sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c9b8a21b7ae37c4b2f1221fed016e3197274e67c4ffd8c6d3aeefeb32243f068 | Shell | 1,165 | 43 | #!/bin/bash
#
# Path to the Nextflow processing run configuration file.
#
WORKING_DIR="/net/trapnell/vol1/home/readdf/trapLabDir/hubmap/results/2021_06_07_prelim_DanaRula_BethMethod_nobackup"
CONFIG_FILE="$WORKING_DIR/experiment.config"
#
# Nextflow executable and pipeline script locations.
#
NEXTFLOW="/net/trapnell... |
f22b2123cc428d9706340c86697e0054f84b441ab9c5f37a3ea93868e9af4bac | Shell | 1,165 | 31 | #!/bin/bash
#SBATCH -n 4 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-03:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p serial_requeue # Partition to submit to
#SBATCH --mem=60000 # Memory pool for all cores (... |
f64f6997b1a2018d616d7390a3dee193e0f1c2df6de8373791aad3b9d9a57405 | Shell | 1,167 | 27 | data_path='novartis_acid'
infer_task='novartis_acid'
results_path='novartis_acid_results'
model_path='finetune_save'
head_name='chembl'
conf_size=11
dict_name='dict.txt'
charge_dict_name='dict_charge.txt'
task_num=1
batch_size=16
loss_func="finetune_mse"
nfolds=5
only_polar=-1
for ((fold=0;fold<$nfolds;fold++))
... |
642a4b5369775a733c9998cd403b39f65aaab4840d3255ebe880c97284df8f76 | Shell | 1,168 | 26 | #!/bin/bash
img0_folder=/data/color/cam0_images
img1_folder=/data/color/cam1_images
gps_path=/data/vehicle_pose.txt
row_segmentation=/data/row_segmentation.csv
#row_segmentation=/data/row01.pkl
#weight_dir=/assets/seg_weights/PM_best_checkpoint_ep391.pth
#weight_dir=/media/aux/ignored/dm_new_net_addBN/04112021_053427/b... |
503c51606f8193109565f00b463c7bde0a7fd190dda0ebaf9687761517674b59 | Shell | 1,172 | 27 | data_path='./unimol/examples'
infer_task='fe_example'
results_path='fe_results'
head_name='chembl_small'
conf_size=11
dict_name='dict.txt'
charge_dict_name='dict_charge.txt'
task_num=1
batch_size=16
model_path='dwar_finetune'
loss_func="infer_free_energy"
nfolds=5
only_polar=-1
for ((fold=0;fold<$nfolds;fold++))
... |
0701b8b223b0eb30076f1c57bd2ad7011376c673d08dd04df2ab088ba03d4bf5 | Shell | 1,190 | 24 | #!/bin/bash
ENTITIES="NCBI-disease BC5CDR-disease BC5CDR-chem BC4CHEMD JNLPBA BC2GM linnaeus s800"
MAX_LENGTH=128
for ENTITY in $ENTITIES
do
echo "***** " $ENTITY " Preprocessing Start *****"
DATA_DIR=../datasets/NER/$ENTITY
# Replace tab to space
cat $DATA_DIR/train.tsv | tr '\t' ' ' > $DATA_DIR/train.txt.tmp
c... |
fc02a895a6927baae9d1259c0cf48516e71b4fa06af3f0096c95afc66dc1a0bb | Shell | 1,194 | 26 | #!/usr/bin/bash
dataset=$1
vamb \
--model vaevae \
--outdir /home/projects/cpr_10006/people/svekut/cami2_${dataset}_out \
--fasta /home/projects/cpr_10006/projects/vamb/data/datasets/cami2_${dataset}/contigs_2kbp.fna.gz \
--rpkm /home/projects/cpr_10006/projects/vamb/data/datasets/cami2_${dataset}/abun... |
4e8efdb4a36dbfe66fb028d5caf26ea4fe7f8da02467eaed45d7d20813f9e6ab | Shell | 1,197 | 51 | #!/bin/bash
#SBATCH -J mast_res_all
#SBATCH -N 1
#SBATCH -n 16
#SBATCH -p kellis
#SBATCH --time=48:00:00
#SBATCH --mem=20G
#SBATCH --output=/home/cboix/data/DEVTRAJ/db/out/mast_res_all_%j.log
#SBATCH --export=ALL
#SBATCH --requeue
# -----------------------------------------------------
# Runs of MAST + RE for DG... |
a7750be10fc50990924be5a5f24a790b51d5d074b394e15dd1e1f24995898340 | Shell | 1,200 | 32 | #!/bin/bash -e
if [ $# -ne 2 ]; then
echo "usage v1: srna_signals.sh <bam_file> <chrom_sizes>"
echo "Converts BAMs from alignments from stranded libraries to bigwig format. Is independent of DX and encodeD."
exit -1;
fi
bam_file=$1 # Bam file.
chrom_sizes=$2 # chrom_sizes file that matches the geno... |
f924a2748ed25762e32e3d998f88b8a2ef10326cfc4d3d8495e9f1a498d38134 | Shell | 1,202 | 60 | #!/usr/bin/env bash
# Before running this script, please make sure golang is installed
# and buildifier is also installed. The example is showed in .travis.yml.
set -eo pipefail
ROOT_DIR=$(cd "$(dirname "$0")/$(dirname "$(test -L "$0" && readlink "$0" || echo "/")")"; pwd)
BUILDIFIER="${BUILDIFIER:-buildifier}"
func... |
29bf23b40f50c02fb2d54d2a669a7b1684bb765287bf0df29bbff3ee95419230 | Shell | 1,208 | 39 | #!/bin/bash
if [[ -z "$1" ]] ; then
echo "usage: $0 VARIANT_POS"
exit 1
fi
BAM=HG002.pFDA_r941g360.grch38_chr1.mvp-pdv-filtfix2-rle.haplotagged.bam
TRUTH_H1=/home/tpesout/work/marginPolish/phasingData/haplotagged/200527_HG002_trio-binned-miten/HG002_haplotype-HG003_ids.fixed.txt
TRUTH_H2=/home/tpesout/work/marginPo... |
d86e0f270db72aaad0bdf65944315789ddf8c6c9fc13278624f1831b7e692f82 | Shell | 1,209 | 49 | #!/bin/bash
#SBATCH -J psbulk_deseq2
#SBATCH -N 1
#SBATCH -n 8
#SBATCH -p kellis
#SBATCH --time=3:00:00
#SBATCH --mem=30G
#SBATCH --output=/home/cboix/data/DEVTRAJ/db/out/psbulk_deseq2_%j.log
#SBATCH --export=ALL
#SBATCH --requeue
#SBATCH --array=1-668
# Run as:
# sbatch --array=1-668 $SBINDIR/differential_expr... |
4301503aeb4da5888ed5d423ee8d31db47b8ddbd5c6ad74a66f72dffeb10af71 | Shell | 1,210 | 17 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
echo mkdir ../results/polyA/$sample/intron_matcher/AFTER/
mkdir ../results/polyA/$sample/intron_matcher/AFTER/
echo ../../Intron-Matcher/build/intron_matcher -G ../Dataset/hg38.ncbiRefSeq.gtf -o ../results/polyA/$sample/... |
8c63965839f05c2dde2957b64c68f4b96a81087b988db7a776234ae250815878 | Shell | 1,211 | 27 | #!/bin/bash
# Purpose: Create a new feat file with the clean data. This script will create the individual design files.
# Create a list of subjects to use in this analysis and count how many there are.
subject_dir=/nfs/turbo/lsa-csmonk/FF_Data/Working_Files/Resting/GIMME/Subjects
subjectlist=$(cd ${subject_dir}; ls ... |
f548dd2dbf33649fa9c6bb76c9942bdbeb3e2cf9f09f767d2ebb804686b4eba7 | Shell | 1,211 | 35 | #!/usr/bin/env bash
# SETUP EXPERIMENT DIRECTORIES ----------------------------------------------
# Prepare experiment directories with necessary input files for DeepRVAT running
# Replace `[path_to_deeprvat]` with the path to your clone of the repository.
# Activate your virt-env before running script. i.e. $ mamba a... |
cebb756cafad830c956cc9d6b41bac05d08e1549bd61b5216d38278d3aab2e0e | Shell | 1,216 | 29 | #!/bin/bash
####################### FF Feat Script ##############################
# Purpose: Create individual feat design files for FF subjects.
# Create a list of subjects to use in this analysis and count how many there are.
subject_dir=/nfs/turbo/lsa-csmonk/FF_Data/Working_Files/Resting/GIMME/Subjects
subjectli... |
fcd690b1eb29e737a46d35f417b829f8d5b4f3de6b763082f39b31c99aef0f2a | Shell | 1,217 | 33 | #!/usr/bin/env bash
# Where are the projects
PROJECTS_DIR=$1
if [ -z "$PROJECTS_DIR" ]
then
echo "Please provide the path to the Projects directory"
exit 1
fi
# Generate flagstats.txt inside of each project
for p in ${PROJECTS_DIR}/*; do sn=$(basename $p); samtools flagstat ${p}/${sn}.bam > ${p}/flagstats.txt... |
bf505acf2b998cab334bad86e35616e6a897296e1537689eafd9f80ba44901a9 | Shell | 1,218 | 41 | #!/usr/bin/env sh
#PBS -A mnh5174_c_g_sc_default
#PBS -l nodes=1:ppn=20
#PBS -l walltime=72:00:00
#PBS -l pmem=8gb
#PBS -j oe
#PBS -M michael.hallquist@psu.edu
#PBS -m n
export G=/gpfs/group/mnh5174/default
module use $G/sw/modules
ni_tools="$G/lab_resources"
#location of MRI template directory for preprocessing
M... |
27cb04bd10cbfd13b9d7e20b3e4065965e613c3a5e39f322451da0e05416b34b | Shell | 1,224 | 49 | #!/bin/bash
#SBATCH -J mastwx_res
#SBATCH -N 1
#SBATCH -n 32
#SBATCH -p kellis
#SBATCH --time=48:00:00
#SBATCH --mem=90G
#SBATCH --output=/home/cboix/data/DEVTRAJ/db/out/mastwx_res_%j.log
#SBATCH --export=ALL
#SBATCH --requeue
#SBATCH --array=2-668
# Run as:
# sbatch --time=48:00:00 --array=2-139 $SBINDIR/diffe... |
60db539cda8ada0a8e7a2174b00585223e229ccc235b837249b3c082523c2524 | Shell | 1,224 | 31 | #!/usr/bin/bash
folder=$(awk -v var="$PBS_ARRAYID" 'NR==var {print; exit}' /home/projects/cpr_10006/people/svekut/almeida_N_samples/folder_list_1.txt)
# vamb bin default \
# --outdir /home/projects/cpr_10006/people/svekut/almeida_N_samples/data_folders/${folder}/vambout \
# --fasta /home/projects/cpr_10006/peo... |
43b01b34ded08c04566fe1660bd32382661f2cf301e5bc96adf77e26b973bbfa | Shell | 1,225 | 31 | #!/usr/bin/bash
folder=$(awk -v var="$PBS_ARRAYID" 'NR==var {print; exit}' /home/projects/cpr_10006/people/svekut/almeida_N_samples/folder_list_10.txt)
# vamb bin default \
# --outdir /home/projects/cpr_10006/people/svekut/almeida_N_samples/data_folders/${folder}/vambout \
# --fasta /home/projects/cpr_10006/pe... |
bca1a2958e6b4eeb6a08dec9b0c4ab54e00826410910ebd45f9ceb2380cfdd2f | Shell | 1,226 | 31 | #!/usr/bin/bash
folder=$(awk -v var="$PBS_ARRAYID" 'NR==var {print; exit}' /home/projects/cpr_10006/people/svekut/almeida_N_samples/folder_list_100.txt)
# vamb bin default \
# --outdir /home/projects/cpr_10006/people/svekut/almeida_N_samples/data_folders/${folder}/vambout \
# --fasta /home/projects/cpr_10006/p... |
28785f10b56e62baf95d2dd1a2afd27ada5622bc74b9d9e42fd678307cff031a | Shell | 1,229 | 34 | #!/bin/bash
source 00_global_variables.sh
saveto_parent=./LDSC_SEG_analysis
mkdir -p $saveto_parent
cts_Cahoy=../Cahoy.ldcts
cts_Multi_tissue_gene_expr=../Multi_tissue_gene_expr.ldcts
cts_Multi_tissue_chromatin=../Multi_tissue_chromatin.ldcts
cts_GTEx_brain=../GTEx_brain.ldcts
cts_ImmGen=../ImmGen.ldcts
cts_Corces_AT... |
4620a7747be953daf8322faf65e1d1656786a1dca438e45c4b2019fea40bd1be | Shell | 1,229 | 29 | #!/usr/bin/bash
annotator=$1
thres=$2
vamb \
--model vaevae \
--outdir /home/projects/cpr_10006/people/svekut/almeida10_${annotator}_fix \
--fasta /home/projects/cpr_10006/people/paupie/vaevae/almeida_10_samples/03_abundances/abundances/contigs.flt.fna.gz \
--rpkm /home/projects/cpr_10006/people/paupie... |
d5deb05cfdba4aaf206b5caddcc88900d16c50df6a993c7d21e450337b1de653 | Shell | 1,229 | 34 | #!/bin/bash
folder_name=${1%/}
#read the last line of the log, get job IX
log_name=$folder_name/status.csv
last_line=$(tac $log_name |egrep -m 1 .)
IFS=',' read -ra ADDR <<< "$last_line"
job_ID=${ADDR[4]}
UpdateLog.sh $folder_name zip_data $job_ID START Zipping_Data_And_Deleting_Raw_Images
#get how many img files a... |
1b5ffc9ea1530a206f4669249d70d9e85ec0086224bffbd92e3a92ee3ba09e17 | Shell | 1,230 | 29 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=1:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 #... |
aeef8973fcf2039658574becee1c841cf7e9dcb06c949b216db7256ffbd54e5f | Shell | 1,230 | 34 | #!/bin/bash
#$ -S /bin/bash
#$ -N ann
#$ -cwd
#$ -o /mnt/analysis-psp/users/timchang/v3/pc/2211/data/vcfs/bm/eur/none/annovar/ann.$TASK_ID.log
#$ -j y
#$ -m bea
#$ -l h_data=12G,h_rt=48:00:00
#$ -hold_jid remSamp
#$ -t 1:22
#remove Variants from list
chr=($(seq 1 1 22) X Y M)
echo ${chr[${SGE_TASK_ID}-1]}
indir=/mn... |
7e90510e6b4795f929cd40a82072c22f41ed2b15245e99b3fdbacca133861a22 | Shell | 1,232 | 40 | makesd_exp_m6A2ha(){
for tis in Brain Lung Muscle Heart; do for n in `seq 22`; do Rscript makesd_exp.R $tis $n m6A ha; done; done
}
makesd_exp_m6A2me(){
for tis in Lung Muscle; do for n in `seq 22`; do Rscript makesd_exp.R $tis $n m6A me; done; done
}
makesd_exp_ha2m6A(){
for tis in Brain Lung Muscle... |
373e1b0cdc035932cdb98406c26f7f27a263e8107984c996d9c8a3858b2c8b40 | Shell | 1,233 | 43 | #!/bin/bash
# usage: run-graphprot2.sh <positive.fa> <negative.fa> <test.fa> <outdir>
set -eu
function realpath { echo $(cd $(dirname $1); pwd)/$(basename $1); }
P_fa=`realpath $1`
N_fa=`realpath $2`
T_fa=`realpath $3`
OUTDIR=`realpath $4`
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
mkdir... |
e1ab129c16e4dff96c20a14fd9ffb7f09a568223da147e5d8fe0ff0d7a145d95 | Shell | 1,233 | 25 | #!/usr/bin/bash
# vamb \
# --outdir /home/projects/cpr_10006/projects/semi_vamb/data/sludge/vambout64_20102023 \
# --fasta /home/projects/cpr_10006/projects/semi_vamb/data/sludge/contigs_2kbp.fna \
# --rpkm /home/projects/cpr_10006/projects/semi_vamb/data/sludge/vambout/abundance.npz \
# -l 64 \
# ... |
93fb1c139a2615389a1ae0876906cd6302749b0970807651a6ed49a2c62aa157 | Shell | 1,238 | 41 | #!/bin/bash
###############################################################
## Convert all ERA5 input data files to 128x64 lonxlat grids ##
###############################################################
proj_dir="/path/to/main_project_folder/" # edit this line
regions=('southcentral_north_america' 'southern_europe'... |
90c35c7a067c11ae0365447a3e219ef6e123da3deac7c02330078a2afa32b0ce | Shell | 1,240 | 32 | #!/bin/bash -e
if [ $# -ne 2 ]; then
echo "usage v1: lrna_bam_to_stranded_signals.sh <bam_file> <chrom_sizes>"
echo "Converts BAMs from alignments from stranded libraries to bigwig format. Is independent of DX and encodeD."
exit -1;
fi
bam_file=$1 # Bam file.
chrom_sizes=$2 # chrom_sizes file that ... |
95f183795495c805685f6fd5b7087941e6249cf153382f61a31143fb29b2b1f8 | Shell | 1,241 | 49 | #!/bin/bash
#SBATCH -J nb_res
#SBATCH -N 1
#SBATCH -n 32
#SBATCH -p kellis
#SBATCH --time=24:00:00
#SBATCH --mem=90G
#SBATCH --output=/home/cboix/data/DEVTRAJ/db/out/nebula_res_%j.log
#SBATCH --export=ALL
#SBATCH --requeue
#SBATCH --array=1-668
# Run as:
# sbatch --time=72:00:00 --array=2-139 $SBINDIR/different... |
df32fc8ad21cccc8907f8f28fa0ce6c058476f950ecb9b7e6eff499741d906ba | Shell | 1,241 | 25 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=5:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 #... |
1083b131b5c2ebb8ced5e061f8dd868231334e8d69b9b9580b99848282e2fa72 | Shell | 1,242 | 25 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=00:10:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 ... |
472f98e7388ae7a2a3c61b97db5b7733035482a7cbe5de4a5d5504743cee0c11 | Shell | 1,243 | 33 | #!/bin/bash
#SBATCH -n 4 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-01:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p serial_requeue # Partition to submit to
#SBATCH --mem=30000 # Memory pool for all cores (... |
8bf72ae2f4e3e335ec777677a1baac0000245041e27f9cfc9cfddeb8cff85fa8 | Shell | 1,244 | 33 | #!/usr/bin/bash
# folder=$(awk -v var="$PBS_ARRAYID" 'NR==var {print; exit}' /home/projects/cpr_10006/people/svekut/almeida_N_samples/folder_list_100.txt)
folder='3_100'
# vamb bin default \
# --outdir /home/projects/cpr_10006/people/svekut/almeida_N_samples/data_folders/${folder}/vambout \
# --fasta /home/pr... |
995b017d502dca64f2691621c8e3fe704956994389aff77404cbb3aefd22e286 | Shell | 1,244 | 10 | #!/bin/tcsh -f
# Extracts the clusters for each individual subject.
# This is for phonological neighborhood density -- sub-brik [6] for betas, [7] for t-stat
set top_dir = top_dir/
foreach subject(S0056INA1 S0105LIA1 S0125HAN1 S0162JRG1 S0212QLT1 S0313QWR1 S0522GSR1 S0706OPY1 S0717JHH1 S0734IDQ1 S0776SSB1 S0835TAV1 ... |
33ca267d4cc0b229a6ee5c05e3bad69cd16be9d0e7130d2d6e9e20467f54cb77 | Shell | 1,246 | 57 | #!/bin/bash
# Build, test and push cebra container.
set -e
# Parse command line arguments
RUN_FULL_TESTS=false
while [[ $# -gt 0 ]]; do
case $1 in
--full-tests)
RUN_FULL_TESTS=true
shift
;;
*)
echo "Unknown option: $1"
exit 1
;;
esac
done
if [[ -z $(git status --porcel... |
32f514359e3980e788de03ffee22efee558be11d7d6fadfb924badbd1118361d | Shell | 1,254 | 33 | #!/bin/bash
# Set the root directory where sub-* directories are located
root_dir="/ZPOOL/data/projects/SRPAL-DataInBrief/bids"
# Loop through each subject directory (sub-*) in the root directory
for subject_dir in "$root_dir"/sub-*; do
if [ -d "$subject_dir" ]; then
echo "Processing directory: $subject_d... |
8b06512e918560ce0739fd21e5f8982f4234702a546aff5446b85a3b29d5db8d | Shell | 1,257 | 31 | #!/bin/bash
#######################################################
## create empty directories for processed data files ##
#######################################################
proj_dir="/path/to/main_project_folder/" # edit this line
regions=('southcentral_north_america' 'southern_europe' 'western_russia' 'weste... |
4533c6249ecf25c367901a98e23d3edcbb62cfa441ea9be2b8be08350a09bd3d | Shell | 1,260 | 50 | #!/bin/bash
#SBATCH --job-name=allen-video-features
#SBATCH --error=logs/allen-video-%j-%A-%a.err
#SBATCH --output=logs/allen-video-%j-%A-%a.out
#SBATCH --nodes=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=50G
#SBATCH --gres=gpu:1
#SBATCH --time=01:00:00
DATADIR=allen_movies/movies
params=( $(cat mis... |
f26ace70fe5bebc9e1967e4f18c183e5602175ba07cea04feba57e85ea97958c | Shell | 1,264 | 65 | #!/bin/bash
# Shard VCF into sequential, evenly-sized splits
###USAGE
usage(){
cat <<EOF
usage: shard_VCF.sh [-h] VCF LINES PREFIX
Shard a VCF into sequential, evenly-sized splits
Positional arguments:
VCF VCF from sv-pipeline
LINES Number of records per shard
PREFIX Output pr... |
d1ea0bf25f6c12467daf78372e3157d5941e2a046a63b221dcacb9bfb2385833 | Shell | 1,270 | 28 | #!/usr/bin/bash
thres=$1
vamb bin taxvamb \
--outdir /home/projects/cpr_10006/projects/vamb/almeida_vaevaeout_predictor_${thres}_mem \
--fasta /home/projects/cpr_10006/projects/vamb/analysis/almeida/data/almeida.fna \
--rpkm /home/projects/cpr_10006/projects/vamb/analysis/almeida/data/almeida.jgi.depth.npz... |
43870e80ba25bc3a418f5787916d7dbd134f0b34abf779e215bae4be0aff2a7a | Shell | 1,271 | 33 | #!/bin/bash
##################### Coverage Check Script ################################
# Purpose: This QC script calculates the individual coverage rates for all included masks and writes it out to a csv file.
# Create subject list.
subject_dir=/nfs/turbo/lsa-csmonk/FF_Data/Working_Files/Resting/GIMME/Subjects
sub... |
6ccd3e0d4a74e89231e63580ccbf9c0c46e93a8256708175358ac95fb4f8e1d7 | Shell | 1,276 | 24 | #!/usr/bin/bash
dataset=$1
run_id=$2
# --taxonomy_predictions /home/projects/cpr_10006/people/svekut/cami2_${dataset}_reassembled_1/results_taxonomy_predictor.csv \
# vamb \
# --model vae \
# --outdir /home/projects/cpr_10006/people/svekut/cami2_${dataset}_vamb_${run_id} \
# --fasta /home/projects/cpr_... |
78c231e9bd70462ab452ebef84cae2490f9992d3d0cb53e01ef243646dfbc8b5 | Shell | 1,276 | 40 | #!/bin/bash
# concat-fastqs.sh
main() {
# If available, will print tool versions to stderr and json string to stdout
versions=''
if [ -f /usr/bin/tool_versions.py ]; then
versions=`tool_versions.py --dxjson dnanexus-executable.json`
fi
echo "* Concat id: '${concat_id}'"
#echo "* Value... |
20ce43dd133d3393a269bb85ca76beb8930411dde2dfa9ce561d3313d0766642 | Shell | 1,279 | 27 | #!/usr/bin/bash
# --taxonomy /home/projects/cpr_10006/people/paupie/vaevae/mmseq2_annotations/long_read_sludge/lr_sludge_taxonomy.tsv \
vamb \
--model vaevae \
--outdir /home/projects/cpr_10006/projects/semi_vamb/data/sludge/vaevaeout \
--fasta /home/projects/cpr_10006/projects/semi_vamb/data/sludge/conti... |
c0673ff1468b540ba5c9a78f1f87e64805af0c09da4d35b247412321398887b6 | Shell | 1,280 | 26 | #!/bin/bash
#build STAR indexes for mm10 from ensemble
#https://leonjessen.wordpress.com/2014/12/01/how-do-i-create-star-indices-using-the-newest-grch38-version-of-the-human-genome/
#get fasta files mm10:
#tp://ftp.ensembl.org/pub/release-92/fasta/mus_musculus/dna/
mkdir -p STAR_libs/mm10/sequence
cd STAR_libs/mm10/s... |
8c4c14a2318246f7d6353dcb58cf43b86193835f7da4c9560be73600a5573d1c | Shell | 1,289 | 45 | #!/bin/bash
# usage: run-graphprot.sh <positive.fa> <negative.fa> <test.fa> <outdir>
function realpath { echo $(cd $(dirname $1); pwd)/$(basename $1); }
P_fa=`realpath $1`
N_fa=`realpath $2`
T_fa=`realpath $3`
OUTDIR=`realpath $4`
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
set -eu
mkdir -p... |
3e0db124c5e01e4873948ab1ce6cd98e5c94fe677344d94ff067cf88d7c63507 | Shell | 1,293 | 25 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
mkdir ../results/polyA/$sample/gffcompare/
mkdir ../results/polyA/$sample/gffcompare/chess/
mkdir ../results/polyA/$sample/gffcompare/chess/BEFORE
mkdir ../results/polyA/$sample/gffcompare/chess/AFTER
gffcompare... |
cd960d040a19fc84d3b751ad23c44afca1530b01751ee25f3e992876dc1e735b | Shell | 1,296 | 33 | #!/bin/bash
set -e
i=$1
j=$2
freqmin=$3
freqmax=$4
awk -v var=$i -v freqmin=$freqmin -v freqmax=$freqmax '{if ($4>=var && $2<=freqmax && $2>freqmin) print }' recover.single.txt >one.$i.$j.$freqmin.$freqmax.txt
awk -v var=$j -v freqmin=$freqmin -v freqmax=$freqmax '{if ($4>=var && $2<=freqmax && $2>freqmin) print }... |
28cbe86aac06c051868a169ef48397f929fd5664e9b72d84051b4e18dfb3ff32 | Shell | 1,303 | 24 | #!/usr/bin/bash
# vamb \
# --outdir /home/projects/cpr_10006/projects/semi_vamb/data/human_longread/vambout64_20102023 \
# --fasta /home/projects/cpr_10006/projects/semi_vamb/data/human_longread/contigs_2kbp.fna \
# --rpkm /home/projects/cpr_10006/projects/semi_vamb/data/human_longread/vambout/abundance.np... |
ec6e36d34b67fc2f9477b897ff1ab7cbebf3b448b40c0e5c7fb62646d238e2e4 | Shell | 1,308 | 55 | #!/bin/bash
# Fit Spherical Mean Technique
# usage:
# bash smt_fit.sh pathFolderIn pathFolderOut inputFilesBasename
# By Ricardo Coronado-Leija
# print date, command
now=$(date +%Y-%m-%d-%H-%M-%S)
echo $now
# print command
echo $*
# ================================================================================... |
f3a752053527f9e8079f89268db1e6ef34e064a6d47d6888c903bed00185c2fb | Shell | 1,310 | 39 | #!/bin/bash
#$ -S /bin/bash
#$ -N normann
#$ -cwd
#$ -o /mnt/analysis-psp/users/timchang/v3/pa/2211/data/vcfs/bi/norm/id.$TASK_ID.log
#$ -j y
#$ -m bea
#$ -l h_data=2G,h_rt=72:00:00
#$ -tc 10
#$ -hold_jid bcf_pass
#$ -t 1:22
#psp con samples only
#keep min-ac =1
#filter for qual = pass only
#normalize indel only. no m... |
c02a5d0f43d74c22d621f403be394efadfa4bacdb2cdbbf64c0beeffa6419a47 | Shell | 1,315 | 35 | # prepare genomes for STAR and RSEM
# input parameters:
STARgenomeDir=$1 #STAR genome directory
RSEMgenomeDir=$2 #RSEM genome directory
fastaGenome=$3 #fasta file(s), e.g. "male.hg19.fa"
fastaSpikeins=$4 #fasta file with spike-ins, e.g. "spikes.fixed.fasta"
gtf=$5 #all-inclusive gtf file "gencode.v19.annot... |
0d13608855b2b94d330f9120696f4ae60eb8f0558067170bddb928ae87da4ef6 | Shell | 1,324 | 41 | #!/bin/bash
wget -O models/first_stage_models/kl-f4/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f4.zip
wget -O models/first_stage_models/kl-f8/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f8.zip
wget -O models/first_stage_models/kl-f16/model.zip https://ommer-lab.com/files/latent-diffusion/kl... |
4265dd4a935e664b9de2b09d88d05236c1d1eb1cfac5d2319c3a0016ec76902e | Shell | 1,325 | 17 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
echo mkdir ../results/polyA_STAR/$sample.bamAligned.sortedByCoord.out/assembly/AFTER/
mkdir ../results/polyA_STAR/$sample.bamAligned.sortedByCoord.out/assembly/AFTER/
echo stringtie -o ../results/polyA_STAR/$sample.b... |
852691eabd2ba7bac8964e2e4352203764a23704de7d88a2a562ae907429c0b2 | Shell | 1,326 | 46 | #!/bin/bash
N_THREADS=8
export MKL_NUM_THREADS=$N_THREADS
export NUMEXPR_NUM_THREADS=$N_THREADS
export OMP_NUM_THREADS=$N_THREADS
Sumstat=MetS_noUKB_F1_GWAS.REFORMAT4PRS.GWAS.txt
SampleSize=279429
ref_1kg_eur=../ldblk_1kg_eur
UKB_bim=../ukb_eur_unrel_comb
OUT=./out_F1
mkdir -p ${OUT}
python3 ../PRScs/PRScs.py --ref_... |
a1b16c21712a95a1b2f4fc2516cb0af35f0984d8e70dacf40d06674fe2e7d9af | Shell | 1,331 | 51 | #!/bin/sh
#
# Script to submit jobs to cluster to perform NBS for comparing RSFC between all ASD & all controls in ABIDE-I
#
# Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
tThresh=$1
id_asd=$2
id_con=$3
sub_info_file=$4
Nperm=$5
output_name=$6
output_dir... |
fb7dc066173cb3a18057dd4da78e7c9cdedb4ecb944863fb692690e8c0c70bb6 | Shell | 1,337 | 37 | #!/bin/bash
############################### FAST loop script ###################################
# Purpose: Runs FAST
# Create a list of subjects to use in this analysis and count how many there are.
subject_dir=/nfs/turbo/lsa-csmonk/FF_Data/Working_Files/Resting/GIMME/Subjects/
subjectlist=$(cd ${subject_dir}; ls ... |
eb8325128501f3203599186524c6f39340789bdb7aaf15ce8737537332404a8d | Shell | 1,345 | 46 | #!/bin/bash
N_THREADS=8
export MKL_NUM_THREADS=$N_THREADS
export NUMEXPR_NUM_THREADS=$N_THREADS
export OMP_NUM_THREADS=$N_THREADS
Sumstat=MetS_noUKB_F1_GWAS.REFORMAT4PRS.GWAS.txt
SampleSize=279429
ref_1kg_eur=../ldblk_1kg_eur
KoGES_bim=KCHIP.snp.imputed.HRC.rsID.rmdup
OUT=./out_F1
mkdir -p ${OUT}
python3 ../PRScs/PR... |
8f69afe8c28a728d2d558ef90170bce121da46ae5bc1d2ec6ba8a7d22719e857 | Shell | 1,347 | 40 | # run_kallisto_1sample <input_RNASEQ_rawdir> <sample> <input_ref_name_idx> <output_dir>
run_kallisto_1sample(){
source activate sqanti2_py3
# variables
input_dir=$1
sample=$2
input_ref_name=$3
output_dir=$4
# cd to $J20/Tg4510_input_directory
cd $input_dir
echo "Finding reads f... |
9e745f6f864f607cfcc6c51894f01f95e1804a0830125618714fc4b246ad856b | Shell | 1,354 | 26 | #!/bin/bash
#SBATCH -n 4 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-08:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared # Partition to submit to
#SBATCH --mem=72000 # Memory pool for all cores (see also... |
aead01de0cf41d6ebd946458f6030173bff9959624d2b663bd610ff44780bcd7 | Shell | 1,354 | 12 | #!/bin/tcsh -f
# Extracts the clusters for each individual subject.
# This is for lexical frequency -- sub-brik [4] for betas, [5] for t-stat
# phonological neighborhood desnity is [6] for betas, [7] for t-stat
set top_dir = top_dir/
foreach subject(S0056INA1 S0105LIA1 S0125HAN1 S0162JRG1 S0212QLT1 S0313QWR1 S0522GS... |
de2c4c887553dff941285ac609eae18e08c38f460f66d6bd3bcb4a716cc160e3 | Shell | 1,365 | 35 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=1:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 #... |
1a0fe166e3ac9a7cb4b194c2f89c0ef279c51d35f3cb5376c6557ffa646bd99e | Shell | 1,368 | 25 | ####################################################################################################
# Copyright (c) 2023 - 2024 Marwan Abdellah < abdellah.marwan@gmail.com >
#
# This file is part of OMesh, the OptimizationMesh library.
#
# This program is free software: you can redistribute it and/or modify it under t... |
0ba4a6a9e4c36e35fcde9961112ed55cdb2003ab5001deb4bb0678caf30e7c7c | Shell | 1,369 | 37 | #! /usr/bin/env bash
# compiles all
function usage() {
echo "usage: `basename $0` <Matlab Compiler>"
}
if [ $# -eq 1 ]; then
MCC_FILE="$1"
fi
if [ ! -e $MCC_FILE ]; then
echo "unable to locate matlab compiler"
usage
exit 1
fi
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
# set ... |
0ed61415957b0179d150ed1b5394121de491bac741d84c543962d0fb433c3fa1 | Shell | 1,373 | 25 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
mkdir ../results/polyA/$sample/gffcompare/
mkdir ../results/polyA/$sample/gffcompare/refseq_ucsc/
mkdir ../results/polyA/$sample/gffcompare/refseq_ucsc/BEFORE
mkdir ../results/polyA/$sample/gffcompare/refseq_ucsc/AFT... |
32290c197d8e5d90c5477928d4cf79271c9dc399b657c66536819030a1fb8085 | Shell | 1,378 | 38 | #!/bin/bash
#SBATCH -J DelSwitch
#SBATCH -p high
#SBATCH --exclude=node0[19-21,25]
#SBATCH --gres=gpu:1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=32G
#SBATCH --array=0-20
#SBATCH -o /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.out
#SBATCH -e /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.... |
63d601e09abe32e86a643e67106bd86bad55c93ddf0d2b4cc7e55674b87a2f97 | Shell | 1,379 | 43 | #!/bin/bash
set -e
DATASET_ROOT="/your/path/to/BOLDMomentsDataset"
TMP="/your/path/to/tmp_directory"
WORK="$TMP/tmp/BMD-workdir"
FMRIPREP_VERSION="23.2.0"
USERNAME=yourusername
#to deal with permission issues that can arise when creating folders in docker
su $USERNAME -c "mkdir -p $DATASET_ROOT/derivatives/versionB"
s... |
759933557bdb7479481ce2d9dda3afc8629ab008403c645c9e05ee0a599aa126 | Shell | 1,379 | 40 | #!/usr/bin/env bash
#
# Trains DROID-RV for one epoch on the sample data in ./test_data, to demonstrate
# the training recipe end to end. Run from model_zoo/DROID-RV/ inside the DROID
# docker image (see README.md for setup):
#
# docker run -it -v {PATH TO CLONED ML4H DIRECTORY}:/ml4h/ alalusim/droid:latest
# cd /m... |
93f9a1f90cfb82a0e2fa0906c56c6f81c99eb21e64c0c19707e8b50f9a5c10c3 | Shell | 1,379 | 62 | #!/bin/bash
SECONDS=0
echo "Launching Metamap recognizer..."
cd /root/vsc/hnfc-dataset-agent/
if ls ./data/metamap_sent/*.xml 1>/dev/null 2>&1;
then
rm ./data/metamap_sent/*.xml;
fi
if ls ./data/metamap_sent/*.json 1>/dev/null 2>&1;
then
rm ./data/metamap_sent/*.json;
fi
if ls ./data/metamap_sent/*.txt... |
3b0ea5f42334eeb8cdc669bbe7e6351cfbbff63ed9cff3784291c65c8ec37a36 | Shell | 1,382 | 38 | #!/bin/bash
#SBATCH -J DelSwitch
#SBATCH -p high
#SBATCH --exclude=node0[19-21,25]
#SBATCH --gres=gpu:1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=32G
#SBATCH --array=0-20
#SBATCH -o /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.out
#SBATCH -e /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.... |
370b3cf0b57896279baf555ca6218a325fce81e52d10fc5037261c7f51577f44 | Shell | 1,384 | 38 | #!/bin/bash
#SBATCH -J DelSwitch
#SBATCH -p high
#SBATCH --exclude=node0[19-21,25]
#SBATCH --gres=gpu:1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=32G
#SBATCH --array=0-20
#SBATCH -o /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.out
#SBATCH -e /homedtic/gjimenez/DADES/DADES/Delineator/Logs/%A-%a.... |
bb344f376add12e6c44325b2f8e9a8c69729bcd1e8f1963c0f4ade6b11371b77 | Shell | 1,385 | 25 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
mkdir ../results/polyA/$sample/gffcompare/
mkdir ../results/polyA/$sample/gffcompare/gencode/
mkdir ../results/polyA/$sample/gffcompare/gencode/BEFORE
mkdir ../results/polyA/$sample/gffcompare/gencode/AFTER
gffc... |
0f20b2dc6ba65abac8a209ab7d34d7dc91bd43fccb6676636bcd46fb7f3bfebf | Shell | 1,387 | 45 | #!/bin/bash
# shellcheck disable=SC2206
#SBATCH --job-name=test
#SBATCH --cpus-per-task=5
#SBATCH --mem-per-cpu=1GB
#SBATCH --nodes=4
#SBATCH --tasks-per-node=1
#SBATCH --time=00:30:00
set -x
# __doc_head_address_start__
# Getting the node names
nodes=$(scontrol show hostnames "$SLURM_JOB_NODELIST")
nodes_array=($no... |
b7181deeac88dd5cf457850558c82529dc51dbce4f2a460a15b612c1cb4d7eca | Shell | 1,388 | 29 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=20:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 ... |
59368870323d80b500143a615b81fa18dc10ca554e3df8bd0df86c86dcf0dddc | Shell | 1,393 | 31 | #!/usr/bin/bash
annotator=$1
thres=$2
# vamb \
# --model vaevae \
# --outdir /home/projects/cpr_10006/people/svekut/almeida10_${annotator}_predictor_${thres}_fix \
# --fasta /home/projects/cpr_10006/people/paupie/vaevae/almeida_10_samples/03_abundances/abundances/contigs.flt.fna.gz \
# --rpkm /home/pro... |
3d9156ab8d3fcad7f1ab58cc7ecf03552ee6d24ed8b000d16162a7d0c9d5c764 | Shell | 1,397 | 39 | #!/bin/bash
IMAGE="1.7.0"
if [ $# -eq 0 ]
then
echo "Please Specify the release tag (i.e. 1.7.0)"
exit 1
fi
while [[ $# -gt 0 ]]
do
key="$1"
case $key in
--release-tag)
shift
IMAGE=$1
;;
*)
echo "Usage: fix-docker-latest.sh --release-tag <TAG>"
exit 1
esac
shift
done
ASSUME_ROLE_CREDENTI... |
1684e88baeaa2ee9cc0f3545a51479386405b77e13d21d1df10c2f136827145b | Shell | 1,399 | 13 | #!/bin/csh -f
# Extracts the individual overlap cluster by participant - area in the cerebellum where there was (at an invididual level) spatial overlap
# of sensitivity to lexical frequency and phonological neighborhood density
# The cluster is indicated by a value of '3' so we want to extract voxels for each partici... |
1163dc639e3caae5148e239aff9330d81076c2956319a212b3f6582d7b9b63f7 | Shell | 1,404 | 36 | #!/usr/bin/env bash
# SETUP EXPERIMENT DIRECTORIES --------------------------------------------
# Prepare experiment directories with necessary input files for DeepRVAT running
# Replace `[path_to_deeprvat]` with the path to your clone of the repository.
# Activate your virt-env before running script. i.e. $ mamba ac... |
60abb2c8aa02744ac82c1894902822a3da7be841c53a4bb4a04779be7718bb58 | Shell | 1,404 | 23 | # polyA
for sample in R2826 R2835 R2839 R2845 R2855 R2857 R2869 R2874 R2894 R2895 ; do
echo mkdir ../results/polyA/$sample/intron_matcher
mkdir ../results/polyA/$sample/intron_matcher
echo mkdir ../results/polyA/$sample/intron_matcher/BEFORE/
mkdir ../results/polyA/$sample/intron_matcher/BEFORE/
e... |
5c5c926c87442997f120228b4819ed06d0c748fc50bb4ed836bddab84a9ed881 | Shell | 1,405 | 28 | #!/usr/bin/bash
dataset=$1
# --taxonomy /home/projects/cpr_10006/people/svekut/mmseq2/${dataset}_taxonomy_2023.tsv \
# --taxonomy_predictions /home/projects/cpr_10006/people/svekut/cami2_urog_out_32_667/results_taxonomy_predictor.csv
# --taxonomy /home/projects/cpr_10006/people/svekut/mmseq2/${dataset}_tax... |
594fc60253d7a97c312c9072d591709344f82dec18f5909b38b6fd9dad3083dd | Shell | 1,406 | 42 | #!/bin/bash
#SBATCH --account=hai_cellnet
#SBATCH --nodes=1
#SBATCH --output=slurm_out/out.%j
#SBATCH --error=slurm_out/err.%j
#SBATCH --time=24:00:00
#SBATCH --partition=booster
#SBATCH --gres=gpu:4
cd ~/"$USER" || exit
# load modules
ml purge
ml Stages/2023
ml GCC/11.3.0
ml OpenMPI/4.1.4
ml CUDA/11.7
ml cuDNN/8.6.0... |
9920aae8b25672fb68afe5f0aac85d81a4fac26c4f375bab7b32013e424814e9 | Shell | 1,407 | 36 | #!/bin/bash
#SBATCH -n 1 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-04:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared # Partition to submit to
#SBATCH --mem=16G # Memory pool for all cores (see also -... |
60bbdab89f6b7c964de356efcbb8b603cd7582a80eaefe8630c8e394ed384480 | Shell | 1,419 | 55 | #!/bin/sh
#
# Script to submit jobs to cluster to perform NBS for comparing RSFC between ASD & controls in subgroups
#
# Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
tThresh=$1
id_asd_subgrp=$2
id_con_subgrp=$3
id_asd=$4
id_con=$5
sub_info_file=$6
Nperm=$... |
d5e73c67a98aee3aa91574116b409907fff4c135a68a90c4d2b35f782841a417 | Shell | 1,419 | 52 | #!/bin/bash
# usage: ./data_preparation.sh train.positive.fa train.negative.fa test.fa train.gz test.gz
# Check if exactly five arguments are provided
if [ "$#" -ne 5 ]; then
echo "Five arguments required"
exit 1
fi
min_len=99
{
# Process Positive sequences
while read -r header; do
read -r seq
... |
bf84795f931ed676787259b90f6c964690ab8658e19d3cfe610b68403e904022 | Shell | 1,431 | 31 | #!/usr/bin/bash
# --taxonomy /home/projects/cpr_10006/people/svekut/mmseq2/almeida_taxonomy.tsv \
# --taxonomy_predictions /home/projects/cpr_10006/projects/vamb/almeida_vaevaeout/results_taxonomy_predictor.csv \
vamb \
--model vaevae \
--outdir /home/projects/cpr_10006/projects/vamb/almeida_vaevaeout_flatsof... |
438d2404183aaea14dee0ff20959b03c530a562a8330a2ff9c7d1fb36fc5d970 | Shell | 1,434 | 46 | #!/bin/bash
set -e
# Create a temporary directory for backup files and setup cleanup trap
TEMP_DIR=$(mktemp -d)
cleanup() {
echo "Cleaning up temporary directory: $TEMP_DIR"
rm -rf "$TEMP_DIR"
}
trap cleanup EXIT
echo "Created temporary directory: $TEMP_DIR"
# Create backup copies of req files to reference ... |
649ba1832775faaae1e5c0b287f73c5395a93eebd5d62083b7dec6d017612066 | Shell | 1,441 | 26 | #!/bin/bash
#SBATCH -n 1 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-06:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared # Partition to submit to
#SBATCH --mem=32000 # Memory pool for all cores (see also... |
2c2e5dcdd612dd8ec0d531e1805bc63bd6cb025715c216b17f55fd9d9fc9c55c | Shell | 1,445 | 39 | #!/usr/bin/env bash
#######
# Purpose: Split database list of genomes into multiple chunks to
# distribute fastANI execution on multiple compute nodes
# Usage: <this_script> <file containing genome paths, one per line> <count> <output_directory>
# Ouput: see <count> number of files in <output_directory>
DA... |
058e572e6e4dde32057ff94e424dcd0bf011d0b7092043a656a9e2441e7d1c53 | Shell | 1,449 | 47 | #!/bin/bash
#SBATCH --gpus-per-node=1
#SBATCH --output=logs/%j.out
conda init bash
. ~/.bashrc
conda activate GraphPT
cd ../src/
#### GIN fine-tuning
split=scaffold
dataset=$1
model=$2
expt_dir=$3
batch_size=256 ## try 32, 64
adapt=$4
model_group="supc" ## for logging to WANDB
portion=1
skips=(aux_skip_connec... |
f079e0562373b8f1e452ddec67a38724c2fbe1bada4432198c1b88b53fa7614c | Shell | 1,461 | 53 | #!/bin/bash
#SBATCH -J nb_res
#SBATCH -N 1
#SBATCH -n 32
#SBATCH -p kellis
#SBATCH --time=24:00:00
#SBATCH --mem=90G
#SBATCH --output=/home/cboix/data/DEVTRAJ/db/out/nebula_res_%j.log
#SBATCH --export=ALL
#SBATCH --requeue
#SBATCH --array=1-668
# Run as:
# sbatch --time=72:00:00 --array=1-450 $SBINDIR/different... |
7b7394cc3de109479a788049400f14d4cc1078f518e892a20a597884219ff27b | Shell | 1,471 | 43 | # Author: Zachary Chiang, Buenrostro Lab, Harvard University
# Runs haplotyping pipeline for in situ genome sequencing data
# download VCF files
wget ftp://ftp-mouse.sanger.ac.uk/current_snps/strain_specific_vcfs/C3H_HeJ.mgp.v5.snps.dbSNP142.vcf.gz
wget ftp://ftp-mouse.sanger.ac.uk/current_snps/strain_specific_vcfs/D... |
b8fcd9afa8546073135162316fb443bc8fe4ecb56a98891fbf1f8126d720d082 | Shell | 1,471 | 37 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrchq # submit to the parallel queue
#SBATCH --time=2:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 ... |
e7db0ee5e1a0a381659c3294d1555ac81a86e4cd884f1932ec3d1fe69f9dba3c | Shell | 1,480 | 27 | #!/bin/bash
#SBATCH -n 1 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-01:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared # Partition to submit to
#SBATCH --mem=16000 # Memory pool for all cores (see also... |
98a08d7a756f4790e0570243c5018a3ec6c4cdd7d3240f698016ce2c75e2f5a9 | Shell | 1,481 | 33 | #!/bin/bash
[[ ${SLURM_NODELIST} ]] || { echo "SLURM environment not detected." ; exit 1 ; }
pdir=$(pwd)
profile="${SLURM_JOBID}_profile"
clog="ipcontroller_${SLURM_JOBID}.log"
#/mnt/xfs1/bioinfoCentos7/software/installs/python/2.7.10/bin/ipcontroller --profile=${profile} --ipython-dir=${pdir} --ip='*' > ${clog} 2>&1... |
4163153eb5e4697b9189aa2160741f130c4561691bedd91e9b8d40f7afa4828d | Shell | 1,485 | 33 | #!/bin/bash
#SBATCH --export=ALL # export all environment variables to the batch job
#SBATCH -D . # set working directory to .
#SBATCH -p mrcq # submit to the parallel queue
#SBATCH --time=3:00:00 # maximum walltime for the job
#SBATCH -A Research_Project-MRC148213 # research project to submit under
#SBATCH --nodes=1 #... |
bc7fe3729a5d1f4c09612a6b21b6d39a5caf89f05f6cfacc34cda81b4e2a5961 | Shell | 1,485 | 28 | #!/bin/bash
#SBATCH -n 4 # Number of cores (-n)
#SBATCH -N 1 # Ensure that all cores are on one Node (-N)
#SBATCH -t 0-08:00 # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared # Partition to submit to
#SBATCH --mem=72000 # Memory pool for all cores (see also... |
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