sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5cab3d2f182afc816b3614bfbd07fdb90f65a99a3bac8b00981e19ed6b9bc9c3 | Shell | 489 | 11 | #!/usr/bin/env bash
#donwload average template from ABI Website
wget -O abi_10micron_average.nrrd http://download.alleninstitute.org/informatics-archive/current-release/mouse_ccf/average_template/average_template_10.nrrd
#download annotation
wget -O abi_10micron_annotation.nrrd http://download.alleninstitute.org/info... |
d9828fdc17e38d64e93768db81a4a31e74c4c4b8eee7fbf1121887c78333f755 | Shell | 489 | 18 | #!/bin/bash
set -euo pipefail
PYTHON_VERSION=${1:-}
if [[ -z "${PYTHON_VERSION}" ]]; then
FILENAME="requirements_compiled.txt"
else
FILENAME="requirements_compiled_py${PYTHON_VERSION}.txt"
fi
mkdir -p /tmp/ray-deps
# Remove the GPU constraints
cp "python/${FILENAME}" "/tmp/ray-deps/${FILENAME}"
sed -e '/^-... |
fe38582e056d384acd8876532bf6b71e4d54e1d53f2c4dbfaeb8749cc146bd28 | Shell | 489 | 4 | for sample in R12258 R12260 R12263 R12265 R12266 R12277 R12278 R12280 R12285 R12287; do
echo samtools sort ../results/ribozero_STAR/$sample.bamAligned.sortedByCoord.out/cleaned_2stage.bam -o ../results/ribozero_STAR/$sample.bamAligned.sortedByCoord.out/cleaned_2stage.sort.bam &
samtools sort ../result... |
241924cefccca8417f9d1991b84776cd8abf6e378e7f5367ca63d5d7ae6bdbb3 | Shell | 491 | 7 | #/bin/bash
# Automatically find last checkpoint file (first line), and evaluate that model on the test data (second line)
ckpt=$(ls `pwd`/nifti/experiments/mdgru_discardme/*/cache/*.index -dArt | grep -v -e "latest" | tail -n 1 | sed 's/.index//g')
python3 ../../RUN_mdgru.py --datapath `pwd`/nifti --onlytest --locati... |
f5be73f3eb0e3d253d623ceedba39d3bde00127f2ecb21eab022ca7f38dc3f0e | Shell | 493 | 21 | #!/bin/bash
trait=MetS_lind
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--diff-freq 0.2 \
--cojo-file ${dir_cojo_input}... |
0c75efff248ca504e9a6a7b60bf94d10ad9fda7ff88cd1da2d1b909053a755c2 | Shell | 494 | 4 | for sample in R12258 R12260 R12263 R12265 R12266 R12277 R12278 R12280 R12285 R12287 ; do
echo scp /Users/chaokuan-hao/Documents/Projects/PR_SPLAM/results/ribozero_STAR/$sample/junction_score.bed s3:/ccb/salz3/kh.chao/SPLAM/results/ribozero_STAR/$sample.bamAligned.sortedByCoord.out/
scp /Users/chaokuan-... |
b6dae9e0baf18f935182e469494511f38e10b5c7b78a914929fc02d687f38ea4 | Shell | 494 | 22 | #!/bin/bash
#SBATCH --cpus-per-task=8
#SBATCH --mem=16G
#SBATCH --time=1-00:00:00
reads=$1
outbase=$2
ref=$3
#should be in <path_to_miniC>/data/C_Mcommon/bowtie2/cm.common.mt
#ref=data/C_Mcommon/bowtie2/cm.common.mt
#out=`basename $reads`
# bowtie alignment
/homes/liu3zhen/local/bin/bowtie2 --no-head --all \
-x $re... |
b6fd16dbcb8d345edf300b27887a9ebafa6d483485f8b002a037355b9d7194b4 | Shell | 495 | 21 | #!/bin/bash
trait=MetS_walree
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--diff-freq 0.2 \
--cojo-file ${dir_cojo_inpu... |
296b396e02f8af8816580a6c06b04ba14227873c58cb3fb936f0d114f204b58b | Shell | 497 | 17 | #!/bin/sh
python3 ../ntd/train_diffusion_model.py \
base.experiment=crcns_experiment \
base.tag=conv_wn \
dataset=crcns \
diffusion=diffusion_linear_200 \
diffusion_kernel=white_noise \
network=cat_conv_crcns \
optimizer=base_optimizer \
optimizer.lr=0.0001 \
optimizer.num_epochs=50... |
307cb0f3f48c27d76ed2a1c0b0ded273ae5ca1e50fd68f5dce975260c6c714ed | Shell | 497 | 11 | #!/bin/csh -f
# the -acf parameters were generated from running 3dFWHMx on the group stats errts file.
# then, averaged across all 79 participants to get the average a, b, and c parameters
cd top_dir/
# Using the MNI cerebellum group mask
3dClustSim -mask ./Group_Cerebellum_Mask/groupcerebellummask_79subjs_75ghits_ma... |
1977aab33ea7db464ba874c7497591a4a8656f6d349036b49bf8458055f27121 | Shell | 498 | 20 | #!/bin/bash
NAME=MetS
LDSCOUT=../../ldscout/MetS_ldscout.RData
outDir=.
#######################################
Rscript exc.parallel_analysis.R --name "${NAME}" \
--rdata "${LDSCOUT}" \
--outDir "${outDir}"
NAME=MetS_noUKB
LDSCOUT=../../ldscout/MetS_noUKB_ldscout.RData
outDir... |
204be16b3ff74eea1e6872ea48d044a1624f948996062783eaa76a864f0561b8 | Shell | 498 | 35 |
SCHEME STDERR
AVERAGEFREQ ON
MINMAXFREQ ON
COLUMNCOUNTING STRICT
VERBOSE OFF
GENOMICCONTROL OFF
SEPARATOR TAB
MARKER SNP
ALLELE A1 A2
FREQLABEL MAF
EFFECT Effect
STDERR SE
PVAL Pval
PROCESS ../../EasyQC/results/CLEANED.T2D_Finngen_r7_GC.txt
GENOMICCONTROL ON
SEPARATOR TAB
MARKER SNP
ALLELE A1 ... |
408f73d70685270ff46b10cd129ba33436e2adae30ad83b4e3654c81cab7c7db | Shell | 498 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# mujoco/reproduction/trpo (specify non-mujoco env to test without mujoco)
python examples/mujoco/reproduction/trpo/train_trpo.py --steps 10 --trpo-update-interval 5 --outdir $outdir/mujoco/reproduction/trpo --env Pendulum-v0 --gpu $gpu
model=$(find $outdir/mujoco/r... |
6e1343d77d68d40055f25fcc434eb208235aac151ea9d90e17b4219e8f545ab7 | Shell | 499 | 19 | #!/bin/bash
NAME=MetS_noUKB
LDSCOUT=../../2_ldsc/ldscout/MetS_noUKB_ldscout.RData
outDir=.
#######################################
Rscript exc.compute_KMO.R --name "${NAME}" \
--rdata "${LDSCOUT}" \
--outDir "${outDir}"
NAME=MetS
LDSCOUT=../../2_ldsc/ldscout/MetS_ldscout.RData... |
eafa2f4d982b6716ca6f1a4d1db74793c15d484bc0305b647d49563d890baabf | Shell | 499 | 17 | #!/bin/bash
# Builds and runs a marugoto container.
#
# Usage:
# ./marugoto-container.sh \
# marugoto.mil.train --target_label isMSIH [other marugoto options]
podman build --target deploy $(dirname -- "$0")
image_id=$(podman build --target deploy --quiet $(dirname -- "$0"))
podman run --rm -ti --shm-size 16g \
... |
381776f2f257b1a9b9abed829d423492f245655fdffd6a108548d8f37ddd7755 | Shell | 500 | 19 | #!/usr/bin/env sh
if [ ! -f "data/stage1_train.zip" ]; then
printf "Downloading data from kaggle\n"
kaggle competitions download -c data-science-bowl-2018 -f stage1_train.zip -p data
else
printf "data/stage1_train.zip already exists\n"
fi
if [ ! -d "data/cells" ]; then
printf "Unzipping datasets/stage1_train.zip ... |
b88db48006cad239e2f5d1bf0897ea38467f7dfee275b5178378914bc9356218 | Shell | 500 | 12 | #!/usr/bin/bash
keyword=$1
vamb taxometer \
--outdir /home/projects/cpr_10006/people/svekut/cami2_rhizo_predictor_taxometer_${keyword}_cpu \
--fasta /home/projects/cpr_10006/data/CAMI2/rhizo/vamb_output/contigs_2kbp.fna \
--rpkm /home/projects/cpr_10006/data/CAMI2/rhizo/vamb_output/vambout/abundance.npz \
... |
289a001660ef0d4551fa206a5eda2e47ab69c730bd1b5ffe1af62b9e71f55307 | Shell | 501 | 19 | #!/usr/bin/env sh
set -e
FILE_NAME=speech_commands_v0.01.tar.gz
URL=http://download.tensorflow.org/data/$FILE_NAME
DATASET_FOLDER=datasets/speech_commands
echo "downloading $URL...\n"
wget -O datasets/$FILE_NAME $URL
echo "extracting $FILE_NAME..."
TEMP_DIRECTORY=$DATASET_FOLDER/audio
mkdir -p $TEMP_DIRECTORY
tar -x... |
b05bdfad3c55ef4aa83ab3e2b6c8d98323337946c211c549783cb2820c13a6cd | Shell | 503 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# mujoco/reproduction/td3 (specify non-mujoco env to test without mujoco)
python examples/mujoco/reproduction/td3/train_td3.py --env Pendulum-v0 --gpu $gpu --steps 10 --replay-start-size 5 --batch-size 5 --outdir $outdir/mujoco/reproduction/td3
model=$(find $outdir/... |
b4cb17f383ab51c6c7fd9a67ef9470a8cbc9d586a5ba239a978becc20fbd221c | Shell | 504 | 12 | #!/usr/bin/bash
keyword=$1
vamb taxometer \
--outdir /home/projects/cpr_10006/people/svekut/cami2_marine_predictor_taxometer_${keyword}_cpu \
--fasta /home/projects/cpr_10006/data/CAMI2/marine/vamb_output/contigs_2kbp.fna \
--rpkm /home/projects/cpr_10006/data/CAMI2/marine/vamb_output/vambout/abundance.npz... |
5e599b0d298e88d3dd71a962b0bbfc463f715ad30e0186f74e2a88eaf49d9e53 | Shell | 507 | 25 | #!/bin/bash
#
# make_promoters.sh
#
# Derive promoters from gencode GTF
#
set -e
gtf=$1
window=$2
zcat $gtf \
| awk -v FS="\t" -v OFS="\t" -v window=$window '{
if ($3=="transcript") {
split($9, fields, ";");
split(fields[1], gene_id, " ");
split(fields[5], gene_name, " ");
if ... |
6104b37768a6532879fad037931d8527c5f39e8ba4295f6418502258179b4ff0 | Shell | 507 | 9 | plink2 --vcf $1.vcf.gz --make-bed --out $1
plink2 --bfile $1 --set-missing-var-ids @:# --make-bed --out $1.annotated
plink2 --bfile $1.annotated --maf 0.05 --make-bed --out $1.maf0.05
plink2 --bfile $1.maf0.05 --hwe 1e-6 --make-bed --out $1.hwe
plink2 --bfile $1.hwe --indep-pairwise 250 50 0.4 --out $1.pruned
plink2 -... |
770981fa169ff5b58ea0e451f7ba7355de3416b19fccf4100b7f522bdc57acac | Shell | 508 | 18 | #!/bin/bash
folder_name=$1
user_name="$USER"
echo $folder_name
# zip the raw image files if applicable
PROCESS_ID=$(sbatch -N1 -n1 --mem-per-cpu=4000M -t01:59:00 zip_data.sh $folder_name) #
#echo $script_name' finished in '$folder_name
# # Convert to analysis folders
# # PROCESS_ID=$(sbatch -N1 -n1 --mem-per-... |
00046620b246eb757120bd858d5160da60c68689817dcd6b15a13c2798ef598b | Shell | 510 | 18 | #!/bin/bash
folder_name=$1
user_name="$USER"
echo $folder_name
# zip the raw image files if applicable
PROCESS_ID=$(sbatch -N1 -n1 --mem-per-cpu=4000M -t01:59:00 unzip_data.sh $folder_name) #
#echo $script_name' finished in '$folder_name
# # Convert to analysis folders
# # PROCESS_ID=$(sbatch -N1 -n1 --mem-pe... |
d854238962ce392e78f03a1f6bffd965d4d51038abd716c6249188b730e931f8 | Shell | 510 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# mujoco/reproduction/ddpg (specify non-mujoco env to test without mujoco)
python examples/mujoco/reproduction/ddpg/train_ddpg.py --env Pendulum-v0 --gpu $gpu --steps 10 --replay-start-size 5 --batch-size 5 --outdir $outdir/mujoco/reproduction/ddpg
model=$(find $out... |
1ed80e791bf1eab9e54c767fff7cfbac957662182324466a20ce3980f5381a6b | Shell | 511 | 21 | #!/usr/bin/bash
# Merge all of the temporary mtx files
pconf -t DEVTRAJ -s multiRegion
UCSCDIR=$SDBDIR/ucsc_datasets/
ADDIR=${UCSCDIR}/ad-multi-region/
cd $ADDIR
if [[ ! -s ${ADDIR}/matrix.mtx.gz ]]; then
cat ${ADDIR}/tmp_matrix_header.mtx > ${ADDIR}/matrix.mtx
while read -r file; do
echo "-- $file"
... |
52ab98fdc4721a15e2a3a8a57db5ab3df175b063a48af32ff65c3bc5f8791b28 | Shell | 511 | 22 | #!/bin/bash
trait=WC
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-file... |
537328d3788e902a84e3d73c953b484af0f84753f1a7fb7ce035c20655d5a0a8 | Shell | 511 | 22 | #!/bin/bash
trait=MetS
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-fi... |
87d66f847797fcb05804aabdcd02719738326cb1fc0f41036b4e7065fef4e2ba | Shell | 511 | 22 | #!/bin/bash
trait=TG
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-file... |
bf726ed0da330c5238cc9610936381af590a78de9afe53f819a68b0a54a9a145 | Shell | 511 | 15 | #!/usr/bin/env bash
# Push caller's shell options (quietly)
{ SHELLOPTS_STACK="${SHELLOPTS_STACK-}|$(set +o); set -$-"; } 2> /dev/null
set -euxo pipefail
SCRIPT_DIR=$(builtin cd "$(dirname "${BASH_SOURCE:-$0}")"; pwd)
WORKSPACE_DIR="${SCRIPT_DIR}/../.."
sudo apt-get install -y maven openjdk-8-jre openjdk-8-jdk
"${W... |
59364266dc4034c6b0ac92b8f494af24672fd6d319dc5fe74ce7c917130cfa9b | Shell | 512 | 22 | #!/bin/bash
trait=T2D
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-fil... |
675f192dc3f7e74cf39bcb2739e150d5e1654f325e436cf40b046bb79b7184d7 | Shell | 512 | 22 | #!/bin/bash
trait=HTN
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-fil... |
78590faccc2cf0a211d7201425b18c2028932d648079d86cd670cb0a03c75e77 | Shell | 512 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# atari/reproduction/dqn
python examples/atari/reproduction/dqn/train_dqn.py --env PongNoFrameskip-v4 --steps 100 --replay-start-size 50 --outdir $outdir/atari/reproduction/dqn --eval-n-steps 200 --eval-interval 50 --n-best-episodes 1 --gpu $gpu
model=$(find $outdir... |
a11eaa98d86222af43d1bb46d59624da4b1dfb1c1e760105b98449a7af104b36 | Shell | 512 | 17 | #!/bin/bash
docker build -t cebra-docs -f docs/Dockerfile .
docker run -u $(id -u):$(id -g) \
-p 127.0.0.1:8000:8000 \
-v $(pwd):/app \
-v /tmp/.cache/pip:/.cache/pip \
-v /tmp/.cache/sphinx:/.cache/sphinx \
-v /tmp/.cache/matplotlib:/.cache/matplotlib \
-v /tmp/.cache/fontconfig:/.cache/fontconfig \
-e... |
ada8b7d1ff4fe72dfea5ace7233700995a377a8dd60855fc3254ae365434528b | Shell | 512 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# mujoco/reproduction/ppo (specify non-mujoco env to test without mujoco)
python examples/mujoco/reproduction/ppo/train_ppo.py --steps 10 --update-interval 5 --batch-size 5 --epochs 2 --outdir $outdir/mujoco/reproduction/ppo --env Pendulum-v0 --gpu $gpu
model=$(find... |
cc53bf753d0a638a4033dba2fbbc1f4be9cc347b3789758fd286c1d70bd1d217 | Shell | 512 | 22 | #!/bin/bash
trait=HDL
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-fil... |
d998490f71b7a71be6e5b629573a1cbc0dd5099e26899de55f6c411e9a6873a2 | Shell | 512 | 22 | #!/bin/bash
trait=BMI
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile} \
--maf 0.01 \
--diff-freq 0.2 \
--cojo-fil... |
2c82b3eb9b780141e46b60a1b109e57342733550254d459c55a227de7f07f831 | Shell | 513 | 23 | #!/bin/bash
# set number of parallel processes
NUM_PARALLEL=1
if [ $# -eq 1 ]
then
NUM_PARALLEL=$1
fi
# use exputils package to generate experiments and run them
python -c "import exputils
print('Generate experiments ...')
exputils.manage.generate_experiment_files('experiment_configurations.ods', directory='./expe... |
e8c63eb097da58f353e422cab161893d2239e8239b3a4308c44ac8ea905dcfd1 | Shell | 513 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# atari/reproduction/iqn
python examples/atari/reproduction/iqn/train_iqn.py --env PongNoFrameskip-v4 --steps 100 --replay-start-size 50 --outdir $outdir/atari/reproduction/iqn --eval-n-steps 200 --eval-interval 50 --n-best-episodes 1 --gpu $gpu
model=$(find $outdi... |
fd05619e00390bac36736f64480e5beabe9fe169f9ba1963047dac7189828e91 | Shell | 513 | 17 | #!/usr/bin/bash
vamb \
--model vaevae \
--outdir /home/projects/cpr_10006/projects/vamb/almeida_vaevaeout \
--fasta /home/projects/cpr_10006/projects/vamb/analysis/almeida/data/almeida.fa.gz \
--rpkm /home/projects/cpr_10006/projects/vamb/analysis/almeida/data/almeida.jgi.depth.npz \
--taxonomy /ho... |
565ccdaa87e7cbbfed75b93a68418a9bab01b7a943223b6f2722eefd7d12172b | Shell | 514 | 24 | #!/bin/bash
#SBATCH -t 10:00
#SBATCH --ntasks 1
#SBATCH --cpus-per-task 1
#SBATCH --mem-per-cpu=1GB
#SBATCH --job-name FRASESCREEN
#SBATCH --array 0-10598
module load miniconda3
eval "$(conda shell.bash hook)"
conda activate rdkit-tools
start_time=$(date +%s)
folder_id=0
arr=(`ls ../FRASE_database_PDB${folder_id}/`... |
178574013ac45c7116354f130d9dff24b7cba6b0b193d8c93a70ebe5185e59cc | Shell | 515 | 13 | #!/usr/bin/bash
keyword=$1
# --cuda \
vamb taxometer \
--outdir /home/projects/cpr_10006/people/svekut/cami2_rhizo_predictor_taxometer_${keyword}_cpu \
--fasta /home/projects/cpr_10006/data/CAMI2/rhizo/vamb_output/contigs_2kbp.fna \
--rpkm /home/projects/cpr_10006/data/CAMI2/rhizo/vamb_output/vambout/a... |
3892ad91e0c88bca0ff3a72d7c8d2fd5f494b57af8276d111b9a88d6e812ae10 | Shell | 515 | 22 | #!/bin/bash
trait=FG
n_thread=5
###
exe_gcta=gcta-1.94.1
bfile=UKB_random10k_noqc
file_leadsnp=../leadSNP/leadSNP_list.${trait}.txt
dir_cojo_input=../cojo_input
dir_out=cojo_out.${trait}
mkdir -p ${dir_out}
${exe_gcta} --bfile ${bfile}${chr} \
--maf 0.01 \
--diff-freq 0.2 \
--coj... |
e363d01b4864bb7a52c9f83bc3c0c24a384f6e1ca434b138eabdb07be9c8cca1 | Shell | 515 | 4 | for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
echo ../SPLAM_C++/build/SPLAM clean -m ../MODEL/splam_14_script.pt -r ../Dataset/hg38_p12_ucsc.no_alts.no_fixs.fa -o ../results/polyA/$sample/ --paired-removal --2-stage-run ../Dataset/polyA/$sample/$sample.bam &
../SPLAM_C++/build/... |
113a0ea40649974cc92c44e80f7a47a829e9036f9e2acd95f6517d47a734fd33 | Shell | 516 | 7 | #!/bin/bash
# Automatically select last two checkpoints (first line) and evaluate them using automatic naming using one optionname (second line)
ckpts=$(ls `pwd`/nifti/experiments/mdgru_discardme/*/cache/*.index -dArt | grep -v -e "latest" | tail -n 2 | sed 's/.index//g')
python3 ../../RUN_mdgru.py --datapath `pwd`/n... |
e0243ad450326bde7f9b154a270ecdd77429ae29a11af3b52a22dc8009f9ebf8 | Shell | 517 | 36 |
SCHEME STDERR
AVERAGEFREQ ON
MINMAXFREQ ON
COLUMNCOUNTING STRICT
VERBOSE OFF
GENOMICCONTROL OFF
SEPARATOR TAB
MARKER SNP
ALLELE A1 A2
FREQLABEL MAF
EFFECT Effect
STDERR SE
PVAL Pval
PROCESS ../../EasyQC/results/CLEANED.HTN_Finngen_r7_GC.txt
GENOMICCONTROL OFF
SEPARATOR TAB
MARKER SNP
ALLELE A... |
f9fb9c400182cb53a616a063f1ecbd667093c6e2482628a03107dea8944a368b | Shell | 519 | 13 | #!/usr/bin/bash
keyword=$1
# --cuda \
vamb taxometer \
--outdir /home/projects/cpr_10006/people/svekut/cami2_marine_predictor_taxometer_${keyword}_cpu \
--fasta /home/projects/cpr_10006/data/CAMI2/marine/vamb_output/contigs_2kbp.fna \
--rpkm /home/projects/cpr_10006/data/CAMI2/marine/vamb_output/vambou... |
5da2871511cf1cd4783109844c24ee67eb66997ecc3e82caf048c57d8cd2a452 | Shell | 522 | 8 | #!/bin/bash
wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1V4PUIW2LN6QjMOANEEt46LMuM7ktDZg6' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+)... |
e56152e367db7a64a00ae1b55dff488729a5e5ca13d909ec6c7d525408ef1ddf | Shell | 522 | 14 | echo "Updating the bin folder from the Linux source tree"
mkdir -p "bin"
cp "LICENSE" "bin"
cp "celslc/celslc" "bin"
cp "celslc/celslc howto.txt" "bin"
cp "msa/msa" "bin"
cp "msa/msa howto.txt" "bin"
cp "wavimg/wavimg" "bin"
cp "wavimg/wavimg howto.txt" "bin"
cp "BuildCell/executables/Linux/BuildCell.linux" "bin/BuildC... |
1e6fffd75718c8d37bfcb0114ba1a86a295041fc314f47adefa26fa73214aedd | Shell | 523 | 25 | #!/bin/bash
#
# add_genelists.sh
#
set -e
coding=$1
fout=$2
# Add header
echo -e "name\teffect\tgenelist" > $fout
# First mark all genes
awk -v OFS="\t" '($2 != "INTERGENIC") {print $1, $2, "Any"}' $coding \
| sort -k1,1 -k2,2 -u \
| sed -e '1d' >> $fout
while read genelistname; do
genelist=genelists/geneSe... |
32d5b8bf02f4de084d14b26c95dfa25b642fb2a58d8011f13d0e2df01562c706 | Shell | 523 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/Mandino_2019_3xTg/ds001890-download/:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/rabies_Mandino_2019_3xTg_20211026:/rabies_out \
-B /home/m/mchakrav/desgab/atlase... |
341f2f2f51399d36ad159ceb1b1c83de4fe71a015d4d263b4372efdb599eebeb | Shell | 524 | 31 | #!/bin/bash
# Check that all required arguments are provided
if [[ $# > 1 ]]; then
echo "Usage: $0 [ veryclean ]" >&2
exit 1
fi
to_remove=(
)
veryclean_to_remove=(
.run-config/
output/
)
# Check for "veryclean" option
if [[ $1 == "veryclean" ]]; then
echo "Running in veryclean mode..."
to_remove+=... |
969849ff18fd3970d54d2fbc03de4b412a7f1a22c0e34c7299a6a80d66505d79 | Shell | 525 | 29 | #!/usr/bin/bash
while getopts "d:o:" opt; do
case $opt in
d) drep_dir=$OPTARG ;;
o) clusters_file=$OPTARG ;;
*) echo 'error' >&2
exit 1
esac
done
echo 'creating z y v clusters from the final set of bins'
cd $drep_dir
for bin in $(ls . 2> /dev/null)
do
if [[ $bin == **".fna" ]]
then
cl... |
a7d649a660836faa68d1d6fc07eb039e42d37c792858ff343d69f7e32ef21ed5 | Shell | 525 | 13 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
# Stringtie assembly for before
echo samtools index ../Dataset/polyA/$sample/$sample.bam &
samtools index ../Dataset/polyA/$sample/$sample.bam &
done
# ribozero
for sample in R12258 R12260 R12263 R12265 R12266 R1227... |
315c5be6384d15de0a56e71596bbb4e913c525658b14c94125e7570c305ddb26 | Shell | 526 | 21 | #!/bin/bash
#
# run script OPNMF solution brain projection
# R script requires 2 aguments #
## 1: Cohort to be investigated - "chimp" or "human"
## 2: relative path to GM mask for cohort e.g. "/masks/Chimp_GM_TPM_03_Cortex_2mm.nii.gz"
## Here wd = ~/project/chimp_human_opnmf/ which is hard coded into R script
# Coho... |
9a4fb7aa4f094d31820ada5c97f8e274848df560756cd9a298dc423a190fdaa3 | Shell | 526 | 5 | #!/bin/tcsh -f
set top_dir = top_dir/
cd $top_dir/
3dfractionize -template Group_stats_files_MNITransformed/MNI_Phonoden_in_LexFreq_out_noRF_AmpMod_vs_0_ttest+tlrc. -input OneCerebellum-MNIsegment.nii -clip 0.2 -vote -prefix GroupCerebellumMask
3dcalc -fscale -a Group_stats_files_MNITransformed/MNI_Phonoden_in_LexFreq_... |
82cb3fa0940b6f66e78e678231dbef8935224bf8a3a3f6751b7e98f410797f6e | Shell | 527 | 20 | #!/bin/bash
date_folder=$1
repress_completed=${2:-1}
if [ -f "$date_folder/labview_parameters.csv" ]; then
# this is a experiment folder
ViewExperimentDirectory.sh $date_folder $repress_completed
else
# this is not an experiment folder, repeat iteratively
# loop through all the directories in a date folder
for ... |
e76f696b8e71a82d498f0f2e4e00e8225898c31bda71545f5db1227288445228 | Shell | 528 | 3 | python -m experiments.eval_autism.generate_autism_exome
python -m experiments.eval_autism.generate_autism_genome
python main.py --save_path experiments/eval_sqtls --mut_data_path data/autism_exome/data.json data/autism_genome/data.json --load_model_path pretrained_models/DeltaSplice_models/model.ckpt-0 pretrained_mode... |
61fe854575b080b3d15ffd49d9ab9ec1557affcf3a87c9b080dcc08373bf4fea | Shell | 529 | 5 | #for sample in R12258 R12260 R12263 R12265 R12266 R12277 R12278 R12280 R12285 R12287 ; do
for sample in R12260 R12266 R12285 R12287 ; do
echo python Step_1_splam_prediction.py -f ../results/ribozero_STAR/$sample/fasta/junction.fa -o ../results/ribozero_STAR/$sample/junction_score.bed -m ../src/MODEL/SPL... |
c0e5beb85cc071fb43f57b3dde240bba450e6fdcfeab118e2f281032c580a371 | Shell | 533 | 16 | #!/bin/bash
set -euo pipefail
CONFIG_PATH="${1:-ci/raydepsets/configs/rayllm.depsets.yaml}"
mkdir -p /tmp/ray-deps
# Remove the GPU constraints
cp python/requirements_compiled.txt /tmp/ray-deps/requirements_compiled.txt
sed -e '/^--extra-index-url /d' -e '/^--find-links /d' /tmp/ray-deps/requirements_compiled.txt >... |
be8fe626147bc45df8c50868d003bcf3906874df3bfef448df0e689afb138520 | Shell | 538 | 7 | #!/bin/bash
# Automatically load last two checkpoint files (first name) and use provided optionnames for each of them during evaluation (second line)
ckpts=$(ls `pwd`/nifti/experiments/mdgru_discardme/*/cache/*.index -dArt | grep -v -e "latest" | tail -n 2 | sed 's/.index//g')
python3 ../../RUN_mdgru.py --datapath `p... |
def07655acedfe180f929f0d00a8af6fe627dd81b54edd1d01214be7214906ea | Shell | 538 | 16 | #!/bin/bash
# save the previous logs with the current timestamp and initialize new logs
log_directory=~/logs/
master_log_name=masterlog.csv
error_log_name=errorlog.csv
log_header=Script_Name,Status,Time,Folder_Name,JobID,Computer_Name,Comment
current_time=$(date +"%Y%m%d%H%M")
mv $log_directory$master_log_name $log... |
6dd35e4484691eaa39fcd51e9e52a5e09281389f0a757c5a9e2d150efdebd0e3 | Shell | 541 | 5 | rm -r experiments/eval_sqtls/test_results
python -m experiments.eval_sqtls.generate_sqtl
python -m experiments.eval_sqtls.generate_neg
python main.py --save_path experiments/eval_sqtls --mut_data_path data/sQTLs/data.json data/sQTLs_neg/data.json --load_model_path pretrained_models/DeltaSplice_models/model.ckpt-0 pr... |
91d3e6e52d0341ccae3cb2b082cc6793bede7c3f68fc414e0f5fd478e0c6659f | Shell | 546 | 4 | for sample in R12258 R12260 R12263 R12265 R12266 R12277 R12278 R12280 R12285 R12287 ; do
echo ../SPLAM_C++/build/SPLAM clean -m ../MODEL/splam_14_script.pt -r ../Dataset/hg38_p12_ucsc.no_alts.no_fixs.fa -o ../results/ribozero/$sample/ --paired-removal --2-stage-run ../Dataset/ribozero/$sample/$sample.bam ... |
cea806bda31c19be7632c27e05decf3efe3e62771eb335a72c50a46e446aabe7 | Shell | 547 | 19 | #!/bin/bash
N_THREADS=8
export MKL_NUM_THREADS=$N_THREADS
export NUMEXPR_NUM_THREADS=$N_THREADS
export OMP_NUM_THREADS=$N_THREADS
Sumstat=QC.MetS_noUKB_GWAS.REFORMAT4PRS.GWAS.txt
SampleSize=1252787
OUT=./out;mkdir -p $OUT
ref_1kg_eur=ldblk_1kg_eur
UKB_bim=ukb_eur_unrel_comb
python3 ../PRScs/PRScs.py --ref_dir "${ref... |
191441070477e1fc8d6355125ef38d8a0570e96c5cfaf0ef0a0f535ad0b8899b | Shell | 548 | 4 | #!/bin/bash -ue
min_threads=$(((16/2)<4 ? (16/2):4))
bcl2fastq -R /net/shendure/vol9/seq/NEXTSEQ/220110_NS500488_1276_AH23G5BGXL --output-dir ./lane_fastqs --sample-sheet SampleSheet.csv --loading-threads $min_threads --processing-threads 16 --writing-threads $min_threads --bar... |
5d4de79806a6d286438f5c66f0d8649aea4861be33071b2dded7e63864b8007b | Shell | 548 | 27 | #!/bin/bash
#
# trackpesr_ID.sh
#
##Keep track of PE-SR IDs throughout pipeline##
set -euo pipefail
##gzipped vcf##
vcf=$1
originalidlist=$2
OUTFILE=$3
##append new ids to original list##
svtk vcf2bed $vcf int.bed -i MEMBERS
##remove header and match id one per line##
awk '{if (NR>1) print $4 "\t" $NF}' int.bed \... |
05f70e368f86d6905fcce7b73bc4d5e5855b090fff46d4699c112163bd6db1c0 | Shell | 549 | 29 | #!/bin/bash
#
# merge.sh
#
set -e
quad=$1
ALU=${quad}.ALU.final_comp.vcf
LINE1=${quad}.LINE1.final_comp.vcf
SVA=${quad}.SVA.final_comp.vcf
vcf-concat -c $ALU $LINE1 $SVA |& fgrep -e "do not match"
if [[ $? -eq 0 ]]; then
echo "Columns do not match for quad ${quad}"
exit 1
fi
cat merged_header.vcf \
<(egrep ... |
430778ca6a1abfcc9681cbd8e890ffff70667a3c49430fd5f059cf1733d2358b | Shell | 551 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_RT_med_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_RT_med_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/singularity... |
b1388c6c87503f626799f003072f8404b50eeecca6506192c52cc42836d9657f | Shell | 551 | 11 | #!/bin/bash
#SBATCH --job-name=schlichting
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=16G
#SBATCH --time=2:30:00
conda activate leabra
jupyter nbconvert cross_pair_analysis.ipynb --to python
./main --mode=batch --saveDirName=./figs/test/results_--LRateOverAll=2 --runs=2 --trncyclog=false --tstcyclog=false ... |
3cc7aed0c4872388d4c6e10293f99a96797db850f6285b71ccecd8a9e422074e | Shell | 552 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/47_RT_iso_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_47_RT_iso_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/singulari... |
6381524c7e106d02f13ff3c349abd08f7d1687d7d10d6166fc6b7f3de7a21ee3 | Shell | 552 | 14 | #!/usr/bin/bash
dataset=$1
run_id=$2
vamb \
--model taxonomy_predictor \
--outdir /home/projects/cpr_10006/people/svekut/cami2_${dataset}_predictor_${run_id} \
--fasta /home/projects/cpr_10006/projects/semi_vamb/data/cami_errorfree/${dataset}/contigs.fna \
--rpkm /home/projects/cpr_10006/projects/semi_... |
82576e0b816a5c9284518a4b19953376f4009cc25af92ea1c44e439efebc1761 | Shell | 552 | 15 | #!/bin/bash
cat *.circRNA_exon_usage.txt | sort -k 5,5 | sort -k 1,1 | uniq > circRNA_exon_usage.txt
# Filter to only keep rows with 5 columns. These are the real hits:
cat circRNA_exon_usage.txt | awk 'NF==5{print}{}' > circRNA_exon_usage_filter.txt
# Get the alternatively used exons
cat circRNA_exon_usage.txt | awk... |
9e05be07d6eba5e73cf250be4f4241a0f38fcc6f49dfc00c1e7d9ba58588dd1d | Shell | 552 | 25 | #!/bin/bash
# Stop the script if an error occurs
set -e
### Feature extraction layer ###
# Install dependencies
sudo apt install --yes gcc g++ make cmake libatlas-base-dev libblas-dev libopenblas-dev liblapack-dev liblapacke-dev
#sudo add-apt-repository ppa:rock-core/qt4 && sudo apt install qt4-default
# Compile
c... |
14643b4d290cd70d30e6220392f99cab507abede19b92e6cd43ca604a25252da | Shell | 553 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/94_RT_iso_v:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_94_RT_iso_v_20221024:/rabies_out \
/home/m/mchakrav/desgab/singulari... |
c8010262108076d1a8d38545a4bd049d4bf34d65888bd3303c5b566154fc809b | Shell | 553 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_Cryo_aw_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_Cryo_aw_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/singulari... |
faab60b165b37240d5ff66174c9cb33a74641c3dbdc18ae4466c6418978c1e17 | Shell | 553 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_RT_halo_v:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_RT_halo_v_20221024:/rabies_out \
/home/m/mchakrav/desgab/singulari... |
ae6529f5f620300f8060b153185aa3dd00a3d0d74f4fa1edb98e06a16e1c5ded | Shell | 555 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/hypercapnia_ge_epi_data/bids_out/:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/rabies_hypercapnia_ge_epi_data_20211026:/rabies_out \
-B /home/m/mchakrav/desgab/atl... |
09900be26f3376c7b9e11c1c8f77264eb6159eee88275902da660caab1a4dd4c | Shell | 557 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_Cryo_med_f1:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_Cryo_med_f1_20221024:/rabies_out \
/home/m/mchakrav/desgab/singu... |
1917ba39af955731b23d95058899773e9c7defef6586a69839affc5d1557963e | Shell | 557 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/94_Cryo_iso_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_94_Cryo_iso_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/singu... |
291cc75b45661b3aca609897eae9f010345fd929310a7b35cba31211757eeda4 | Shell | 557 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_Cryo_med_f3:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_Cryo_med_f3_20221024:/rabies_out \
/home/m/mchakrav/desgab/singu... |
c48315dd2d128e868dae3dc0621554a88c8f30a03d5cabfb940baf535af15fcb | Shell | 557 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_Cryo_med_f2:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_Cryo_med_f2_20221024:/rabies_out \
/home/m/mchakrav/desgab/singu... |
df7baf695f44b9794a172fd76733ad2e4e1ee782c4927a39cb958c158238cd9d | Shell | 557 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/94_Cryo_med_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_94_Cryo_med_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/singu... |
3b942d39f0af8ee46f39c2054093afd3a7a797a2e55b85b07f5583d4f9c1c401 | Shell | 559 | 16 | mkdir data/genomes
cd data/genomes
for name in hg19 hg38 mm10 panTro5 rheMac10 rn6 susScr11 bosTau9 calJac4
do
wget https://hgdownload.cse.ucsc.edu/goldenpath/${name}/bigZips/${name}.fa.gz
done
gzip -d *.gz
for name in hg19ToBosTau9.over.chain hg19ToMm10.over.chain hg19ToPanTro5.over.chain hg19ToRheMac10.over.chain... |
42e299d6ab6f8f61b431701ffed02a933aec3c261e5fa42cac5e1a3491af4a12 | Shell | 559 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/117_Cryo_iso_f:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_117_Cryo_iso_f_20221024:/rabies_out \
/home/m/mchakrav/desgab/sin... |
bff19cc28f1ba03d01d69a96e0bdc4fcbfdea6bb597c440f477314a50c350c48 | Shell | 560 | 19 | #!/usr/bin/bash
#SBATCH --job-name=unet
#SBATCH --partition=gpu
#SBATCH --gres=gpu:nvidia_geforce_gtx_1080_ti:1
#SBATCH --mem=48g
#SBATCH --time=48:00:00
#SBATCH --output=/home/schaudhary/whole-brain_DeepDenoising/slurm_jobs/unet-%j.out
source ~/.bashrc
conda activate pytorch-env
python3 /home/schaudhary/whole-brain_... |
32181736909bc540e14d54854e20a46c6950f54c2dee40b3bb9a5ce437f4a6ad | Shell | 561 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/7_Cryo_mediso_v:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_7_Cryo_mediso_v_20221024:/rabies_out \
/home/m/mchakrav/desgab/s... |
f8fde54c4f6dffa5a8707297714879251dd892fa38344f27228f54483276f547 | Shell | 561 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/94_RT_mediso_f1:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_94_RT_mediso_f1_20221024:/rabies_out \
/home/m/mchakrav/desgab/s... |
3d53f9695570a592dd96021d9d10de5907356ed6115be17fc5bbb1d99f74f720 | Shell | 562 | 12 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
gpu="$1"
# mujoco/soft_actor_critic (specify non-mujoco env to test without mujoco)
python examples/mujoco/reproduction/soft_actor_critic/train_soft_actor_critic.py --env Pendulum-v0 --gpu $gpu --steps 10 --replay-start-size 5 --batch-size 5 --outdir $outdir/mujoco/soft_acto... |
cd2c4c560442f4a0ca1be06fb96cbfeae787765d1343a56835389b42637ae7fc | Shell | 563 | 13 | #!/bin/bash
set -Ceu
outdir=$(mktemp -d)
echo "outdir: $outdir"
gpu="$1"
# atari/reproduction/rainbow
python examples/atari/reproduction/rainbow/train_rainbow.py --env PongNoFrameskip-v4 --steps 100 --replay-start-size 50 --outdir $outdir/atari/reproduction/rainbow --eval-n-steps 200 --eval-interval 50 --n-best-epi... |
4ef54bf565566712db17377088024da8d346cd1e8280d1520bb050a439b39f8d | Shell | 565 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/117_Cryo_mediso_v:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_117_Cryo_mediso_v_20221024:/rabies_out \
/home/m/mchakrav/desg... |
6a12f4e858c756e13a2e18519634c147ad03b42bd706ecace90855ac384bca62 | Shell | 565 | 20 | #!/bin/bash
latex -interaction=nonstopmode main
bibtex main
latex -interaction=nonstopmode main
latex -interaction=nonstopmode main
latex -interaction=nonstopmode main
latex -interaction=nonstopmode main
pdflatex -interaction=nonstopmode main
latex -interaction=nonstopmode supplement
bibtex supplement
latex -interact... |
c4d29f4ab417c9f0e1507246453c93ac466b307efd143a3b8845097434bef828 | Shell | 565 | 19 | #!/bin/bash
N_THREADS=8
export MKL_NUM_THREADS=$N_THREADS
export NUMEXPR_NUM_THREADS=$N_THREADS
export OMP_NUM_THREADS=$N_THREADS
Sumstat=QC.MetS_noUKB_GWAS.REFORMAT4PRS.GWAS.txt
SampleSize=1252787
OUT=./out;mkdir -p $OUT
ref_1kg_eur=ldblk_1kg_eur
KoGES_bim=KCHIP.snp.imputed.HRC.rsID.rmdup
python3 ../PRScs/PRScs.py ... |
40670a319a0b2d077c7ad5b45252589d4fa7775959bb944fd25dea12a5c1a7c0 | Shell | 567 | 13 | # # polyA
# for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
# # Stringtie assembly for after
# echo samtools index ../results/polyA/$sample/$sample.cleaned.bam &
# samtools index ../results/polyA/$sample/$sample.cleaned.bam &
# done
# ribozero
for sample in R12258 R12260 R1... |
5095398ea67fd12b07564ad2a91840dacd321d98733b4a669eff075c24d85eaf | Shell | 568 | 9 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/bids_grandjean_rest_awk_subset:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/rabies_bids_grandjean_rest_awk_bold_only_subset_20221024:/rabies_out \
/home/m/mchakrav... |
5ae596ce1bc1771f3ef0550c421f39c2ca1a03fd7d4204153672513ac80e4ef2 | Shell | 568 | 18 | #!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license
# Download latest models from https://github.com/ultralytics/assets/releases
# Example usage: bash ultralytics/yolo/data/scripts/download_weights.sh
# parent
# └── weights
# ├── yolov8n.pt ← downloads here
# ├── yolov8s.pt
# └── ...
python - <<EOF
from ul... |
020305162980a800a4172d54d571458b78e78d731e386fce45de26ab21aed16c | Shell | 575 | 11 | #!/bin/bash
#SBATCH --job-name=color_diff
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=5G
#SBATCH --time=00:50:00
conda activate leabra
jupyter nbconvert cross_pair_analysis.ipynb --to python
./main --mode=batch --saveDirName=./figs/test/results_--HiddNumOverlapUnits=5 --runs=2 --trncyclog=false --tstcyclog=false ... |
bea830e4e34826aee505beb272e7a252dfdd28e38e2e8f1908d30fb61616ac19 | Shell | 575 | 10 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
singularity run -B /scratch/m/mchakrav/desgab/data/multicenter/inputs/94_RT_mediso_f2:/nii_inputs:ro \
-B /scratch/m/mchakrav/desgab/data_preprocess/multicenter/rabies_94_RT_mediso_f2_20221024:/rabies_out \
/home/m/mchakrav/desgab/s... |
6f69a2f4cede21f2533b6d99ce68c1a153b80d77670444f012f2d3f7cd0b3a77 | Shell | 577 | 10 | extracted_junc_type="all"
if [ "$extracted_junc_type" == "all" ]; then
project_root=/ccb/cybertron/khchao/splam-analysis-results/
output_dir=${project_root}train/results/ALL_RefSeq/REF_junctions/
sort -k1,1 -k2,2n -k3,3n ${output_dir}ref_d_a_${extracted_junc_type}.bed | uniq > ${output_dir}ref_d_a_${extract... |
afd09ae754ad431812f434c56fa15736fb74e21dd3671b79e6bc12277aa3007b | Shell | 577 | 19 | #!/bin/bash
set -x
IDX=../ref/gencode.vM28.transcripts.fa.fai
for FQZ1 in *_R1_001.fastq.gz ; do
FQZ2=$(echo $FQZ1 | sed 's/_R1_/_R2_/')
echo $FQZ1 $FQZ2
skewer -q 20 -t 16 $FQZ1 $FQZ2
FQT1=$(echo $FQZ1 | sed 's/fastq.gz/fastq-trimmed-pair1.fastq/')
FQT2=$(echo $FQZ1 | sed 's/fastq.gz/fastq-trimmed-pair2.fa... |
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