sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5617af402be4e5fec812874be3c287a217bae71df565df8c1846088c2bf43fc9 | Shell | 605 | 10 | #!/bin/sh
### An example script used to make prediction
parent_path=$( cd "$(dirname "${BASH_SOURCE[0]}")" ; pwd -P )
cd "$parent_path"
GPU=0
echo "=====Use the model trained on qm8 (random split seed=122) to make prediction====="
CUDA_VISIBLE_DEVICES=${GPU} python ../src/predict.py --dataset=qm8 --ori_dataset_path=... |
29549d954d20766970b6b3bdc80991d0285c5d4310f454939f9254bae731d053 | Shell | 608 | 15 | #!/bin/bash
#SBATCH -p short
#SBATCH -c 1
#SBATCH -t 0-11:59
#SBATCH --mem=50G
#SBATCH -o /n/groups/marks/users/david/ex62/out/runs/%j.out # File to which STDOUT will be written, including job ID
#SBATCH -e /n/groups/marks/users/david/ex62/out/runs/%j.err
source activate /home/dd128/mambaforge/envs/dd... |
c2c7fe321bc81f699e557ea9c18ff598f3e97980e70bff3f12ae59fbcf10c81f | Shell | 608 | 15 | #!/bin/bash
#SBATCH -c 1
#SBATCH -t 5:00:00
#SBATCH -p medium
#SBATCH --mem=50G
#SBATCH -o /n/groups/marks/users/david/ex62/out/runs/%j.out # File to which STDOUT will be written, including job ID
#SBATCH -e /n/groups/marks/users/david/ex62/out/runs/%j.err
source activate /home/dd128/mambaforge/envs/d... |
675fc4a35b971d749b08c0ab1b83a6a4c68b0b9821b573aca868078f02ac6521 | Shell | 619 | 21 | #!/bin/sh
#
#SBATCH --cpus-per-task=8 # Number of CPU cores per task
#SBATCH --output=logs/ML_out.txt # Standard output log
#SBATCH --error=logs/ML_err.txt # Standard error log
#SBATCH --mem=128G # Memory request per node
DATASET_INFO="./dataset_info.json"
# ---- Cluster configuration (set the... |
0500ef712842f3816ecfa0a490a1907d2c151db0967c36163c4f6a0cf7f479b3 | Shell | 624 | 15 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
basedir="$(dirname "$scriptdir")"
task=mid
for sub in `cat ${scriptdir}/newsubs.txt`; do
if [ "${task}" == "socialdoors" ]; then
cp -r /ZPOOL/data/proj... |
63c4de0aa202bbec39084ecbcdd91863dab6f140de2eb272fbf4f869a4c728e4 | Shell | 627 | 12 | #!/bin/bash
#PBS -l select=1:ncpus=16:mem=150G,walltime=200:00:00
## PCA processing - STAGE 3
for chr in $(seq 1 22);
do
/home/wrr239/c3202333/plink2 --bfile /home/wrr239/TwinsUK/DTR_Genotypes_1000G_V3P5_Collab_PublicID/PCA_calculations_in_either_TwinSubset/Chr${chr}_Stage_1_PCA\
--extract /home/wrr239/Twi... |
647f7f19871abfb1833bf8a868056ef98e55a586421362cafb1cf047dfff4e68 | Shell | 632 | 23 | #!/bin/bash
#SBATCH --time=12:00:00
#SBATCH --account=def-akhadra
#SBATCH --mem=4G
#SBATCH --mail-user=niklas.brake@mail.mcgill.ca
#SBATCH --mail-type=FAIL,END
#SBATCH --output=simulation.log
module load python/3.8.10
module load mpi4py
module load scipy-stack
module load matlab/2020a
module load neuron
virtualenv --... |
18e6f9127c2be222548ed114d4826c4c84b76c0563ab82bd95737503eff3df2c | Shell | 633 | 24 | #!/usr/bin/env bash
set -e
# Install dependencies
cd clients/new-js
pnpm build
# Generate the JS client
echo "Generating JS client..."
pnpm genapi:chromadb
# run git diff and check if packages/chromadb/src/api/ has changed
echo "Checking for changes in generated client..."
if ! git diff --quiet --exit-code packages/... |
c527cef3caad93db62b6ce260b0d7ab3c9084c56ccffc4d464c263ba719f814b | Shell | 633 | 22 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q hpc
#BSUB -n 1
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=128GB]"
#BSUB -J convertH5
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and error file. %J is the job-id --
#BSUB -o "/w... |
112afb8aa68e9154b2371e84be56fd92d110ea0b53be3089fddade0994b9ff02 | Shell | 635 | 5 | ./runPipeline.sh -N 8 -b splintr3F2 -B 1 #-s "color-correction" #R /home/dgoodwin/ExSeqRepo/registration/
#./runPipeline.sh -N 8 -b splintr3F2 -c "'ch00','ch01','ch02','ch03'" -B 1 #-s "color-correction" #R /home/dgoodwin/ExSeqRepo/registration/
#./runPipeline.sh -N 20 -b exseqautoframe7 -c "'ch00','ch01SHIFT','ch0... |
5b68e2f3ae7712146e150dcf6f83ecc82fb38151d1632e59d2d610a8d512022e | Shell | 639 | 17 | #!/usr/bin/env bash
pip install -U pip Cython
pip install -r requirements.txt
mv ./dataset/coco/download_coco.py . && rm -rf ./dataset/coco/* && mv ./download_coco.py ./dataset/coco/
# prepare lite train data
wget -nc -P ./dataset/coco/ https://paddledet.bj.bcebos.com/data/coco_benchmark.tar
cd ./dataset/coco/ && tar... |
584e9b97d0e70d64eee0f7fbc34aa365d8d357efc728f7fea699f2b051196baf | Shell | 641 | 26 | ID1=$(sbatch --array=24,50,10,14,8,7,43,28,26,54 --parsable synthetic_spikes.sh)
ID1=$(sbatch --array=7,54 --parsable synthetic_spikes.sh)
sbatch --depend=afterok:$ID1 --array=7,10,14,28,54 shuffle_synapses.sh
sbatch --array=7 synthetic_spikes.sh
sbatch --array=10 synthetic_spikes.sh
sbatch --array=14 synthetic_s... |
ee0186768cb9e48c28adcd6dc328d6a14f290d4c624bffc29e5d1e2b24a8437a | Shell | 643 | 15 | #!/usr/bin/env bash
# Local convenience wrapper: format, then run the same core checks CI runs.
# CI test jobs go through the .github/actions/run-tests composite action;
# the commands below mirror its defaults for the PR-gating suites.
set -euo pipefail
cd "$(dirname "$0")/.."
# Format in place (CI checks formatting ... |
3a05a86bca3360a0f7e5a09a0b3a5c47434d9c986602e9ade4948d2571403353 | Shell | 650 | 20 | #!/bin/bash
#untar Python installation.
tar -xzf python38.tar.gz
#untar a set of packages
tar -xzf packages.tar.gz
# make sure the script will use your Python installation,
# and the working directory as its home location
export PATH=$PWD/python/bin:$PATH
export PYTHONPATH=$PWD/packages
export HOME=$PWD
#copy the com... |
35a5a51c1aeef3d622ede6d0f315c99048c3ec18f575df55d99d11e05be5780d | Shell | 651 | 20 | #!/bin/bash
#untar Python installation.
tar -xzf python38.tar.gz
#untar a set of packages
tar -xzf packages.tar.gz
# make sure the script will use your Python installation,
# and the working directory as its home location
export PATH=$PWD/python/bin:$PATH
export PYTHONPATH=$PWD/packages
export HOME=$PWD
#copy the com... |
6f71a867cb77737ddc3cca5ed5858f843a206918056fe5709426add81fc567b0 | Shell | 656 | 22 | #!/bin/bash
#SBATCH --time=002:00:00
#SBATCH --account=def-akhadra
#SBATCH --mem=4G
#SBATCH --mail-user=niklas.brake@mail.mcgill.ca
#SBATCH --mail-type=FAIL
#SBATCH --cpus-per-task=8
#SBATCH --output=correlation.log
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
folder=$1
subfolders=($(ls -d $folder/*))
for i in {0..9};... |
5c4e0f6a97998cd6d35403e9c06ce2245105fa3ebf423acb515dc04db61675d1 | Shell | 657 | 36 | # Model
model=ecg_resnet34_psvt
# Hyperparameters
bs=32
lr=1e-4
wd=1e-4
epochs=15
# Dataset
num_folds=10
cv_folds_path='./cv_folds'
num_leads=12
# Other settings
result_path='./cv_results'
gpu_num=0
for i in `seq 0 $(($num_folds-1))`
do
python main.py \
--model $model \
--batch_size $bs \
... |
cfea8785f29de84659a0b669d2c6a8e227d372b4f4e9c2dd954a5774558d1a89 | Shell | 661 | 22 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q hpc
#BSUB -n 1
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=128GB]"
#BSUB -J convertH5
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and error file. %J is the job-id --
#BSUB -o "/w... |
04dd5726ea729873a30f0692278b1d9c39436bff9ba04ea1d77c5880c13d6ce8 | Shell | 666 | 31 | #!/bin/bash
#
#$ -N fmriprep_job
#$ -o logs/fmriprep_out.log
#$ -e logs/fmriprep_err.log
#$ -l h_vmem=16g
#$ -pe smp 8
#$ -t 1-NSUBJECTS
#$ -q YOUR_QUEUE
# ---- Cluster configuration (set these for your system) ----
NIPOPPY_VENV_PATH="/path/to/your/nipoppy_venv/bin/activate"
# -----------------------------------------... |
f3e9776a38e827be6e0cd203964aecf58d621b9c489010eaf5b226f8af91dc4f | Shell | 672 | 13 | #!/bin/bash
#PBS -l select=1:ncpus=16:mem=150G,walltime=200:00:00
## PCA in each subcohort - removing one random pair of KING coefficient > 0.0442 (third degree relatives)
for i in $(seq 1 2);
do
/home/wrr239/c3202333/plink2 \
--bfile /home/wrr239/TwinsUK/DTR_Genotypes_1000G_V3P5_Collab_PublicID/PCA_calcul... |
d68fdd0186f313fa550dd32cf866c7e5e2413ec7ab1f64743412be90b9280f16 | Shell | 683 | 20 |
# example use of scripts
# data directory
# must have embeddings and data all set up
# e.g. binary_embeddings.txt
DIR='WS'
# run metalda, second arg is number of topics
# must have 'raw_embeddings.txt' available in top directory ..
# usually its a link to a big 6Gb embeddings file somewhere else
# first tas... |
114a63bbc97b344075343864af24292174da27717ee84a2f7838d43c9ebf517e | Shell | 684 | 16 | #!/usr/bin/bash
#USAGE: time bash run_bcl2fastq_sample_0038.sh &> bcl2fastq_0038_log_out.txt
#docs: https://support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/bcl2fastq/bcl2fastq2-v2-20-software-guide-15051736-03.pdf
module load bcl2fastq/2.20.0
BCL_DIR=../data/00_sequenc... |
230f9ac8a19f86b84e0d020cad14601a1cdc9ab501b75937b7419e721a9d93d9 | Shell | 689 | 13 | #!/bin/bash
#PBS -l select=1:ncpus=16:mem=150G,walltime=200:00:00
## PCA processing - STAGE 1
for chr in $(seq 1 22);
do
/home/wrr239/c3202333/plink2 --bfile /home/wrr239/TwinsUK/DTR_Genotypes_1000G_V3P5_Collab_PublicID/0.8_rsq_PGS_calc/Chr${chr}_0.8_r2_HWE_MAF \
--maf 0.05 --extract /home/wrr239/TwinsUK/D... |
adcd39a48a93becd8f511af0851e3ae9dee0f633115883737cc0dbbc99df38fa | Shell | 691 | 38 | #!/usr/bin/env bash
pushd () {
command pushd "$@" > /dev/null
}
popd () {
command popd "$@" > /dev/null
}
if [ "$1" = "clean" ]; then
pushd src/SimulationCode
make clean
popd
exit 0
fi
pushd ./src/SimulationCode
make CRADS="15*pow\(10,-6\)" &&
./mtsim &&
cp vectordata/centering_vector_strain8_rad25_... |
1d191b8c76ff91311c581e0d61a04aa71e39b1a430a74032502cd3aae13a47bd | Shell | 694 | 16 | data_path=bdd100k
img_dir=${data_path}/images/track
label_dir=${data_path}/labels/box_track_20
save_path=${data_path}/bdd100kmot_vehicle
phasetrain=train
phaseval=val
classes=2,3,4,9,10
# gen mot dataset
python bdd100k2mot.py --data_path=${data_path} --phase=${phasetrain} --classes=${classes} --img_dir=${img_dir} --... |
7a7efc2b86974869763d523d5cb46077cb4d3eb15e96bcfff83dd95082c15392 | Shell | 699 | 16 | #!/usr/bin/bash
#USAGE: time bash run_bcl2fastq_sample_0037.sh &> bcl2fastq_0037_log_out.txt
#docs: https://support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/bcl2fastq/bcl2fastq2-v2-20-software-guide-15051736-03.pdf
module load bcl2fastq/2.20.0
BCL_DIR=../data/00_sequenc... |
bfccdd0c3abe1ebfa78e9e944600e3b2e5244eb4b596f3b3ed39d8a4ca90289c | Shell | 699 | 17 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
maindir="$(dirname "$scriptdir")"
for sub in 1001 1002 1003 1004 3218 3220 1006 1007 1009 1010 1011 1012 1013 1015 1016 1018 1019 1021 1240 1242 1243 1244 1... |
8c28529393988ae0925afc1eb4f0d62d6941689610960490aacbf66a1f3a192a | Shell | 700 | 16 | #!/usr/bin/bash
#USAGE: time bash run_bcl2fastq_sample_0038.sh &> bcl2fastq_0038_log_out.txt
#docs: https://support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/bcl2fastq/bcl2fastq2-v2-20-software-guide-15051736-03.pdf
module load bcl2fastq/2.20.0
BCL_DIR=../data/00_sequenc... |
bef3ddb47641036dde07eae8e1dab40f9c84ccd7884d57eec0e3a7ee6a0898af | Shell | 702 | 23 | #!/bin/bash
manifold="all"
n_samples=10
operation="all"
while getopts m:n:o: flag
do
case "${flag}" in
m) manifold=${OPTARG};;
n) n_samples=${OPTARG};;
o) operation=${OPTARG};;
esac
done
echo "Manifold: $manifold";
echo "N Samples: $n_samples";
echo "Operation: $operation";
python gen... |
298b3cc0fe43dbe42d416ea5e041eba18136ce022f9083cf486ff6b0bfc8a9f7 | Shell | 719 | 23 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q hpc
#BSUB -n 1
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=128GB]"
#BSUB -J convertH5
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and error file. %J is the job-id --
#BSUB -o "/w... |
0c5181ca89014e1d7f75972b19a723701adb7c053af1ba921250b2d60485bf9d | Shell | 725 | 19 | #!/bin/bash
#Set the pairs of modality we want to run with the R script.
declare -a StringArray=("--modality rest" "--modality task" "--modality movie")
echo "--------------------------"
echo "R Script - var with age"
echo "--------------------------"
#We run the R script for each pair of modality using a for loop
f... |
940f469419ecd870c31617a7e719784e0acaccce494a61c8f9238cc1aea5b635 | Shell | 729 | 21 | # All rights `PaddleDetection` reserved
# References:
# @inproceedings{yang2016wider,
# Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
# Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
# Title = {WIDER FACE: A Face Detection Benchmark},
# Year = {20... |
dbf561c786afda3fad2b0663a0f37eff236fcda028da61b597911f0b5cb50bbc | Shell | 730 | 19 | #!/bin/bash
#Set the pairs of modality we want to run with the R script.
declare -a StringArray=("--modality rest" "--modality task" "--modality movie")
echo "--------------------------"
echo "R Script - hctsa with age"
echo "--------------------------"
#We run the R script for each pair of modality using a for loop... |
f715aa942bde889d44a7ee6fd550ce8f14378bad411bb469e3ca80cdb3e558c7 | Shell | 744 | 15 | #!/bin/bash
#SBATCH --partition=scavenge
#SBATCH --requeue
#SBATCH --ntasks=1 --nodes=1
#SBATCH --cpus-per-task=20
#SBATCH --mem-per-cpu=6000
#SBATCH --time=12:00:00
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
module load MATLAB/2018b
matlab -nodisplay -nosplash -nodesktop -r "root_path='/gpfs/ysm/project/ahf38/An... |
a3e2dbf6690e761e6910c55e308c03e1ece7508f3a7476190b119aefc698dab7 | Shell | 763 | 22 | #!/bin/bash
#SBATCH --time 48:00:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=16G
#We convert to a bed file as this is recommended by various people.
#Similar arguments to encode are used.
for file in *filt.filt.bam
do
bedtools bamtobed -i $file > ${file::-4}.bed
macs2 callpeak -t ${file::-... |
2b0c6f34fa620667e25b8c4186027bb3c8923f239cfa50fff7f593b4bfe874c9 | Shell | 770 | 24 | #!/bin/sh
#
#SBATCH --job-name=report_job # Optional: Name of your job
#SBATCH --output=logs/report_out.txt # Standard output log
#SBATCH --error=logs/report_err.txt # Standard error log
#SBATCH --time=24:00:00 # Walltime for each task (24 hours)
#SBATCH --mem=64G # Memory reques... |
5162b7d5d28e1e3c9153c803e909e5c5743e4a74d4081d15af8363b817a70dd3 | Shell | 773 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=16GB]"
#BSUB -J inferance_speed
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the outp... |
dded2e3be13fc420787a3abaa11e10d0f2bc2e1e3b675ed98f5d15e9f1976d7e | Shell | 776 | 28 | #! /bin/sh
#SBATCH --get-user-env
#SBATCH --job-name=calc_context_PDR-%j
#SBATCH --chdir=${WORKDIR}
#SBATCH --error=${LOG_DIR}/calc_context_PDR-%j.err
#SBATCH --output=${LOG_DIR}/calc_context_PDR-%j.out
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
#SBATCH --gres-flags=enforce-binding
#SBATCH -... |
a0945a53283da1f0b28aab6f9419d9342e7a3a80d167ec75ab5bd64c7ddae840 | Shell | 782 | 23 | #!/bin/bash
# FigureS11.sh
# Plots for Supplementary Figure S12.
# Just executes ./extract_ROI_HOA_GLM1_TAfT.sh.
# Similar script as for Supplementary Figure S11.
#
# EEG/fMRI STUDY, DONDERS INSTITUTE, NIJMEGEN.
# J. Algermissen, 2018-2023.
# we are here:
# cd /project/3017042.02/Analyses/FiguresOutcomeLocked
# Inv... |
f19fe1af443160ac296aa020e4dfecf3b69fa35b73098a23bc628bf96d3a3070 | Shell | 792 | 23 | #!/usr/bin/env sh
set -e
# Run the transformation script instead of copying the file
echo "Fetching and transforming OpenAPI specification..."
python3 transform-openapi.py
# Run the OpenAPI generator
echo "Running OpenAPI generator..."
openapi-generator-plus -c config.yml
if [[ "$OSTYPE" == "darwin"* ]]; then
sed ... |
ab7b0b000503a3b55a20fe7120d2d4c4853c08d109237c9c1df8052d4742ea6d | Shell | 793 | 20 | #!/bin/bash
#SBATCH --job-name=snakemake
#SBATCH --error=job_errors/snakemake.%j.err
#SBATCH --output=job_errors/snakemake.%j.out
#SBATCH --time=7-00:00:00
##SBATCH --qos=long
#SBATCH -p hbfraser
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=banwang3@stanford.edu
echo "---start running ----"
ml contribs
ml poldrack... |
3235fbc70326678297c57deeb9195495b11bec1674a81ef1d3478dbcabd9c4e8 | Shell | 798 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J deeponet1D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output an... |
c03c02d22325464152adc47bfa3833b215690b8ebf6777cb170a83ff9de3bc1a | Shell | 798 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J deeponet2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output an... |
6b6b581c01533cfe31b4ea41cc29516a4115f90d7be6fc82f7bfb46b29812e53 | Shell | 799 | 18 | #!/bin/bash
# This script runs bismark methylation extractor for an input BAM file
# Format for calling script:
# bash ./bismark_meth_extract.sh ${SLURM_ARRAY_TASK_ID}
# Define the fastq BAM file listed in the .txt file as well as the sample-specific barcode.
BAM_FILE="$1"
# Set up output filenames and locations.
... |
fd05a45f99aa01ec70b03388c7c6d408e815f1f8d7d2f154d97b87b7020872eb | Shell | 813 | 23 | #!/usr/bin/env bash
PACKAGING_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
REPO_ROOT="$(cd "${PACKAGING_DIR}/../.." && pwd)"
MAPMANAGER_REPO="${REPO_ROOT}/../cs_project/mapmanager-web-components"
NICEPOOL_PROJECT="${MAPMANAGER_REPO}/integrations/nicepool-pyqt5"
NICEPOOL_STATIC="${NICEPOOL_PROJECT}/src/nicepool_... |
b88defe35508da3609c819ad65344e6100f7ef0035584d37adddee2da744a6bb | Shell | 815 | 33 | #!/bin/sh
#
#$ -N assess_dfc_job
#$ -o logs/dfc_out.txt
#$ -e logs/dfc_err.txt
#$ -l h_rt=24:00:00
#$ -l h_vmem=32g
#$ -t 1-NSUBJECTS
#$ -q YOUR_QUEUE
# ---- Cluster configuration (set these for your system) ----
VENV_PATH="/path/to/your/venv/bin/activate"
PYDFC_CODE_DIR="/path/to/pydfc"
# ----------------------------... |
c99d126f5a7824f7be1641e1a332bba0aab352dc707a02e619f210631dbc611d | Shell | 816 | 27 | Rscript /projects/petar/Code/wgcna-toolbox/rwgcna_main_seurat3.0.R \ #get this from https://github.com/perslab/wgcna-toolbox
--pathDatExpr /projects/petar/dmb/05_wgcna/vsd_counts.csv \
--pathMetadata /projects/petar/dmb/05_wgcna/vsd_meta.csv \
--dirProject /projects/petar/dmb/05_wgcna/wgcna_output/ \
--prefixData dmb ... |
72a3aac752363d8f53193936acda7339e0992e7b87b07c63f4642d3245a01f90 | Shell | 819 | 24 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q hpc
#BSUB -n 1
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=128GB]"
#BSUB -J convertH5
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and error file. %J is the job-id --
#BSUB -o "/w... |
0bd0a94bed786c74463f5d7dc3b45124fec2de7ac319a4942fa0dece4c00665b | Shell | 825 | 33 | #!/usr/bin/env bash
# -*- encoding: utf-8 -*-
### Arguments list
### ----------------------------
# $CNT : simulation counter
# $RESDIR : results directory
# $FCONF : current configuration file
### ----------------------------
### Print current simulation start time [24H format]
CURRTIME=$(date +"%T")... |
f2b98ba60e19ae705beed6e17fda55fcc75f19e632f3146a06389c56104952d3 | Shell | 832 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J rect2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
9ade39aa2fe68c824501e80232d7fb06dcd11751e3365eb25bdc15dcbc08cfb8 | Shell | 834 | 29 | #!/bin/bash
#BSUB -W 24:00
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process:gmem=30GB"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -R "select[localssd0]"
#BSUB -J deeponet3D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends -... |
4712a514618f07092efb6140c0f1b90e62820bfc416789c8299def67a40ed459 | Shell | 835 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J rect2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
ec8dc728c1feb85fc47c7813bdc7a6d683758ada36e0ed866c7e59eb75226d60 | Shell | 842 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J Lshape2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and ... |
d922ebe6f2aabd8549fc299553267a911beb0a56b73ab76b0987289197c1237a | Shell | 843 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J furn2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
a7d304cd667233e074421a389927dd3dbbb8a5318f9d2620c7159d47c60187c2 | Shell | 844 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J rect2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
bd639b41d2f9a22668c5827cc2cd5689ab8e4be37e4142d194cdfa1cfdc50ad7 | Shell | 849 | 30 | #!/bin/bash
export PATH=%PATH:/mnt/c/Users/Richard/Anaconda3/envs/deepmsi
out_dir="./processed_data"
path_files="./file_dir_coronal_3D_slide3_5.json"
decoder_dir="./saved_model/coronal3D_latent32_epoch10_decoder"
regressor_dir="./saved_model/coronal3D_latent32_epoch10_regressor"
recon_ROI=(
"R00"
"R01"
"R0... |
eaa3a81c8acc6fc1df5ec05bde5155102398697051debf3c6dd78f4093d44717 | Shell | 849 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J Lshape2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and ... |
70094fb4ad600f6f7cd776d9c2c528a9733bed63fbe0c76d32f84e32c5f003ec | Shell | 851 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J furn2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
48037f7d5f40cd61b1b5e78d56a9beb9d2591c01a9430b7ab9fb29c384780434 | Shell | 857 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J furn2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and er... |
f0df753ff5ebc82d54b1abd5bbbe8cc231503719e0c219d9171c6e130d32b2a0 | Shell | 861 | 28 | #!/bin/bash
#BSUB -W 02:00
#BSUB -q gpuv100
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -n 4
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=64GB]"
#BSUB -J Lshape2D
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output and ... |
61341b0c88e5440b93e5333a2bd98b541ae0333a9094d47d741314f1ab9834a4 | Shell | 862 | 43 | #!/bin/bash -ex
IMGNAME="fmriprep-20.1.1.simg"
BASEDIR=/idata/DBIC/castello/budapest-data-paper
IMG=$BASEDIR/singularity/$IMGNAME
OUTDIR=$BASEDIR/outputs
WORKDIR=$OUTDIR/workdir
TMPDIR=$WORKDIR/tmp
DATADIR="$BASEDIR"
FS_LICENSE=$BASEDIR/singularity/license.txt
NCORES=16
if [ ! -d "$WORKDIR" ]; then
echo "Creating... |
2f407896fee1f664fe8dcca9db7a09a92d2c36134af97c9d07ab9d0dfaf36c66 | Shell | 863 | 19 | #!/bin/bash
# Make output & log directories
mkdir output
mkdir logs
# Make a copy of each Read 1 SRA fastq file with "/1" at end of each sequence identifier line
for i in $(ls -1 *_1.fastq | sed 's/\_1.fastq//')
do
awk -v "n=$n" 'NR % 4 == 1 {$0 = $0 "/1"} {print}' $i\_1.fastq > $i.R1.fastq
rm $i\_1.fastq
done
# Make a... |
0f755f1ff6c00aff8f03f64fe9aa261e1dae6f39c0ce7989de5882f645e5290f | Shell | 865 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J cube3D_eval
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output a... |
3e2ba4cfd5502bb3ec39bdf4eb00df03daa0553d9e94ca1899a5aa6215432c1c | Shell | 865 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J dome3D_eval
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output a... |
ace35a12129f5b214831f149dbe65f43921748bea0defc63034b8a5e8f707cb5 | Shell | 873 | 29 | #!/bin/bash
#
#SBATCH --job-name=fmriprep_job # Name of the job
#SBATCH --output=logs/fmriprep_out.log # Standard output log
#SBATCH --error=logs/fmriprep_err.log # Standard error log
#SBATCH --mem-per-cpu=16G # Memory (16 GB) per cpu
#SBATCH --cpus-per-task=8 # Number of CPU cores ... |
b08f693ef59f1e142d3534cb88344d722d6039812b02c5b4d663ccdf049bbd7c | Shell | 875 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J Lshape3D_eval
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output... |
e8645aad9fd3bbde13d315a057b645ca59a95c29f6401a3cad4e854e0b478016 | Shell | 875 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J furn3D_eval
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the output a... |
4148b9fbc48d65203fb0288972fa5d5e4c90a2b5c2c60b31dd5f7b6e64937296 | Shell | 876 | 19 | #!/bin/bash
#Set the pairs of modality we want to run with the R script.
declare -a StringArray=("--modality rest" "--modality task" "--modality movie")
echo "--------------------------"
echo "R Script - Var with ICAs"
echo "--------------------------"
#We run the R script for each pair of modality using a for loop
... |
9d198a07fabffd6ce66431c6a928dbc91c552a73c069d3a9152652528056ca4f | Shell | 879 | 32 | #!/bin/bash
#SBATCH --time=002:00:00
#SBATCH --account=def-akhadra
#SBATCH --mem=40G
#SBATCH --mail-user=niklas.brake@mail.mcgill.ca
#SBATCH --mail-type=FAIL
#SBATCH --cpus-per-task=10
#SBATCH --output=embedding.log
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
module load python/3.8.10
module load mpi4py
module load sc... |
bcf530459773608976a1caf7076a2059cef0ea7fbf1219be0863b37dc9cdfce0 | Shell | 879 | 19 | #!/bin/bash
#Set the pairs of modality we want to run with the R script.
declare -a StringArray=("--modality rest" "--modality task" "--modality movie")
echo "--------------------------"
echo "R Script - Var with ICAs"
echo "--------------------------"
#We run the R script for each pair of modality using a for loop
... |
e8c0e62709d365d33a4cf7d729e524641cd4e435e840a8c5feac4a73d5f649ac | Shell | 886 | 20 | #!/bin/bash
#SBATCH --cpus-per-task=3
#SBATCH --time=36:00:00
#SBATCH --output=job-%j.out
#SBATCH --error=job-%j.err
## PWAS - METSIM+INTERVAL TWAS (Chatterjee - Blood)
for chr in $(seq 1 22);
do
Rscript ~/data/users/william/PWAS_weights/Blood/scripts/PWAS.assoc_test.R \
--sumstats ~/data/users/william/Meta_retin... |
709ad68f00dfc122a012f2030912681e6ecd23499c5a3d76d6c5dbc19323e143 | Shell | 888 | 20 | #!/bin/bash
#SBATCH --cpus-per-task=3
#SBATCH --time=36:00:00
#SBATCH --output=job-%j.out
#SBATCH --error=job-%j.err
## PWAS - METSIM+INTERVAL TWAS (Chatterjee - Blood)
for chr in $(seq 1 22);
do
Rscript ~/data/users/william/PWAS_weights/Blood/scripts/PWAS.assoc_test.R \
--sumstats ~/data/users/william/Meta_retin... |
e8b67032bac43be4707b8ec53cc379b1fd3290c266767f814ec46874aebb1843 | Shell | 896 | 39 | #!/bin/sh
set -eu
method="$1"
script_name="$2"
cp -r /app/* /work
cp -r /snakebids /src
script="'${script_name}' tests/data tests/result participant -c1 --skip-bids-validation"
case "$method" in
"setuptools" )
python -m venv .venv
.venv/bin/python -m pip install --no-color .
PATH=".venv/b... |
6a75b8c66dfbb9aff5702fae05ea2b9f0bb34cb74144cc288de47db09e8daac3 | Shell | 900 | 24 | #!/bin/bash
# FigureS11.sh
# Plots for Supplementary Figure S11.
# Just executes ./extract_ROI_HOA_GLM2_SVC.sh and ./extract_ROI_HOA_GLM1_TAfT.sh.
# Similar script as for Supplementary Figure S12.
#
# EEG/fMRI STUDY, DONDERS INSTITUTE, NIJMEGEN.
# J. Algermissen, 2018-2023.
# we are here:
# cd /project/3017042.02/An... |
ae1e2c66443d0b31d5f5045efaf758a899f0492e42c233c213e53747195d618e | Shell | 901 | 28 | #!/bin/bash
#BSUB -W 00:30
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J cube3D_src_dir
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the outpu... |
c8bbaed10b2db28f38c8610df3d38dc515d1b096d939f9659257eb686f49cf61 | Shell | 901 | 35 | #!/bin/bash
# Number of GPUs and the number of samples per batch per GPU (total batch size = N_GPU x BATCH_SIZE).
N_GPU=1
BATCH_SIZE=30
# Number of parallel workers per GPU for loading data from disk.
N_WORKERS=8
export OMP_NUM_THREADS=1
torchrun \
--standalone \
--nnodes 1 \
--nproc_per_node $N_GPU \
... |
a689b733848ad30999409422637a4609770fc9228b5b85791c197cf1f0ea20ef | Shell | 905 | 28 | #!/bin/bash
#BSUB -W 00:10
#BSUB -q gpuv100
#BSUB -n 4
#BSUB -gpu "num=1:mode=exclusive_process"
#BSUB -R "span[hosts=1]"
#BSUB -R "rusage[mem=32GB]"
#BSUB -J dome_quarter3D_eval
### -- Notify me by email when execution begins --
#BSUB -B
### -- Notify me by email when execution ends --
#BSUB -N
### -- Specify the ... |
974200ed7257df5dc45aedb646d586c4a4fcc9e4f1569d1bbabdb6db13ec1fcb | Shell | 908 | 35 | #!/bin/sh
#
#$ -N fit_fcs_job
#$ -o logs/fcs_out.txt
#$ -e logs/fcs_err.txt
#$ -l h_rt=168:00:00
#$ -pe smp 8
#$ -l h_vmem=8g
#$ -q YOUR_QUEUE
# ---- Cluster configuration (set these for your system) ----
VENV_PATH="/path/to/your/venv/bin/activate"
PYDFC_CODE_DIR="/path/to/pydfc"
# For conda environments, replace the ... |
ca3585c94262ac06118db4c435f57ebfa37b37b741213f06607cde67a5eafb18 | Shell | 922 | 32 | #!/usr/bin/env bash
rm lattice_filter.so
mkdir build_dir
cd build_dir
CUDA_COMPILER='path_to_cuda_nvcc'
CXX_COMPILER='path_to_gcc'
CUDA_INCLUDE='path_to_cuda_include'
SPATIAL_DIMS=3
INPUT_CHANNELS=2
REFERENCE_CHANNELS=9
MAKE_TESTS=False
cmake -DCMAKE_BUILD_TYPE=Debug -D CMAKE_CUDA_COMPILER=${CUDA_COMPILER} \
... |
4bba7400d8fb06ddc8160527e3f51441e5ca0671e20a295b05254c1c460e2fe0 | Shell | 938 | 23 | # Run simulations for m=0.98
cd /lustre04/scratch/nbrake/code/critical_dipole_correlation
folder='/lustre04/scratch/nbrake/data/simulations/embed_branching_network/m=0.98'
# Initialize network models in matlab and simulate crit dynamics
ID1=$(sbatch --parsable --array=1-10 initialize_network.sh $folder 0.98)
# Compu... |
a10143278dcf649bf04d19949d8bab2a8294f8f80f7e24a22e937a65b7368880 | Shell | 941 | 13 | #!/bin/bash
n1=20
n2=14
windowSize=10000
#mkdir -p trainingSimsStats trainingSets classifier results
#gunzip trainingSims/*.msOut.gz
#for inFile in `ls trainingSims/ | grep .msOut` ; do cat trainingSims/$inFile | ./twoPopnStats_forML $n1 $n2 | python normalizeTwoPopnStats.py None $windowSize > trainingSimsStats/$inFil... |
55dcfde6a6cf00c5d155503feb1eb29d6343cb62eec7167ee5a0d73f8405aefd | Shell | 942 | 33 | #!/bin/bash
#SBATCH --get-user-env
#SBATCH --job-name=calc_CpG_PDR-%j-chr_%a
#SBATCH --chdir=${WORKDIR}
#SBATCH --error=${LOG_DIR}/calc_CpG_PDR-%j-chr_%a.err
#SBATCH --output=${LOG_DIR}/calc_CpG_PDR-%j-chr_%a.out
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=24G
#SBATCH --gres-flags=enforce-bindin... |
ee601ee8be2d3e941a0afc07761a9da318597b1bcd85c2895d5a9ee4b9791eeb | Shell | 951 | 30 | #!/bin/sh
#
#SBATCH --job-name=fit_fcs_job # Optional: Name of your job
#SBATCH --output=logs/fcs_out.txt # Standard output log
#SBATCH --error=logs/fcs_err.txt # Standard error log
#SBATCH --time=7-00:00:00 # Walltime for each task (7 days)
#SBATCH --cpus-per-task=8 # Number of CPU cores per task
... |
19b3abc3745fb48c25065570e269e6d1997ebd25430031f6a12e186e4e6d6582 | Shell | 974 | 36 | #! /bin/sh
# If the user specified a --prefix, take that, otherwise /usr/local/
# is the default.
PREFIX=/usr/local
prefixnext=false
for i in "$@"; do
case $i in
--prefix=*) # equals separated:
PREFIX="${i#*=}"
;;
--prefix) # space separated:
prefixnext=true
;;
*)
... |
b762d47190aa40457bb8602c46a7c1964372ce4090d06156aae70c53bcabc143 | Shell | 974 | 39 | #!/bin/bash
acc_dir="./preprocessing_acc/"
methyl_dir="./preprocessing_methyl/"
mart_export_acc=$acc_dir"mart_export_acc.bed"
mart_export_methyl=$methyl_dir"mart_export_methyl.bed"
res_dir_acc=$acc_dir"results_find_common_region"
res_dir_methyl=$methyl_dir"results_find_common_region"
mkdir $res_dir_acc
mkdir $res_dir... |
aa38730a1d5ab179f1dee39c0466fd50f484c4776d0f82d545af494584a79d26 | Shell | 987 | 37 | #!/bin/bash
#
#$ -N simul_dfc_job
#$ -o logs/simul_out.txt
#$ -e logs/simul_err.txt
#$ -l h_rt=24:00:00
#$ -l h_vmem=8g
#$ -t 1-200
#$ -q YOUR_QUEUE
# ---- Cluster configuration (set these for your system) ----
VENV_PATH="/path/to/your/venv/bin/activate"
PYDFC_CODE_DIR="/path/to/pydfc"
# For conda environments, replac... |
0084b55b12cb001afc58a1cccc690d4c78677de121eea11fa6e4ba5fa87ca587 | Shell | 1,000 | 33 | #!/bin/bash -e
: "${BRANCHES_TO_MERGE_REGEX?}" "${BRANCH_TO_MERGE_INTO?}"
: "${GITHUB_SECRET_TOKEN?}" "${GITHUB_REPO?}"
export GIT_COMMITTER_EMAIL='travis@travis'
export GIT_COMMITTER_NAME='Travis CI'
if ! grep -q "$BRANCHES_TO_MERGE_REGEX" <<< "$TRAVIS_BRANCH"; then
printf "Current branch %s doesn't match regex... |
afd82ea3b029d0961a3861fcfa8515b9502335886bf2ab0bec894bdc59f28198 | Shell | 1,000 | 39 | #!/bin/sh
#
#$ -N extract_roi_job
#$ -o logs/roi_out.txt
#$ -e logs/roi_err.txt
#$ -l h_rt=24:00:00
#$ -l h_vmem=64g
#$ -t 1-NSUBJECTS
#$ -q YOUR_QUEUE
# ---- Cluster configuration (set these for your system) ----
VENV_PATH="/path/to/your/venv/bin/activate"
PYDFC_CODE_DIR="/path/to/pydfc"
# ---------------------------... |
6a0f6dd2c94bed47e049b25d7f336afb45a0186307d5d17da325f88a3538a474 | Shell | 1,001 | 31 | #!/bin/sh
#
#SBATCH --job-name=assess_dfc_job # Optional: Name of your job
#SBATCH --output=logs/dfc_out.txt # Standard output log
#SBATCH --error=logs/dfc_err.txt # Standard error log
#SBATCH --time=24:00:00 # Walltime for each task (24 hours)
#SBATCH --mem=32G # Memory request ... |
93b89ce6ab13384470c3157d7c894d015f753b49a60a3554c8bf07e94e89a05d | Shell | 1,012 | 37 | #!/bin/sh
#
#SBATCH --job-name=extract_roi_job
#SBATCH --output=logs/roi_out.txt
#SBATCH --error=logs/roi_err.txt
#SBATCH --time=24:00:00
#SBATCH --mem=64G
# -----------------------------
# Inputs
# -----------------------------
SUBJECT_LIST="./subj_list.txt"
DATASET_INFO="./dataset_info.json"
DENOISING_STRATEGY=${1:-... |
bc1806bd4950c5b8b0b554362d9d657067c6353c62d7514d452054e98714c121 | Shell | 1,026 | 30 | #!/bin/bash
# Automatically creates .fsf files for running 2nd-level subject-wise GLM based on GLM-specific template.
#
# Make executable:
# chmod a+x feat_create_GLM_Subject.sh # make executable
#
# Execute:
# ./feat_create_GLM_Subject.sh # run
#
# EEG/fMRI STUDY, DONDERS INSTITUTE, NIJMEGEN.
# J. Algermissen, 2018-... |
3a452276563a7b718a6444ce269aad077dc299acdfc42b746e2d847fbe98f213 | Shell | 1,029 | 20 | #!/bin/bash
#SBATCH --cpus-per-task=3
#SBATCH --time=36:00:00
#SBATCH --output=job-%j.out
#SBATCH --error=job-%j.err
## TWAS - METSIM+INTERVAL TWAS (GTEx v8 weights)
while read TISSUE CHROMOSOME;
do
Rscript ~/data/users/william/fusion_twas-master/FUSION.assoc_test.R \
--sumstats ~/data/users/william/Meta_retinol_GW... |
4a5a9947ae2949bfee2a77a89d039fb881966be8f28c6f2f1c820d32faea439c | Shell | 1,030 | 9 | set -e
#python3 ./ExcelToOwl.py -d bcio_upper_level.owl,bcio_external.owl -i ../Setting/bcio_setting.xlsx -o ../Setting/bcio_setting.owl
python3 ./ExcelToOwl.py -d bcio_upper_level.owl,bcio_external.owl -i ../ModeOfDelivery/MoD.xlsx -o ../ModeOfDelivery/bcio_mode_of_delivery.owl
python3 ./ExcelToOwl.py -d bcio_upper_l... |
66e207d907d85377754c59be5356ae80d0df1e2faa93e330d502fef8af24952e | Shell | 1,031 | 45 | #/bin/bash
USAGE="
sh tests/mnenufaar_test.sh -v version_number - launch from nenufaar folder
"
if [ "$#" -eq 0 ]; then
echo "${USAGE}"
echo "Error Message : No arguments provided"
echo ""
exit 1
fi
while [[ "$#" -gt 0 ]]
do
KEY="$1"
case "${KEY}" in
-v|--version) #mandatory
VERSION="$2"
shift
;;
-h|-... |
5509879ea164e36ae69b8d90accdafee343507c05ee17a473ec598dad9c0eee7 | Shell | 1,041 | 20 | #!/bin/bash
#SBATCH --cpus-per-task=3
#SBATCH --time=36:00:00
#SBATCH --output=job-%j.out
#SBATCH --error=job-%j.err
## TWAS - METSIM+INTERVAL TWAS (GTEx v8 weights)
while read TISSUE CHROMOSOME;
do
Rscript ~/data/users/william/fusion_twas-master/FUSION.assoc_test.R \
--sumstats ~/data/users/william/Meta_retinol_GW... |
83b2d7a39ce7c6bea623e78a651111669826e81c2afa5ec22c174ddd856a9bed | Shell | 1,043 | 42 | #!/bin/bash
#This script uses denoised fMRI data to calculate DVARS and create a gray plot.
#Check if the inputs are correct
if [ $# -ne 5 ]
then
echo "Insufficient inputs"
echo "Input 1 should be the denoised fMRI data"
echo "Input 2 should be the brain mask"
echo "Input 3 should be the gray matter (1s)/white... |
2da738ef758b14dca2907aa5d673ef9aabd81b0639047529de4c21d9a39ea3bf | Shell | 1,053 | 35 | #!/bin/bash
# Reads uzb-big and kaz-uzb files line by line
# Calculates WER per line
# Sorts by WER score in descending order to show what sentences are causeing the most problem.
# Reading both files line by line at once:
count=0
declare -a lines
while IFS= read -r line_test && IFS= read -r line_ref <&3; do
count... |
63ad4a0b7684d4c822bd2903b1fdee4f64cbbf1aebc4f40cdc7720836160669f | Shell | 1,055 | 37 | #!/bin/bash
# Load STAR module
module load star
# Set run name and overhang length
run_name="0037"
overhang_length="50"
# Specify directories and files
input_dir="../data/01_fastq/${run_name}/"
genome_dir="../data/genome/index/"
gtf_path="../data/genome/ensembl/Mus_musculus.GRCm39.109.gtf"
output_dir="../data/02_ali... |
a943a0cbbf35129ac535b400df30ad09a01ba3d3e6e7c8bfddff0c4aee32fa10 | Shell | 1,055 | 37 | #!/bin/bash
# Load STAR module
module load star
# Set run name and overhang length
run_name="0010"
overhang_length="50"
# Specify directories and files
input_dir="../data/01_fastq/${run_name}/"
genome_dir="../data/genome/index/"
gtf_path="../data/genome/ensembl/Mus_musculus.GRCm39.109.gtf"
output_dir="../data/02_ali... |
ca1926e8786b39a946d75cb0a13729ec5e7c29af362cdcffd1bfd52277da075a | Shell | 1,055 | 37 | #!/bin/bash
# Load STAR module
module load star
# Set run name and overhang length
run_name="0038"
overhang_length="50"
# Specify directories and files
input_dir="../data/01_fastq/${run_name}/"
genome_dir="../data/genome/index/"
gtf_path="../data/genome/ensembl/Mus_musculus.GRCm39.109.gtf"
output_dir="../data/02_ali... |
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