# Pin the version to latest release 0.17.2, building newer commit starts
# to fail on the current image
git clone -b 0.17.2 --single-branch https://github.com/NixOS/patchelf
cd patchelf
sed -i 's/serial/parallel/g' configure.ac
./bootstrap.sh
./configure
make
make... |
b3ea12815689c5e67727e8958cdb4104e7cb62a586424c6672820f00ba253d62 | Shell | 355 | 14 | #!/bin/bash
# Common prelude for macos-build.sh and macos-test.sh
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
sysctl -a | grep machdep.cpu
# These are required for both the build job and the test job.
# In the latter to test cpp extensions.
export MACOSX_DEPLOYMENT_TARGET=14.0
... |
d8c68ce8096b3e16ab7cd49cb0f5e2f91c3d3d3307459d618593753e0a0e620b | Shell | 356 | 14 | #!/bin/bash
#Copyright 2025. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR
bart copy ../02_data_realtime/ksp ksp
time $BART_TOOLBOX_PATH/scripts/rtreco.sh -G ksp img
time $BART_TOOLBOX_PATH... |
73fdad3e0a58f543f49cccf9cb733fa032d8b57c8ff495b32e1f09b1a46220d8 | Shell | 358 | 11 | #!/bin/sh
# Remove generated simulation outputs from every test_* fixture directory.
# (conftest.py does this automatically before each run; this script is for
# manual cleanup.)
for d in test_*/; do
(
cd "$d" || exit 1
rm -f -- *.dat *.pdb traj.xtc eq_traj.xtc restart.pimms log.txt \
py... |
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