sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e19a15baf4c86cc11df300d0f92018738a5981efdb767aed17c13e7b47559c46 | Shell | 300 | 3 | perl doxygraph/doxygraph/doxygraph doc/xml/index.xml graph.dot
iconv -f "windows-1252" -t "UTF-8" graph.dot | sed -e 's/( /(/g' -e 's/ )/)/g' -e 's/\\{/{/g' -e 's/\\}/}/g' -e 's/\\< /</g' -e 's/ \\>/>/g' > graph_.dot
python dirkbaechle-dottoxml-e285fccba8d5/src/dottoxml.py graph_.dot graph.graphml
|
5a642160001871d3880822218dab8643f036a6918b9be93be6b1f7d43dfa37f8 | Shell | 304 | 7 | ############## DI & FRANCESCO 1985 ##############################
MODEL_FILE_CPU="difrancesco.c"
MODEL_FILE_GPU="difrancesco.cu"
COMMON_HEADERS="difrancesco.h"
COMPILE_MODEL_LIB "difrancesco" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
######################################################### |
79d7a0cad95f4a910004a3b57cbc8fcbee8f7ddd6da29e56cc10d10ac62f1b5e | Shell | 304 | 12 | #!/bin/bash
#$ -cwd
for i in *R1*
do
R2=${i//R1_001.fastq.gz/R2_001.fastq.gz}
FOLDER=${i//_S*_L004_R1_001.fastq.gz}
LOG=${i//_S*_L004_R1_001.fastq.gz/.log}
kallisto quant -i Mus_musculus.GRCm39.cdna.all.index -o $FOLDER -t 48 --genomebam --gtf Mus_musculus.GRCm39.105.gtf.gz $i $R2 &> $LOG
done
|
8636790f8e095663a0be208eb5f672e74a8193bdb106d099ced5b167bec9f005 | Shell | 304 | 14 | #!/bin/bash
#SBATCH --job-name=trainDannce
# Job name
#SBATCH --mem=60000
# Job memory request
#SBATCH -t 2-00:00
# Time limit hrs:min:sec
#SBATCH -N 1
#SBATCH -c 16
#SBATCH -p olveczkygpu,gpu
#SBATCH --gres=gpu:1
module load Anaconda3/5.0.1-fasrc02
source activate dannce
dannce-train-single-batch "$@"
|
f95e7742965643d20b1d0e9376c0467207fa7be3287348abc2ec0801f6ec987f | Shell | 304 | 9 | xhost +local:docker
docker run -it \
--rm -e DISPLAY=$DISPLAY \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-v $HOME/.Xauthority:/root/.Xauthority:rw \
--gpus all \
--shm-size=8g \
-v $(pwd):/workspace \
cluster_haptic_texture_database |
1028b5a9333555bebb6061cbb1661cfc978669d8646c8cc8d0124103c0850160 | Shell | 305 | 14 | #!/bin/bash
#SBATCH --time=6-23:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=16
#SBATCH --job-name=gnn_ddd_pars_free
#SBATCH --output=logs/gnn_ddd_pars_free-%j.log
#SBATCH --mem=64GB
#SBATCH --partition=regular
name=${1}
ml R
Rscript ../Script/ddd_pars_est_free_data_fool.R ${name} |
7686043244d78b6a38061f6e97114e956d80ae2d52e7cdbcf8309d459c1a10d0 | Shell | 305 | 3 | SOURCE_FILES="gui.c gui_colors.c gui_window_helpers.c gui_mesh_helpers.c gui_draw.c raylib_ext.c"
HEADER_FILES="gui_shaders.h gui.h gui_colors.h gui_window_helpers.h gui_mesh_helpers.h gui_draw.h raylib_ext.h ../3dparty/raylib/src/extras/raygui.h"
COMPILE_STATIC_LIB "gui" "$SOURCE_FILES" "$HEADER_FILES"
|
ed1201f90089f5b87505346f23b2ed2ac007e084e8f001a50399f32547c68491 | Shell | 305 | 1 | probtrackx2 -x Results/SeedImage_NaSp.nii -l --onewaycondition -c 0.2 -S 2000 --steplength=0.5 -P 5000 --fibthresh=0.01 --distthresh=0.0 --sampvox=0.0 --forcedir --opd -s DTIImgBCF.bedpostX/merged -m DTIImgBCF.bedpostX/nodif_brain_mask --dir=Results --waypoints=Results/TargetImage_NaSp.nii --waycond=AND
|
ac837dcd7be9033ad972fca3299c1224908e61cc3ed5afb63e302d8256b5c873 | Shell | 307 | 15 | # #!/bin/bash
for i in {1..35}; do
file_list=("/Users/bo/Documents/data_liujia_lab/analysis_liuP1_greeble/MRI_raw_bold_4d/sub"$i"_s*")
fslmerge -tr "/Users/bo/Documents/data_liujia_lab/analysis_liuP1_greeble/MRI_raw_bold_4d_session_connected/bold_4d_all_session_sub"$i".nii" $file_list 2
done
|
76cf22b1a4d0387aa2a409cf76ccc482becc95306d8cf72bbe440046efa4a20d | Shell | 308 | 14 | #!/bin/bash
#SBATCH --time=7:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --job-name=gnn_ddd_pars_free_gps
#SBATCH --output=logs/gnn_ddd_pars_free_gps-%j.log
#SBATCH --mem=16GB
#SBATCH --partition=regular
name=${1}
ml R
Rscript ../Script/ddd_pars_est_free_data_GPS.R ${name} |
ab4521d3aca1154d5ebed1377ae579351b15ddab346a095f6367ef9aa31a708f | Shell | 309 | 7 | ############### FABERRUDY 2000 ##############################
MODEL_FILE_CPU="luo_rudy_1991.c"
MODEL_FILE_GPU="luo_rudy_1991.cu"
COMMON_HEADERS="luo_rudy_1991.h"
COMPILE_MODEL_LIB "luo_rudy_1991" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
########################################################## |
afbbd974b3148214c055852397a0bc4621539f553dc5d8708f8528a715978c04 | Shell | 309 | 4 | ALG_SOURCE_FILES="grid/grid.c grid/grid_refinement.c grid/grid_derefinement.c cell/cell.c cell/cell_derefinement.c cell/cell_refinement.c grid_purkinje/grid_purkinje.c"
ALG_HEADER_FILES="grid/grid.h cell/cell.h grid_purkinje/grid_purkinje.h"
COMPILE_STATIC_LIB "alg" "$ALG_SOURCE_FILES" "$ALG_HEADER_FILES"
|
784dc33f8a274f76131969faa9440951b143390365203aaf3287478e53721b53 | Shell | 310 | 13 | #!/bin/bash
#
#SBATCH --job-name=Create_v9_RDS
#
#SBATCH --time=20:00:00
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=80G
#SBATCH --error=Create_v9_RDS-%j.out
module load R/4.1.0
Rscript convert_tsv_to_rds.R --tsv_file results/deseq_all_comparisons.tsv --outdir results --basename deseq_all_comparisons
|
012c01164643cde09df7a88cd8eee76b6e061e796ca93a73bcb22e4fb6a9b28f | Shell | 311 | 11 | #!/bin/bash
#SBATCH --time=1-00:00:00
#SBATCH --partition=ccb
# Example SLURM script for getting the raw sequence class scores
# for input sequence predictions (i.e. no variants)
input_preds="${1:-}" # input preds path
outdir="${2:-}" # output dir path
sh ./2_raw_sc_score.sh $input_preds $outdir
|
b8f93b4655164fc55d08ac91f8182090d268f202a2e329a41f0dc938959ce20a | Shell | 311 | 15 | #!/bin/env bash
NT=1 # number of trajectories
function gen_cluster_gmx_index () {
dname=cluster_gmx_ndx
[[ ! -e $dname ]] && mkdir -p $dname
for ((it=0; it<$NT; it++ )); do
inp=assignments.txt
out=cluster.ndx
python GenGromacsIndex.py $inp > $out
done
}
gen_cluster_gmx_index
|
d0574230b1bce614e6fcc82856ef19be6b38da01c52566e8a888095c3c097dce | Shell | 314 | 18 | #!/bin/env bash
NT=1 # number of trajectories
function gen_cluster_gmx_index () {
dname=cluster_gmx_ndx
[[ ! -e $dname ]] && mkdir -p $dname
for ((it=0; it<$NT; it++ )); do
inp=assignments.txt
out=cluster.ndx
python GenGromacsIndex.py $inp > $out
done
}
gen_cluster_gmx_index
|
e8c05942d921405f48af03115e2be0139cdaa10887ee93d722578711b4f31f3b | Shell | 316 | 15 | #!/bin/bash
#SBATCH --time=1:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=gnn_ddd_data
#SBATCH --output=logs/gnn_ddd_data-%j.log
#SBATCH --mem=2GB
#SBATCH --partition=regular
name=$1
ml R
# Call the R script test.R with the variables name and cap as arguments
Rscript ../Script/bd_data.R "$name"
|
56bbbc790d56dc775cddb09ce53159c167b530278e4d3256b86dddb7f92d37e4 | Shell | 317 | 3 | #! /bin/bash
marine.py --bam_filepath $MARINE/examples/data/bulk_AI.md.subset.bam --output_folder $MARINE/examples/bulk_subset_AI --strandedness 2 --cores 16 --annotation_bedfile_path $MARINE/annotations/hg38_gencode.v35.annotation.genes.bed --contigs "1" --bedgraphs "AI" --min_base_quality 15 --min_dist_from_end 5 |
dcdbb721d9461c51d82067da8fd2ced49fc85035c131f08c42a42a0eb4133500 | Shell | 317 | 3 | #! /bin/bash
marine.py --bam_filepath $MARINE/examples/data/bulk_CT.md.subset.bam --output_folder $MARINE/examples/bulk_subset_CT --strandedness 2 --cores 16 --annotation_bedfile_path $MARINE/annotations/hg38_gencode.v35.annotation.genes.bed --contigs "1" --bedgraphs "CT" --min_base_quality 15 --min_dist_from_end 5 |
fad0b60d01acb04a7728ea47101807fed290036fffcbad1077bd04dd07d93e9f | Shell | 317 | 8 |
# clone pyAFQ (patched version)
# This work used a development version of pyAFQ, based on v1.3.3 (commit hash fe30b287)
# link: https://github.com/tractometry/pyAFQ/tree/luo_wm_dev
cd /cbica/projects/luo_wm_dev/two_axes/software/
git clone --single-branch --branch luo_wm_dev git@github.com:tractometry/pyAFQ.git
|
aa7c5783c4619942ad75f77be2e9e523cf334f33ac65416b9db3505376812959 | Shell | 319 | 7 | ################ BONDARENKO ##############################
MODEL_FILE_CPU="bondarenko_2004.c"
MODEL_FILE_GPU="bondarenko_2004_GPU.cu"
COMMON_HEADERS="bondarenko_2004.h"
COMPILE_MODEL_LIB "bondarenko_2004" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
########################################################### |
e81ba08e51a15cdba912a47ff4768f6741a10b24ac2fc7287f8ad7d92f5615c1 | Shell | 320 | 15 | #!/bin/bash
#SBATCH --job-name=predictDannce
# Job name
#SBATCH --mem=10000
# Job memory request
#SBATCH -t 1-00:00
# Time limit hrs:min:sec
#SBATCH -N 1
#SBATCH -c 8
#SBATCH -p olveczkygpu,gpu
#SBATCH --gres=gpu:1
#SBATCH --constraint=cc5.2
module load Anaconda3/5.0.1-fasrc02
source activate dannce
dannce-predict "$@" |
785bf6b821f683dc685ea4b1369dbc22821c5e024f2aacc937e4d848bac01118 | Shell | 321 | 9 | #!/bin/bash
#$ -M mzarodn2@nd.edu # Email address for job notification
#$ -m abe # Send mail when job begins, ends and aborts
#$ -pe smp 12 # Specify parallel environment and legal core size
#$ -q long # Specify queue
#$ -N QC01 # Specify job name
conda activate bioinfo
Rscript 01_QC.r... |
079c80ecc70337e51ba7397a5711066aa110d54c38344ee069d806c67f89a53e | Shell | 322 | 28 | #!/bin/bash
set -e
cd ../..
if [ $# -eq 0 ]; then
echo "$0 experimental_date animal_id ?"
exit 1
else
ED=$1
ID=$2
fi
##
run_python() {
local m=$1
local a=$2
shift 2
echo "*** now run ${ED}_${ID}__2P_YW/signal $m $a ***"
python -m rscvp.$m $a \
-D "$ED" \
-A "$ID"
}
##
run_python signal c... |
07a26e4229e6467c56455b0e5a54fdbcb708933c94d18cfb6dc214fc7c7dc296 | Shell | 322 | 11 | # CITE-seq-Count v1.4.2-develop
# https://github.com/hisplan/CITE-seq-Count/releases/tag/1.4.2-develop
version="1.4.2-develop"
# CITE-seq-Count v1.5.0-alpha
# https://github.com/Hoohm/CITE-seq-Count/releases/tag/1.5.0-alpha
# version="1.5.0-alpha"
# docker related
registry="quay.io/hisplan"
image_name="cite-seq-count... |
2802b5744fdff1f4dce8b8b6c41d96fa5fa97da3f4e4be151c82139f27c0511e | Shell | 322 | 10 | #!/bin/bash
# If no arguments are passed, run pytest with coverage
if [ "$#" -eq 0 ]; then
mkdir -p /test_results
pytest tests -vv -n auto --cov=pydesigner --cov-report=xml:/test_results/coverage.xml --junitxml=/test_results/results.xml
else
# Otherwise, run the command passed as arguments
exec "$@"
f... |
1734198934ef5316951551bb9f1dae6cde48fd25d754dae3c248a1de433079c6 | Shell | 323 | 7 | ############### OHARA_RUDY 2000 ##############################
MODEL_FILE_CPU="Ohara_Rudy_2011.c"
MODEL_FILE_GPU="Ohara_Rudy_2011.cu"
COMMON_HEADERS="Ohara_Rudy_2011.h"
COMPILE_MODEL_LIB "ohara_rudy_endo_2011" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
#######################################################... |
545b93a2aa5466ed3442a423f8d7a80c5301e3908dc1c7e5a98d1d569c31eba7 | Shell | 323 | 18 | #!/bin/bash
#SBATCH -J make_profiling
#SBATCH -o profiling.o%j
#SBATCH -t 10:00:00
#SBATCH -N 1 -n 4
#SBATCH --gpus=1
source activate Ali
python examples/profileing.py \
--dataset glial_panel_all\
-b 2048 \
--outputCSV /home/lhuang37/repos/VisQ-Search-Engine/examples/paper_results/glial.csv\
--panel glial_panel
... |
b9bfb2ab080c069a5c33eb8ac232d3af8357f05082c6474772a42b3102c43bd0 | Shell | 323 | 9 | #!/bin/bash
# collect profdata
llvm-profdata-9 merge unittest/ut*.profraw test/st*.profraw -o coverage.profdata
# Write total coverage
echo "Code Coverage:"
llvm-cov-9 report ./unittest/unittest -object ./nastja -instr-profile=coverage.profdata -ignore-filename-regex="/external/" | tail -1
#Regex: ^TOTAL.* (\d+\.\d+\... |
18055600efd62f2912e51a9482faaa6dc991c70015e1e1ba812a4334ce411fd6 | Shell | 327 | 13 | #!/bin/bash
set -e
set -o pipefail
# set up running directory
cd "$(dirname "${BASH_SOURCE[0]}")"
# Run R script to generate JSON file
Rscript --vanilla 00-PB-select-pathology-dx.R
# Run R script to subtype PB using methylation data
Rscript -e "rmarkdown::render('01-molecular-subtype-pineoblastoma.Rmd', clean = ... |
f9de3cf0519b924ebae40c60968cdfdebf11caa07097fc1b5e970ea0f5e3cee6 | Shell | 327 | 11 | COMMIT=${1}
COMMIT="$(echo "${COMMIT}" | tr -d '[:space:]')"
export COMMIT
NO_TAG="ghcr.io/${2}/pyafq"
TAG="${NO_TAG}:${COMMIT}"
TAG2="${NO_TAG}:latest"
TAG="$(echo "${TAG}" | tr -d '[:space:]')"
TAG2="$(echo "${TAG2}" | tr -d '[:space:]')"
echo $TAG
docker build --no-cache -t $TAG -t $TAG2 --build-arg COMMIT ./pyafq_... |
b753b8bf85b8d9618a35c7c55933f43e28633438a50f9b0ea272aaeead52211f | Shell | 331 | 17 | #!/bin/bash
#SBATCH --time=08:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=export_eve
#SBATCH --output=logs/export_eve-%j.log
#SBATCH --mem=32GB
#SBATCH --partition=regular
ml R
# Capture the arguments
file=$1
index=$2
# Pass the arguments to the R script
Rscript ../../Script/export_eve_data.R "$fil... |
d75e0a4fa7ec52539f54bf2111e01a80b9e6054e98270a3a0a2bd1d843d092c1 | Shell | 331 | 6 | #!/usr/bin/env bash
# reconfigure & build libs
./dune-common/bin/dunecontrol --opts=dumux-braindiffusion-miniapp/cmake.opts bexec rm -r CMakeCache.txt CMakeFiles
./dune-common/bin/dunecontrol --opts=dumux-braindiffusion-miniapp/cmake.opts cmake
./dune-common/bin/dunecontrol --opts=dumux-braindiffusion-miniapp/cmake.op... |
fa1763bd96e66e25504867cf796d2328a99108c611f0401a55a508b5f5cfff7c | Shell | 332 | 7 |
CUDA_VISIBLE_DEVICES=1 python protein_DIFF/inference.py \
--ckpt result/weight/Jun_5_ago_dataset=CATH_result_lr=0.0002_wd=0.0_dp=0.08_hidden=256_noisy_type=uniform_embed_ss=False_89474.pt \
--target_protein dataset/Ago/AGO_050_model_3_ptm.pt \
--target_protein_dir dataset/Ago/process/ \
--gen_num 100 \
--output_dir re... |
2a9a1a2f018bbf0892cc52a2dbfd76c4d4aabdb460cc9e9adc33427692ed02b0 | Shell | 333 | 29 | #!/bin/bash
set -e
cd ../..
if [ $# -eq 0 ]; then
echo "$0 experimental_date animal_id ?"
exit 1
else
ED=$1
ID=$2
fi
##
run_python() {
local m=$1
local a=$2
shift 2
echo "*** now run ${ED}_${ID}__2P_YW/signal $m $a ***"
python -m rscvp.$m $a \
-D "$ED" \
-A "$ID" \
"$@"
}
##
run_pyth... |
95421a6e29d2758b8e73300ac5149b642feb5d8461842d8a9fdd78e011f9be8f | Shell | 333 | 12 | #!/bin/bash
set -e
set -o pipefail
# Set the working directory to the directory of this file
cd "$(dirname "${BASH_SOURCE[0]}")"
# Run rscript to generate json file for cranio subsetting
Rscript --vanilla 00-CRANIO-select-pathology-dx.R
# Run notebook
Rscript -e "rmarkdown::render('01-craniopharyngiomas-molecular-su... |
4de719d1d63f0e7161f3640f7a504f69c11036251f1eb38dab3dabef9e7b5aec | Shell | 334 | 6 | ############## ToRORd Land Mixed ENDO_MID_EPI ##############################
MODEL_FILE_CPU="ToRORd_Land_mixed_endo_mid_epi.c"
MODEL_FILE_GPU="ToRORd_Land_mixed_endo_mid_epi.cu"
COMMON_HEADERS="ToRORd_Land_mixed_endo_mid_epi.h"
COMPILE_MODEL_LIB "ToRORd_Land_mixed_endo_mid_epi" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$CO... |
aaab9c389326bc600bf24266b1f22e8e4568e5c15148a5dbb8013adff87b078d | Shell | 335 | 13 | #! /bin/sh
cd tests
. ./compat.sh
${DIR}/generate_sequence -v -o seq10m -m 10 -m 22 -s 3141592653 10000000
${DIR}/generate_sequence -v -o seq1m -s 1040104553 1000000 1000000 1000000 1000000 1000000
for i in 0 1 2 3 4; do
gzip -c seq1m_$i.fa > seq1m_$i.fa.gz
done
${DIR}/generate_sequence -v -q -o seq10m -s 14735... |
cdb9828f14a6e94d6b70219d1e58aece41fc2dc1458391a2b88094edb7b8c84b | Shell | 335 | 14 | #!/bin/bash
#SBATCH --job-name=gene_combine
#SBATCH --partition=256GBv1
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --time=24:00:00
#SBATCH --output=mutiTaskJob.%j.out
#SBATCH --error=mutiTaskJob.%j.time
#SBATCH --mail-user=chen.tang@utsouthwestern.edu
#SBATCH --mail-type=ALL
module add python/3.8.x-anaconda
python3... |
1ee1c8dfbfeb95f9ff4dabe29e7e2eee5a8cbea246015e177b2b4cd9e7d15175 | Shell | 337 | 10 | RESTORE_STATIC_DEPS="alg config_helpers utils sds tinyexpr"
if [ -n "$CUDA_FOUND" ]; then
RESTORE_STATIC_DEPS="$RESTORE_STATIC_DEPS"
EXTRA_CUDA_LIBS="c cudart "
fi
CHECK_CUSTOM_FILE
COMPILE_SHARED_LIB "default_restore_state" "restore_state.c ${CUSTOM_FILE}" "" "${RESTORE_STATIC_DEPS}" "$EXTRA_CUDA_LIBS" "$CU... |
25f5f806054f6b75381e4ee62e9da0b8b8a48563a6b4aaaa17e0d1d82344b0c0 | Shell | 337 | 10 | SAVE_STATE_STATIC_DEPS="alg config_helpers utils sds tinyexpr"
if [ -n "$CUDA_FOUND" ]; then
SAVE_STATE_STATIC_DEPS="$SAVE_STATE_STATIC_DEPS"
EXTRA_CUDA_LIBS="cudart"
fi
CHECK_CUSTOM_FILE
COMPILE_SHARED_LIB "default_save_state" "save_state.c ${CUSTOM_FILE}" "" "${SAVE_STATE_STATIC_DEPS}" "$EXTRA_CUDA_LIBS" "$CU... |
f255d3467145cf03faba41e6895e8c87aed45cc6657aee56a196397b0631a823 | Shell | 337 | 5 | applywarp --ref=dataB --in=SeedImage --warp=MNI2T1transf.nii.gz --out=SeedImage_T1Sp
flirt -in SeedImage_T1Sp -ref FA -out SeedImage_NaSp -init T12FA.mat -applyxfm
applywarp --ref=dataB --in=TargetImage --warp=MNI2T1transf.nii.gz --out=TargetImage_T1Sp
flirt -in TargetImage_T1Sp -ref FA -out TargetImage_NaSp -init T12... |
00169c9d08d74312d740c2f45323cbebb8436fe9733a353cf1f690f303914e8a | Shell | 338 | 14 | #!/bin/bash
#SBATCH --job-name=gene_denoise_v1
#SBATCH --partition=256GBv1
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --time=4:00:00
#SBATCH --output=mutiTaskJob.%j.out
#SBATCH --error=mutiTaskJob.%j.time
#SBATCH --mail-user=chen.tang@utsouthwestern.edu
#SBATCH --mail-type=ALL
module add python/3.8.x-anaconda
pytho... |
2161f423d7aba700f93e84cdc695dfcb0785d47ad336553494767559b6d94577 | Shell | 338 | 10 |
# https://github.com/combiozone/CellTypeEstimate
# mouse
Rscript CellTypeEstimate/cte4os.R --rds multiome.rds --db mm.brain.v2 --assay SCT --reduction 'wnn.umap' --plot --outdir out_celltype
# human
#Rscript CellTypeEstimate/cte4os.R --rds multiome.rds --db hs.brain --assay SCT --reduction 'wnn.umap' --plot --outdi... |
75b3058eadc26638530814cd552c955d362189304d15265caa10c50dd53f9cd4 | Shell | 338 | 18 | #!/bin/bash
set -e -E -u -o pipefail
echo "installing lightgbm and its dependencies"
pip install \
--prefer-binary \
--upgrade \
-r ./.ci/pip-envs/requirements-latest.txt \
dist/*.whl
echo "installed package versions:"
pip freeze
echo ""
echo "running tests"
pytest tests/c_api_test/
pytest tests/pyt... |
231a5c8be967f56662f76d29d554b852765540d2a38750f0921e42ced3992cfe | Shell | 340 | 18 | #!/bin/bash
fBase=$1
inFileNames="${@:2}"
rm -f ${fBase}_*_task-runs.txt
i=0
for inFileName in $inFileNames
do
i=$(( i+1 ))
task=$(jq < $(remove_ext ${inFileName}).json '.TaskName')
# remove quotes (first suffix then prefix):
task="${task%\"}"
task="${task#\"}"
echo "$i " >> ${fBase}_${task}_... |
d8b1eb0279118cbe57163f9e86b9f884c1ade515c7273b8bd5bb6048fdb3512c | Shell | 340 | 10 | #!/bin/bash
#compress data needed to trace coverage in testing
find . -name "*.gcno" > files
echo "nastja" >> files
echo "unittest/unittest" >> files
echo "CTestTestfile.cmake" >> files
echo "unittest/CTestTestfile.cmake" >> files
echo "test/CTestTestfile.cmake" >> files
tar czf artifacts.tar.gz --files-from files
ls -... |
3c08b70398e969b1f67888587ba54431bfd2933920c3986482b203204ae48a7a | Shell | 342 | 12 | #!/bin/bash
echo "Start"
mkdir -p ncu_profile
python parsed_ncu_search.py --M 1024 --N 1024 --K 1024
echo "Finished 1024"
python parsed_ncu_search.py --M 2048 --N 2048 --K 2048
echo "Finished 2048"
python parsed_ncu_search.py --M 4096 --N 4096 --K 4096
echo "Finished 4096"
python parsed_ncu_search.py --M 8192 --N 8192 ... |
5924863bd6161be20de1ea3190675676082962a1e5152ac95330c755c693d7e6 | Shell | 342 | 12 | #!/bin/bash
GH_WORKFLOW_TRIGGER=$1
PULL_REQUEST_SHA=$2
STATUS_DESCRIPTION=$3
CONTEXT=$4
curl -L -X POST \
-H "Authorization: token $GH_WORKFLOW_TRIGGER" \
-d $'{"state": "success", "description": "'"$STATUS_DESCRIPTION"'",
"context": "'"$CONTEXT"'"}' \
"https://api.github.com/repos/brain-score/brain-score/status... |
eb55a02e8a013c345bf62de93dec1e2e437680c6d62d53780fdaa5f026a53cb1 | Shell | 342 | 7 | wget http://ogb-data.stanford.edu/data/lsc/pcqm4m-v2-train.sdf.tar.gz
md5sum pcqm4m-v2-train.sdf.tar.gz # fd72bce606e7ddf36c2a832badeec6ab
tar -xf pcqm4m-v2-train.sdf.tar.gz # extracted pcqm4m-v2-train.sdf
wget 'https://dgl-data.s3-accelerate.amazonaws.com/dataset/OGB-LSC/pcqm4m-v2.zip'
unzip pcqm4m-v2.zip
mv pcqm4m-v... |
28827e3bea7811e61571f673481ed09db340e0e61742085479246d901d086cb4 | Shell | 343 | 4 |
#Code we used to derive the 40 components, to run FSL must be installed. Note: fix_ICA_paths.txt can be found in our repo in the data folder.
melodic -i /data1/neurdylab/datasets/nki_rockland/vigilance_analysis/fix_ICA_paths.txt -d 40 -o /data1/neurdylab/datasets/nki_rockland/vigilance_analysis/FIX_ICA_40comps --Oori... |
a3d6a89dd52d995f02287991e424fd197c03992b0f8f0cf9ffe36f8c08a9999d | Shell | 344 | 15 | #!/bin/bash
#SBATCH --job-name=predictCom
# Job name
#SBATCH --mem=10000
# Job memory request
#SBATCH -t 0-03:00
# Time limit hrs:min:sec
#SBATCH -N 1
#SBATCH -n 8
#SBATCH -p olveczkygpu,gpu,cox,gpu_requeue
#SBATCH --gres=gpu:1
#SBATCH --constraint=cc5.2
module load Anaconda3/5.0.1-fasrc02
source activate dannce
com-pr... |
d1b7c2c8f2ee07c93afb779390fd42621dbdb0037a9663add6ed9e88e0258f7f | Shell | 349 | 21 | #!/bin/bash
BUILD_DIR="build"
BUILD_TYPE="Release"
if [[ "$#" -eq 1 ]]; then
BUILD_DIR=$1
fi
if [[ "$#" -eq 2 ]]; then
BUILD_DIR=$1
BUILD_TYPE=$2
fi
if [[ ! -d "${BUILD_DIR}" ]]; then
echo "Directory ${BUILD_DIR} does not exist. Creating."
mkdir ${BUILD_DIR}
fi
cd ${BUILD_DIR}; cmake -DCMAKE_BUILD... |
034fa5a7831e09eca87fa6536a5cd40c10911af3dbfe133e6795afce9e3925af | Shell | 350 | 15 | #!/bin/bash
#SBATCH --job-name=predictDannce
# Job name
#SBATCH --mem=10000
# Job memory request
#SBATCH -t 0-03:00
# Time limit hrs:min:sec
#SBATCH -N 1
#SBATCH -n 8
#SBATCH -p olveczkygpu,gpu,cox,gpu_requeue
#SBATCH --gres=gpu:1
#SBATCH --constraint=cc5.2
module load Anaconda3/5.0.1-fasrc02
source activate dannce
dan... |
c7cedd39c0e2a2c69e73cb27377e4f2d69c308331a09af49c28eaefd1106c931 | Shell | 350 | 17 | #!/bin/bash
#SBATCH --time=16:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=gnn_ddd_data
#SBATCH --output=logs/gnn_ddd_data-%j.log
#SBATCH --mem=2GB
#SBATCH --partition=regular
name=$1
cap=$2
index=$3
ml R
# Call the R script test.R with the variables name and cap as arguments
Rscript ../Script/ddd_d... |
b50e6fec69788acc1b27f7a4cd8b07c24cf35f21fe6174fb3b37ce36dbbe970d | Shell | 351 | 7 | ############## MITCHELL SHAEFFER 2003 ##############################
MODEL_FILE_CPU="mitchell_shaeffer_2003.c"
MODEL_FILE_GPU="mitchell_shaeffer_2003.cu"
COMMON_HEADERS="mitchell_shaeffer_2003.h"
COMPILE_MODEL_LIB "mitchell_shaeffer_2003" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
##########################... |
bb624bcef955c5fc699fb7c954f8a4730a1990618cf70c78e1b2bac9b349fda6 | Shell | 351 | 14 | #!/bin/bash
#SBATCH --job-name=merge_feat
#SBATCH --partition=compute
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --output=./outputs/neukin_merge.o%j
#SBATCH --error=./error/neukin_merge.e%j
eval "$(/opt/conda/bin/conda shell.bash hook)"
source /etc/profile.d/conda.sh
conda activate neural_... |
d88c7541d40a55e22dddf41e4aaa77a4b4997f3d7b60df0b2b7d49e9c1d4857d | Shell | 351 | 12 | mkdir -p libc++-objects
mkdir -p libc++abi-objects
mkdir -p combined
cd combined
if [[ `uname` == 'Darwin' ]]; then
echo Archive Darwin
clang -r -nostdlib $1 -o libc++.o -Wl,-all_load ../libc++.a ../libc++abi.a
else
echo Archive Linux
clang -r -nostdlib -o libc++.o -Wl,--whole-archive ../libc++.a ../libc++abi.a... |
0783a897e3c3686fdced1cf2f20780e6e2f2084858dc0da2e26c7a5a85958cda | Shell | 352 | 31 | #! /bin/bash
set -e
cd ../..
if [ $# -eq 0 ]; then
echo "$0 experimental_date animal_id ?"
exit 1
else
ED=$1
ID=$2
fi
##
run_python() {
local m=$1
local a=$2
shift 2
echo "*** now run $m $a ***"
python -m rscvp.$m $a \
-D "$ED" \
-A "$ID" \
"$@"
}
run_python behavioral bs \
--vcut... |
083db75dca43598f5cbd38406b7436997321ebf5134d76f57e43b8f5d5d55ec1 | Shell | 352 | 12 | #!/bin/bash
echo $LSB_JOBINDEX
echo $1
folder=$(head -n $LSB_JOBINDEX $1 | tail -n1)
echo $folder
TPATH=refgenomes/cellranger/refdata-cellranger-GRCh38-3.0.0
sampleid=cellranger-hg38
/software/cellranger-3.1.0/cellranger count --id=${sampleid} --fastqs=${folder} --transcriptome=${TPATH} --jobmode=local --localcores=... |
119563beab9474ad9b13153e226176fed53091b717ae0a1926a003e0784032d9 | Shell | 352 | 15 | #!/bin/bash
if [[ -z "$1" ]]; then
echo "Missing folder argument."
exit 1
fi
if [[ -z "$2" ]]; then
echo "Missing target."
exit 1
fi
target="kasper:nastja_remote"
echo "Syncing $1 to $target"
rsync -avz --delete --exclude '.git' --exclude 'build*' --exclude 'cmake-build-*' --exclude 'external' --exclude '.cl... |
3ab2855d5a09e3202dba0916746f80dfc2c39255a6fedd3721e4a2fe07d94478 | Shell | 352 | 15 | #!/bin/bash
# Script to run all steps of dannce in a single job.
#
# Inputs: com_config - path to com config.
# Example: sbatch com.sh /path/to/com_config.yaml
#SBATCH --job-name=com
#SBATCH --mem=5000
#SBATCH -t 5-00:00
#SBATCH -N 1
#SBATCH -c 1
#SBATCH -p olveczky
set -e
sbatch --wait holy_com_train.sh $1
wait
sbatc... |
d0a382fb74f283ace0071bd42a9f27e6733f38d5650d9fbf6f6df83cffa20e5c | Shell | 353 | 8 | UPDATE_MONODOMAIN_STATIC_DEPS="alg config_helpers utils"
if [ -n "$CUDA_FOUND" ]; then
UPDATE_MONODOMAIN_STATIC_DEPS="$UPDATE_MONODOMAIN_DEPS"
UPDATE_MONODOMAIN_DYNAMIC_DEPS="cudart"
fi
COMPILE_SHARED_LIB "default_update_monodomain" "update_monodomain.c" "" "$UPDATE_MONODOMAIN_STATIC_DEPS" "$UPDATE_MONODOMAIN_DY... |
c41f2563027c2255b4d9334cd087eef371a1c7a537ba1b0901a34d3ee0633cc6 | Shell | 355 | 8 | #!/bin/bash
for i in $(seq 1 3); do
./bin/ErrorCalculator inputs/corner-activation-map-sc0.vtu inputs/corner-activation-map-sc$i.vtu outputs/corner-error-activation-time-sc0-sc$i.vtu
./bin/ErrorCalculator inputs/corner-conduction-velocity-sc0.vtu inputs/corner-conduction-velocity-sc$i.vtu outputs/corner-error-condu... |
2b51a8d735bf7994f0d7409246cc64dc2124d8eb2bc42ea8909aac945cb5b963 | Shell | 356 | 6 | # We want to exclude webhooks_receiver from SSRF protection,
# so that the server can access it.
# --allow-address doesn't allow hostnames, so we have to resolve
# the IP address ourselves.
webhooks_ip_addr="$(getent hosts webhooks.internal | head -1 | awk '{ print $1 }')"
export SMOKESCREEN_OPTS="$SMOKESCREEN_OPTS --a... |
21569022fe41e5c140a18c4cee111f5e6f79cfbf8a78930111cd883f8cf7779e | Shell | 358 | 17 | #!/bin/bash
set -e
set -o pipefail
# set up running directory
cd "$(dirname "${BASH_SOURCE[0]}")"
# Run R script to generate pathology JSON fiel for sample subsetting
Rscript 00-EWS-select-pathology-dx.R
# Run notebook to subtype EWS per sample_id if hallmark fusion in RNAseq samples
Rscript -e "rmarkdown::ren... |
c8e20a6955a39d36326edce692795f6077e597b25d2acadfe7004d51443ac4b7 | Shell | 358 | 7 | ############## ARPF 2009 ##############################
MODEL_FILE_CPU="stewart_aslanidi_noble_2009.c"
MODEL_FILE_GPU="stewart_aslanidi_noble_2009.cu"
COMMON_HEADERS="stewart_aslanidi_noble_2009.h"
COMPILE_MODEL_LIB "stewart_aslanidi_noble_2009" "$MODEL_FILE_CPU" "$MODEL_FILE_GPU" "$COMMON_HEADERS"
###################... |
ec37f0db0c085e4cdcaa70484f04c245e939cbc2e11d98236871a2676e28a62b | Shell | 359 | 16 | #!/bin/bash
#SBATCH --time=3:59:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --job-name=gnn_emp_mle_ddd
#SBATCH --output=logs/gnn_emp_mle_ddd-%j.log
#SBATCH --mem=3GB
#SBATCH --partition=regular
file_name=${1}
family_name=${2}
tree_name=${3}
ml R
Rscript ../../../../Script/ddd_emp_mle.R $... |
b9abf4d8d133a4f48d61ca10760dafb3c405b2c6e5a7a57f9067e649cd39b782 | Shell | 361 | 17 | #!/bin/bash
#
# hpfilter.sh <fName> <TR> <hpCutOff>
#
# - applies a temporal high-pass filter to fName
# - hpCutOff is the cut-off cycle (longest) in seconds
fName=$1
TR=$2
hpCutOff=$3
hpSigma=$(bc -l <<< "(${hpCutOff}/2)/${TR}")
fslmaths $fName -Tmean tempMean
fslmaths $fName -bptf ${hpSigma} -1 -add tempMean $(rem... |
cda33f6a318eea4559d9bec942b9bdbf3a111f1686c41c96a5948926a61f592d | Shell | 363 | 22 | #!/bin/bash
set -euo pipefail
asl_space_img=$1
asl_space_t1w_img=$2
target_t1w_img=$3
# output
asl_in_t1w_img=$4
output_dir=$(dirname $target_t1w_img)
mkdir -p $output_dir
flirt \
-in $asl_space_img \
-ref $asl_space_t1w_img \
-out $asl_in_t1w_img \
-applyxfm \
-usesqform \
-interp trilinear... |
d6f4959e22ed8ba3d5a40c6d5bd8c6b364ec3e8d34edb539b955414372e92a7f | Shell | 364 | 8 | #!/bin/bash
dataset=$1
tract_name=$2
# Run the R script for the specific dataset and tract
singularity run --cleanenv /cbica/projects/luo_wm_dev/two_axes/software/r_packages/r-packages-for-cubic_0.0.7.sif Rscript --save /cbica/projects/luo_wm_dev/two_axes/code/significance_testing/NEST/tract_to_cortex/NEST_wrapper_e... |
e7255b86a5453529315bad4a0b1390cb2e94be7b39163c03b587bc09737b8649 | Shell | 365 | 13 |
input_folder=$1
sample=$2
output_folder=$3
barcode_file=$4
cutoff=$5
mismatch=1
python="/net/shendure/vol12/projects/sciRNAseq_script/anaconda2/bin/python2.7"
python_script="/net/shendure/vol1/home/martin91/scripts/sciRNAseq3/sam_split.py"
$python $python_script $input_folder/$sample.sam $barcode_file $output_folder... |
1964b53d2b103ffeca402336df9b4dca09a37d06d9e826596fa2697bb898c72d | Shell | 366 | 5 | #!bin/bash
plink1.9 --bfile merged_plink --geno 0.05 --mind 0.05 --maf 0.05 --hwe 1e-6 --make-bed --out merged_plink_qc
plink1.9 --bfile merged_plink_qc --pca --out merged_plink_qc_pca
./gcta/gcta64 --bfile merged_plink_qc --make-grm --thread-num 10 --out merged_plink_qc_grm
./gcta/gcta64 --grm merged_plink_qc_grm --ma... |
59c8f88898cb315a8240c01887e7d1dddb7bab43492f6b7e74c276cb75913cb7 | Shell | 367 | 7 | cd $(git rev-parse --show-cdup) # Change to the root of the repository
git ls-files -z | # List all files in the repository
while IFS= read -rd '' f; do # Read each file in the repository
if [[ $f != *.(png|md|h5|txt) ]]; then
tail -c1 < "$f" | read -r _ || echo >> "$f"; # Add a newline if the file has no ... |
a37845b231294bc2c16a92db35e6915607fb2aac9c9e76b2cc50001f65aebf9d | Shell | 367 | 21 | #!/bin/bash
#SBATCH --time=3-04:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=gnn_sim_qt
#SBATCH --output=logs/gnn_sim_qt-%j.log
#SBATCH --mem=64GB
#SBATCH --partition=regular
ml R
Rscript -e "devtools::install_github('EvoLandEco/eve')"
name=${1}
param_set=${2}
nrep=${3}
ml R
Rscript ../Script/quali... |
4e67655762c478075f5e53ee53f0247ca4fb2c22df44828fa6b4dddf73f39783 | Shell | 369 | 13 | #!/bin/bash
#SBATCH --time=1-00:00:00
#SBATCH --partition=ccb
# Example SLURM script for getting the variant effect sequence class scores
ref_preds="${1:-}" # ref preds path
alt_preds="${2:-}" # alt preds path
outdir="${3:-}" # output dir path
no_tsv="${4:-}" # --no-tsv flag
sh ./2_varianteffect_s... |
618d673d6d559c138ae7507824ff94c16c2bf33165f583093347b972c98da666 | Shell | 369 | 11 | #!/bin/bash
#Change PROT below to match your system
#NS decides number of states to be plotted
PROT=cTEMPPROT
NS=5
for ((i=1; i<=$NS; i++)); do
echo 'Calculating cluster' ${i}
python calcFreeEnergy_v2_5mers.py s1${PROT}_phipsi/cluster$i.txt s1${PROT}_cluster$i.png
python calcFreeEnergy_v2_5mers.py s2${PROT}_p... |
524033883a3286dbe15998d9c2ab9c7cfe60ffeecc07d641daa8aaa8321687fe | Shell | 370 | 15 | #!/bin/bash
# Script to run all steps of dannce in a single job.
#
# Inputs: dannce_config - path to com config.
# Example: sbatch dannce.sh /path/to/dannce_config.yaml
#SBATCH --job-name=dannce
#SBATCH --mem=5000
#SBATCH -t 5-00:00
#SBATCH -N 1
#SBATCH -c 1
#SBATCH -p olveczky
set -e
sbatch --wait holy_dannce_train.s... |
e1f15405d3aacb1a33fe0f7b2b6c7a0181ade8779ba52cea820f639e9fcb5918 | Shell | 370 | 10 | data_directory="/data/wuqinhua/phase/covid19/datasets/pre_data/16_Unterman_2022/data"
for file in "$data_directory"/*.tar.gz; do
if [ -f "$file" ]; then
filename=$(basename "$file" .tar.gz)
mkdir -p "$data_directory/$filename"
tar -xzf "$file" -C "$data_directory/$filename"
echo "已解压文件: $file 到目录: $d... |
446477eb6c445d9e4dab40f843cf6f291d8e272fa2658b506df2bd8db0f48f63 | Shell | 371 | 20 | #!/bin/bash
while IFS='' read -r line || [[ -n "$line" ]]; do
error_file=$(basename "${line}")
if test -f "$line"; then
if cc -I/opt/cuda/include/ -Werror "${line}" -o tmp.gch > "${error_file}".txt
then
echo Header "$line" compiled sucessfuly!
rm "${error_file}".txt
else
echo Failed to compile h... |
1c4d728931ac9e9fb255d8c8046f0ba0e75ac5b61014ac54f879c56f1e8ee18e | Shell | 372 | 8 | curl -X POST \
"http://localhost:8000/predict" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d '[{"imdb_reviews_windowed": "This movie was great! I loved it!",
"imdb_reviews_longformer": "This movie was great! I loved it!",
"imdb_reviews_tiny_be... |
9bcab15ae4bf9c7449b8d20af119ca130aa425cbc6b9eb3e9063d6513898e17d | Shell | 372 | 21 | #!/bin/bash
# Simple SLURM sbatch example
#SBATCH --job-name=pthwy_scoring
#SBATCH --ntasks=1
#SBATCH --time=3-00
#SBATCH --mem-per-cpu=48G
#SBATCH --partition=ncpu
set -e -o pipefail
cd /nemo/lab/gandhis/home/users/grantpm/
ml purge
. load_panpipes.sh
cd MRIxST/code/01-4layers_withendo
echo "Start running python"... |
efd10e7288654236822e8e1461732b37e11afba76d88e9c8a431b37471c5a9e1 | Shell | 373 | 17 | #!/bin/bash
#SBATCH --time=3-04:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=gnn_sim_qt
#SBATCH --output=logs/gnn_sim_qt-%j.log
#SBATCH --mem=16GB
#SBATCH --partition=regular
name=${1}
param_set=${2}
nrep=${3}
ml R
Rscript ../Script/qualitative_data.R ${name} \
${pa... |
e4d767c05affb3d7824192524b1f51b6caaaadba37e82776e05b7a38fae6b14d | Shell | 374 | 3 | #! /bin/bash
$MARINE/marine.py --bam_filepath $MARINE/examples/data/single_cell_CT.md.subset.bam --output_folder $MARINE/examples/sc_subset_CT --barcode_whitelist_file $MARINE/examples/data/sc_barcodes.tsv.gz --barcode_tag "CB" --strandedness 2 --contigs "1,2,3,4,5,6" --min_base_quality 15 --all_cells_coverage --tabul... |
b4760257c1fd3aaf26312a3a6e5e73cd0e5819eada1884f023e8468225071467 | Shell | 375 | 14 |
input_folder=$1
sample=$2
output_folder=$3
mismatch=$4
python="/net/shendure/vol12/projects/sciRNAseq_script/anaconda2/bin/python2.7"
python_script="/net/shendure/vol1/home/martin91/scripts/sciRNAseq3/rm_dup_barcode_UMI.py"
echo Filtering sample: $sample
$python $python_script $input_folder/$sample.sam $output_fold... |
7847ba0061b92a078bee18e288d3f07d6e8409b423eea4d5bae0583a2dd6c4fb | Shell | 379 | 18 | #!/bin/bash
set -e
SPATULA_BIN="/app/bin/spatula"
if [[ ! -f "$SPATULA_BIN" ]]; then
echo "Error: spatula binary was not found at $SPATULA_BIN"
exit 1
fi
# If no arguments are passed, show help
if [[ $# -eq 0 ]]; then
echo " No arguments passed. Showing spatula help:"
exec "$SPATULA_BIN" --help
else
# Forw... |
504a8a3f741b458cb5062522375533c7634f12ef620c07c5a7629c4f43699ace | Shell | 382 | 14 | #!/bin/bash
#SBATCH --mem=128G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --time=10:0:0
#SBATCH --array=97-114
cd $project/moralization_temporal
module purge
module load python/3.10 scipy-stack
source ~/venv2/bin/activate
echo "SLURM_ARRAY_TASK_ID: " $SLURM_ARRAY_TASK_ID
python SWOW_prediction/congressi... |
8c79b0448e4ac348269e3554e125aeb2849d9e0c31d6abe48ff1ba0f0cc46f17 | Shell | 383 | 9 | #build a singularity image for qsiprep
#docker site: https://hub.docker.com/r/pennbbl/qsiprep/tags
#tag: https://hub.docker.com/layers/pennbbl/qsiprep/0.22.0/images/sha256-597df19a6268b975bf8b94dda96bd9f7ba79d9981a9cf7ecfc5bf6ab74471941
cd /cbica/projects/luo_wm_dev/two_axes/software/
mkdir -p qsiprep
singularity bui... |
8b91d8c63dfbbc51b3729840740d69396a6b2a096fc30418cdd70dcf33bb2f4d | Shell | 384 | 8 | #!/bin/bash
# need to make a version.py file for BABS
# BABS expects a version.py file, but the patched version we used for pyAFQ doesn't have that file.
version_content='version = "1.3.2-dev"'
output_file="/cbica/projects/luo_wm_dev/two_axes/software/pyAFQ/AFQ/version.py"
echo "$version_content" > "$output_file"
ech... |
c1d699a74527eb4e44323c62aab2ea81947f0db5db941ced835f0385d153a147 | Shell | 386 | 14 | #!/bin/env bash
PROT=AA # protein name
NCV=1 # number of collective variables
function calc_pca_covar () {
xtc=../../dihed_traj/all.trr
gro=../../dpca.gro
#[[ ! -e $outdir ]] && mkdir -p $outdir
gmx_mpi covar -n ../../dpca.ndx -f $xtc -s $gro -ascii -xpm -xp... |
499bcb3889094e772d88fe39b365304090d8db32c7b321d9101b4a1bdbe9bd93 | Shell | 387 | 14 |
input_folder=$1
sample=$2
output_folder=$3
mismatch=$4
python="/net/shendure/vol12/projects/sciRNAseq_script/anaconda2/bin/python2.7"
python_script="/net/shendure/vol1/home/martin91/scripts/sciRNAseq3/rm_dup_barcode_UMI_no_mismatch.py"
echo Filtering sample: $sample
$python $python_script $input_folder/$sample.sam ... |
823248ebca07cbe1311002a1ac963168f78dd3070f3963cd01ef6b227f845daf | Shell | 388 | 9 | #!/bin/bash
#converts 4mm data in MNI to 2mm. specify the paths
#eg mni4to2.sh /path/to/input /path/to/output
# you may need to replace oldtarg & newtarg with the paths to your FSL standard data
in=$1
out=$2
targ=/usr/local/fsl/5.0.10/data/standard/MNI152_T1_2mm.nii.gz # this is the space we want to move the neuroque... |
8876771cb2e95bb640b7fd23356e778b7742f52d56381a274eb3a8c0050928cc | Shell | 390 | 9 | #!/bin/bash
REP="${SLURM_ARRAY_TASK_ID}"
apptainer run /path/to/mix3r.sif make_template --bim /path/to/PLINK/chr_1000G/1000G_chr${REP} \
--ld /path/to/1000G_linkage_disequillibrium/1000G_chr${REP} \
--frq /path/to/Allele_Frequencies/1000G_chr${REP} \
... |
4ebdf4f8cc3b694d4b04af3e66c506e6485baf61f579b733c75a1d32885a062c | Shell | 393 | 19 | #!/bin/bash
set -eux
scriptdir=$(dirname "$0")
function compile_function()
{
local funcName="$1"
shift 1
local outdir="$scriptdir"/Compiled_"$funcName"
mkdir -p "$outdir"
"$MATLAB_HOME"/bin/mcc -m -v "$funcName".m "$@" -d "$outdir"
}
#addpath() adds to the front, while -I adds to the back, so rev... |
9fc84c1cb5252d6edd4330d28f8169b0c92fc5ee9630eb0d32ff9b4c0068bf28 | Shell | 393 | 19 | #!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --array=0-9
#SBATCH --time=24:00:00
#SBATCH --mem-per-cpu=4GB
#SBATCH --job-name=visualsearch
#SBATCH --mail-type=ALL
#SBATCH --mail-user=svo213@nyu.edu
#SBATCH --output=visualsearch_%j.out
i=${SLURM_ARRAY_TASK_ID}
cd /Desktop/VisualSe... |
512563065180ed5f2de79113c013e391d530c2e2357a3df17217919f2f1f8b8f | Shell | 394 | 13 | COMMIT=${1}
COMMIT="$(echo "${COMMIT}" | tr -d '[:space:]')"
export COMMIT
NVIDIAVERSION=${3}
export NVIDIAVERSION
NO_TAG="ghcr.io/${2}/pyafq_gpu_cuda_${4}"
TAG="${NO_TAG}:${COMMIT}"
TAG2="${NO_TAG}:latest"
TAG="$(echo "${TAG}" | tr -d '[:space:]')"
TAG2="$(echo "${TAG2}" | tr -d '[:space:]')"
echo $TAG
docker build -... |
9a98067e803e48cfd1eccc01139378eb7c7babfa9b591563820de521e5193766 | Shell | 394 | 9 | #build a singularity image for fmriprep
#docker site: https://hub.docker.com/r/nipreps/fmriprep/tags
#tag: https://hub.docker.com/layers/nipreps/fmriprep/20.2.3/images/sha256-102db5fe8b0a34298f2eb2fd5962ad99ff0a948d258cbf08736fcc1b845cad9f
cd /cbica/projects/luo_wm_dev/two_axes/software/
mkdir -p freesurfer
singulari... |
17a601c2ea8e2496b176600f1b8e83210b6b21245fbc6f7a362b477ab648806f | Shell | 398 | 20 | #!/bin/bash
#SBATCH --time=16:00:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --job-name=gnn_eve_data
#SBATCH --output=logs/gnn_eve_data-%j.log
#SBATCH --mem=500MB
#SBATCH --partition=regular
# Assign command line arguments to variables
name=$1
beta_n=$2
batch=$3
index=$4
ml R
# Call the R script with the necess... |
793bf9c12c99cc1109e8cc1c2552b584458914641cb425e48a1b29bb6a2e1e7b | Shell | 398 | 21 | #!/bin/bash
#example script to run testing on trained dataset
set -e
# Input paths
TEST_DATA="data/test"
PRECOMPUTED_TRAIN="data/test_dataset.npz"
# Parameters
NUM_THREADS=8
OUTPUT="ncd_kingdom_output.csv"
# Run NCD test pipeline
python NCD.py \
--train_data "$PRECOMPUTED_TRAIN" \
--test_data "$TEST_DATA" \
-... |
509ad72e275ef3fd070a1901c884fa316758434089f6016c9ec881171b36327f | Shell | 400 | 16 | #! /bin/sh
cd tests
. ./compat.sh
sort -k2,2 > ${pref}.md5sum <<EOF
dcbb23c4a74a923c37a3b059f6a6d89a ${pref}_0
EOF
echo "Counting 10-mers on 1 CPU" && \
$JF count --matrix seq10m_matrix_10 -m 10 -t 1 \
-o $pref -s 10000000 --timing ${pref}.timing seq10m.fa && \
check ${pref}.md5sum
RET=$?
cat ${pref}.timi... |
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