sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ad0da79ecf5690c6c8b1e83032c365821a93ddf8a0fca47aefb5cfe932a5aa6f | Shell | 640 | 26 | #!/bin/bash
DIRECTORY_PROJECT=/scratch/gvignoud/results_dual
NAME_PROJECT=$1
ZIP_TIME=$(date '+%d/%m/%Y %H:%M:%S')
echo -e "\n\nScript zipped on $ZIP_TIME" >> $DIRECTORY_PROJECT/$NAME_PROJECT/info.txt
cd $DIRECTORY_PROJECT/$NAME_PROJECT
INPUT_OAR_JOBS=$DIRECTORY_PROJECT/$NAME_PROJECT/OAR_JOB_NAMES.txt
echo -e "\n... |
2ca9073235f3c2409cb2e99a01661672a6b96728ed238897e4b6dd7292e27c25 | Shell | 641 | 17 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=01_rt_svd
TIME=3
ITER=3
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER --ref-col-rt"
... |
57702fb8376fe518b38e84d3433e12e4476369e18dcf315ee859c2562a3cc506 | Shell | 641 | 22 | #!/bin/sh
#################### activate conda env #######################
eval "$(conda shell.bash hook)"
conda activate pyg
#################### prcessing all fna files #######################
counter=0
sourceDir=`ls ./NEED_to_PREPARE/pdb/`
num=`ls ./NEED_to_PREPARE/pdb/ | wc -l`
for name in $sourceDir
do
((counte... |
c4ee652da6a4629efc8c6c359ace677b8649c2b6cc9d819e327906aba3981f05 | Shell | 641 | 17 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=01_rt_svd
TIME=3
ITER=3
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER --ref-col-rt"
... |
168a4744c35eb41f59c0bcb74d0077c307d3fcb8a543d12c6cb8f581dd2caaa0 | Shell | 642 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER"... |
977ea39c2039c3012f0ea3fcf136a65bab2d5bcb9e0d6413924da5b78c09d42e | Shell | 642 | 26 | #!/bin/bash
DIRECTORY_PROJECT=/scratch/gvignoud/results_single
NAME_PROJECT=$1
ZIP_TIME=$(date '+%d/%m/%Y %H:%M:%S')
echo -e "\n\nScript zipped on $ZIP_TIME" >> $DIRECTORY_PROJECT/$NAME_PROJECT/info.txt
cd $DIRECTORY_PROJECT/$NAME_PROJECT
INPUT_OAR_JOBS=$DIRECTORY_PROJECT/$NAME_PROJECT/OAR_JOB_NAMES.txt
echo -e "... |
e0f82183e91aeee92cf7a51eec6f7246064c6e55100b9f50ca0d6947395ece27 | Shell | 642 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER"... |
aba6b1c206193d692effbb7f04c4346d0a23b84d55819af47ff9caf06e20dca9 | Shell | 644 | 33 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -t 1-1000:1
#$ -tc 50
#$ -l mem_free=5G,h_vmem=5G,h_fsize=100G
#$ -N subsampling_sexBYsz
#$ -o ./logs/summary_$TASK_ID.log
#$ -e ./logs/summary_$TASK_ID.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${JOB_N... |
f2311b75dcc40245cd52b021e243507969fa31d9cfecee871461a051f6a8f15d | Shell | 645 | 21 | #!/bin/bash
lib=$(tail -n+2 data/cayo_brain_bulk_metadata_technical.tsv | cut -f 1 | sed -n ${SLURM_ARRAY_TASK_ID}p)
mkdir -p star
STAR --runThreadN $SLURM_CPUS_ON_NODE \
--genomeDir genomes \
--readFilesIn fastq/${lib}.R1.fastq.gz,fastq/${lib}.R2.fastq.gz \
--readFilesCommand zcat \
--outSAMtype BAM... |
7322591656006ce07d18059f50c7ce6a7f90cca13efbcba8d868039365c22d8d | Shell | 646 | 26 | #!/bin/bash
DIRECTORY_PROJECT=/scratch/gvignoud/results_succession
NAME_PROJECT=$1
ZIP_TIME=$(date '+%d/%m/%Y %H:%M:%S')
echo -e "\n\nScript zipped on $ZIP_TIME" >> $DIRECTORY_PROJECT/$NAME_PROJECT/info.txt
cd $DIRECTORY_PROJECT/$NAME_PROJECT
INPUT_OAR_JOBS=$DIRECTORY_PROJECT/$NAME_PROJECT/OAR_JOB_NAMES.txt
echo ... |
0e5af581ae8a499aac4dea2b504ec121ffcec420b7b0f72a5da2f1dda2b32573 | Shell | 647 | 32 | #!/bin/sh
gpu=(2 2 2)
suffix_list=(
"LRinput_supervised_SRCNN_bicubic_init_s_64_L_2pi"
)
data_frac_list=(
"1/16"
)
for ((i=0; i<1; i++)); do
(
CUDA_VISIBLE_DEVICES=${gpu[i]} \
python ../src/main.py \
--model='SRCNN' \
--batch_size=32 \
--PDE='iCFD' \
--sca... |
f1204d368b5c140b2cbd9f19c89e8d9a192732c8deb376a886f68765a21da0fc | Shell | 647 | 20 | #!/bin/bash
# run this script to set up a xtb environment
# requirements: $XTBHOME is set to `pwd`
if [ -z "${XTBHOME}" ]; then
XTBHOME="$(cd -P "$(dirname "${BASH_SOURCE[0]}")" && pwd)/../../"
fi
# set up path for xtb, using the xtb directory and the users home directory
XTBPATH=${XTBHOME}/@datadir@:${HOME}
# to ... |
caeee49790fc0a96e604675bfc6eadd33acd8f14f85d7be694b16db13ece5682 | Shell | 650 | 34 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -t 1-500:1
#$ -tc 50
#$ -l mem_free=5G,h_vmem=5G,h_fsize=100G
#$ -N mash_allpairs_array
#$ -o ./output/allpairs_$TASK_ID.log
#$ -e ./output/allpairs_$TASK_ID.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${... |
eac569e95f395a4bc6dd952d0db6f2d28bd1b0d351ca7cefb4cd06bfe0975ddf | Shell | 651 | 34 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -t 1-1250:1
#$ -tc 50
#$ -l mem_free=5G,h_vmem=5G,h_fsize=100G
#$ -N mash_allpairs_array
#$ -o ./output/allpairs_$TASK_ID.log
#$ -e ./output/allpairs_$TASK_ID.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: $... |
91e0d1b4d8338cb71abb9cd09be00bd500614f92f86b265d8b7a376eac05cfd5 | Shell | 652 | 19 | #!/bin/sh
gpu=2
CUDA_VISIBLE_DEVICES=${gpu} \
python train_3D/train.py \
--run_name frag2seq \
--batch_size 64 \
--max_epochs 2000 \
--root_path ./seq/two_digit_smiles_reorder_cutoff_15_ligand_only_frag/train_frag_seq \
--output_tokenizer_dir ../seq/storage/two_digit_smiles_reorder_cutoff_15_ligand_only_frag/train_fr... |
a36cf5d37f8f36c09351045618d99d768cba6a4234e84b32ba83e2d861fa13b4 | Shell | 652 | 17 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=01_rt_svd
TIME=3
ITER=3
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER --ref-col-rt"
... |
adc0b566da5c9fc5a176de7817a6d984cf59c91b51f42f598b059a7de4c4c4d3 | Shell | 652 | 30 | #!/usr/bin/env bash
# Takes a command and creates an SVG of a flame graph using perf and utilities
set -e
set -x
if [ $# -lt 2 ]; then
echo Usage:
echo $(basename "$0") COMMAND SVG_OUT
exit 1
fi
if [ ! -d FlameGraph ]; then
echo Please clone the FlameGraph repo so it is available at "FlameGraph"
echo See: https... |
410421388dc7ca61b8a5bd8fcac0fe389da8f2ab33f47fbfd8884af5d017a42c | Shell | 653 | 34 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -t 1-1500:1
#$ -tc 50
#$ -l mem_free=10G,h_vmem=10G,h_fsize=100G
#$ -N mash_allpairs_array
#$ -o ./output/allpairs_$TASK_ID.log
#$ -e ./output/allpairs_$TASK_ID.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name:... |
6cc118aec657ccc667ba316d60f99b08e6f80e338a8167a12b7e2e96c2ed6cf8 | Shell | 653 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER"... |
d2c814330dcfd29d83d6203a03e3202329eb42ccf3bdd025b9cf34328b786ebe | Shell | 653 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER"... |
8ad735ae371b337d7745a47663364b520ec58494fc26984093a002035935a8e3 | Shell | 654 | 22 | #!/usr/bin/bash
start=`date +%s`
SRC_PATH=$1
RESULT_PATH=$2
declare -a cell_types=("hela-lclc-mcf7-mdamb231" "hela-lclc-mcf7-mdamb231-preo" "breastcancer-hela-lclc" "breastcancer-hela-lclc-preo" "breastcancer-hela" "hela-mcf7-mdamb231" "mcf7-mdamb231")
declare -a times=(30 60 90 120 150)
for i in "${cell_types[@]}"... |
94d3703ead201d3a2a79f79045e2f040a083a58646e3a35538cf21cf1d747558 | Shell | 655 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
d07fe80b6cb178957d0fb9f529791f5cbbf1c6f393391031bb6efa38b0bd44f6 | Shell | 655 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
dd68dbe389de20f1010bd6180c177b4c6bd7e6be9769114eed6bb4a8cf206eaf | Shell | 655 | 18 | #!/bin/sh
##
##
#SBATCH -p gpu-super.q
#SBATCH --exclude=nova002,nova003,nova00[5-7],nova01[1-4]
#SBATCH --cpus-per-task=6
#SBATCH -n 1
#SBATCH -N 1
#SBATCH --job-name=ep_100
#SBATCH --output=output.log
#SBATCH --gres=gpu:1
export NCCL_P2P_DISABLE=1
python scripts/inference_end_to_end_w_igfold.py --batch_size 1 --wei... |
12afee6f4e4683406fe96e2ee7e67e58a5bdba5a4aa4a3d65ca27fb571199b76 | Shell | 656 | 11 | gen=test
phen=test.pheno
covar=test.cov
annot=single.annot
env=test.env
../build/GENIE -g $gen -p $phen -c $covar -e $env -m G+GxE+NxE -k 20 -jn 10 -o test.out --annot $annot -t 6 -s 2 --memeff --opt2 0
# ../build/GENIE_multi_pheno -v -g $gen -p ./test.2.pheno -c $covar -e $env -m G+GxE+NxE -k 10 -jn 10 -o test.... |
612f8a1f5c7ac7f265a2aaa85d38c53db985963e846754ec1b6546150e7453b4 | Shell | 656 | 18 | # create_tabix_gtex_sqtl_allpairs.sh
# by Brian Chen
# This script takes GTEx v8 sQTL all pair files and outputs index file for tabix
# $1 is path to tissue file
module load htslib #or module load tabix
module load vcftools
tissueName=$(echo "${1##*/}" | cut -f 1,2 -d '.')
echo $tissueName
zcat $1 | sed '1D' | tr '_... |
d1f858b77753ccbc43cbc08d4e83cddfca960ce7ee06afde9fe8adb841ffd781 | Shell | 663 | 21 | # create_tabix_eqtl_catalogue.sh
# by Brian Chen
# This script creates tabix index files for significant pairs files generated from eQTL Catalogue datasets
# used in make_significant_pairs_files.R
# $1 is path to tissue file
module load htslib #or module load tabix
module load vcftools
# Remove .tsv.gz
tissueName=$(e... |
0cd7b23f6f8d3638a609714c3c8f3b77f5112e31d21662fa512180e5260b5bd6 | Shell | 666 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
96ac34a823e8ccf58802ae0dc9dd8b12ace43906fa59989a56181b01c5c5d91e | Shell | 666 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-13:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=3
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
9be888904d9940aa0723c96f8eb215ea9716d301df0204a5f72c14e95a051c29 | Shell | 666 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-15:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=5
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
a0e8938c518623c135baa692bf3f067ef253d471abd600ee143d8da7a57cd825 | Shell | 666 | 18 | SBATCH_OPTIONS=" -p gpu-a100 -t 0-15:00:00 --ntasks=4 --gres=gpu:4"
SPOKES=13
SPLIT="0.75"
SPLIT_FLAG=2
OS=1.5
COS=1.25
DATASET=02_rt_rovir
TIME=1
ITER=3
ROVIR=" -V"
NETWORK="--scaling-flags=$(bart bitmask 10) --init-rtnlinv --conv-time=$TIME -i$((6+ITER)) --resnet-block=no-batch-normalization,F=64 --iter-net=$ITER ... |
cd2f764f3d387ad2d91994f062d5c901084f67fccdd5e38d19c7f55ba7d960f4 | Shell | 669 | 27 | #!/bin/bash
# Convert probabilistic 4D atlas (labels in 4th dimension) to indexed 3D volume with thresholding
# - Use approach favored by FSL
#
# AUTHOR : Mike Tyszka
# PLACE : Caltech
# DATES : 2015-08-19 JMT From scratch
# 2016-04-20 JMT Use mktemp filename for mask to avoid SGE overwrites
if [ $# -lt 3 ]... |
195a80b0630140c5423c701ea662f6eaa74e3dae9f1d886bdee99754225a9ca6 | Shell | 673 | 44 | #!/usr/bin/env bash
# definitions
workDir=/vols/Scratch
scriptDir=/vols/Scratchcomparative_scripts
outDir=/vols/Scratch/comparative_scripts/gICA
mkdir -p $outDir
subjList="001
002
003
004
005
006
007
008
009
010
011
012
013
014
015
016
017
018
019
020"
template=/vols/Scratch/Valerio_data/Template/QBI_atlas_2mm_v6.ni... |
7f63f786828a671c318db83c7c34e42885bea8ab6be47f709b99bae2094d98c0 | Shell | 676 | 34 | #!/bin/bash
while getopts 'c:n:t:r:p' OPT; do
case $OPT in
c) cuda=$OPTARG;;
n) name=$OPTARG;;
t) task=$OPTARG;;
r) train="true";;
p) predict="true";;
esac
done
echo $name
if ${train}
then
cd /home/yuchen/nnSegnext/nnsegnext/
CUDA_VISIBLE_DEVICES=${cuda} nnSeg... |
109dceede2d4a529f88707a45759b2fa2793db97dad9e98d7443011d73062e64 | Shell | 680 | 24 | #!/bin/bash -x
set -euo pipefail
#working the nudup to get the log file for the PCR duplication rates
#Default is 8 bases, the script obtains it from the readname
bam=$(readlink -e "$1")
paired=$2
pairopt=""
if (( paired == 1 )); then
pairopt="-2"
fi
SID=$(basename "$(dirname "$bam")")
set +e #head has a problem w... |
a485b1c67e2eb142490cc66ac903d33f2c246b20487de374e4222f5313cd5a26 | Shell | 681 | 22 | #!/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")"
# the "type" variable below is setting a path inside the main script
for type in "act" "ppi_seed-VS_thr5" "nppi-dmn"; do #... |
8e16a76274193a0d92f8eee99e7f26c77b719f1f2cfb310499d97a2d62a1514a | Shell | 690 | 28 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 2
#SBATCH --output=example_1.out
source activate mlfold
folder_with_pdbs="../inputs/PDB_monomers/pdbs/"
output_dir="../outputs/example_1_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_parsed_chains=$outp... |
0b55f3a4d76c31d9304477ad8bc66f3ac3c4a0beb69fd9e4befe79f3706ddc39 | Shell | 694 | 16 | #!/usr/bin/env bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... |
ad65ab80fbfb8eeec3821f6cb789e5a3c4a885bcd3e8777591643bba6ce6131c | Shell | 694 | 16 | #!/usr/bin/env bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... |
c42a7057b922c932374110fdbb2925b0f1cc07d792ac006b860aa73d2421e2a3 | Shell | 694 | 16 | #!/usr/bin/env bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... |
7318c0b6d28662d259de9d90c9b1e816ddbdd99c8938b38fa2a682e55a8a2301 | Shell | 697 | 30 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_3_model_w_test.out
source activate mlfold
path_to_PDB="../inputs/PDB_monomers/pdbs/5L33.pdb"
output_dir="../outputs/training_test_output"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
chains_to... |
05cdf820d426f5e5da9a4ed0a6ce05c5043ff94e2cdb0ab24d5057d1cee942e5 | Shell | 699 | 16 | #!/bin/bash
GWAS="/ceph/projects/v4_phase3_paper/inputs/sz_gwas/pgc2_clozuk/map_phase3/zscore/tabix/fine_mapped_loci/torus_pip"
SOFTWARE="/ceph/opt/fastenloc/src"
VCF="../../../../../vcf/_m"
## Prepare probabilistic eQTL annotation
$SOFTWARE/summarize_dap2enloc.pl \
-dir ../../_m/dapg_out/ -vcf $VCF/genotypes_chr... |
433f50ba7538bcc548373cc095ff921f6aa2983ade2c6490d92426435faddc89 | Shell | 699 | 26 | #!/bin/bash
#Copyright 2024. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR/..
RAWDIR=${RAWDIR:-$SCRIPT_DIR/../00_data/10_raw_data}
RAW=$RAWDIR/rt_sa/vol0082_vis1
if [ -z "${RECODIR:-}" ]; then ... |
ec38d809344aa96409447bd7051a9784fbcefd842c64291de131ae8f503f6be1 | Shell | 699 | 26 | #!/bin/bash
#Copyright 2024. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR/..
RAWDIR=${RAWDIR:-$SCRIPT_DIR/../00_data/10_raw_data}
RAW=$RAWDIR/rt_sa/vol0056_vis1
if [ -z "${RECODIR:-}" ]; then ... |
136e3a8b328942857beb3911c867333187c1a6a89adc0c4b7fd4af1bc4020da5 | Shell | 700 | 27 | # bert base
ROOT_PATH=""
model_path="$ROOT_PATH/outputs/enhancers_mel/train_inf_bert_base_step1_lr1e-4/checkpoints/val/fbd.ckpt"
python -m train \
experiment=hg38/enhancer_mel_debug \
wandb.mode=online \
wandb.group=Enhancer_Mel \
wandb.name=genfull_bert_base_temp \
hydra.run.dir="./outputs/enhan... |
c7a1c00627e4e4097b7754f663dee23c4325aaa60ab8d3ed9c1f98c4b580a0ef | Shell | 700 | 25 | # bert base
ROOT_PATH=""
model_path="$ROOT_PATH/outputs/enhancers_fb/train_inf_bert_base_step1_lr1e-4/checkpoints/val/fbd.ckpt"
python -m train \
experiment=hg38/enhancer_flybrain_debug \
wandb.mode=online \
wandb.group=Enhancer_Fb \
wandb.name=genfull_bert_base_temp \
hydra.run.dir="./outputs/en... |
af3fc87defcb335eb4cd46f959c660125134838f570d003cb9f0744469c522df | Shell | 701 | 20 | #!/bin/bash
# from here: https://stackoverflow.com/questions/5014632/how-can-i-parse-a-yaml-file-from-a-linux-shell-script
function parse_yaml {
local prefix=$2
local s='[[:space:]]*' w='[a-zA-Z0-9_]*' fs=$(echo @|tr @ '\034')
sed -ne "s|^\($s\):|\1|" \
-e "s|^\($s\)\($w\)$s:$s[\"']\(.*\)[\"']$s\$|\1... |
717521b08d6214994f2daa3ac3913480908184b9439a15c4ae0e78de92739d94 | Shell | 703 | 16 | #!/bin/bash
GWAS="/ceph/projects/v4_phase3_paper/inputs/sz_gwas/pgc2_clozuk/map_phase3/zscore/tabix/fine_mapped_loci/torus_pip"
SOFTWARE="/ceph/opt/fastenloc/src"
VCF="../../../../../vcf/_m"
## Prepare probabilistic eQTL annotation
$SOFTWARE/summarize_dap2enloc.pl \
-dir ../../_m/dapg_out/ -vcf $VCF/genotypes_chr... |
a321f7a54de88010b7b69858d62c22f2a937f278a187ad2e16fa0a48a084d3c6 | Shell | 704 | 25 | #!/usr/bin/env bash
###############################################################################
#
# Delete all output after a MAPP run.
#
# AUTHOR: Maciej_Bak
# AFFILIATION: University_of_Basel
# AFFILIATION: Swiss_Institute_of_Bioinformatics
# CONTACT: wsciekly.maciek@gmail.com
# CREATED: 27-11-2020
#... |
cbc3245f62b9465f05a3b57f0799f1c1c6474d682a003a5ac3e6ee90899e5aa5 | Shell | 704 | 18 | #!/bin/bash
# This script will perform Level 3 stats across social
# and nonsocial conditions in the ISTART Social Doors task
# for models containing covariates
MAINDIR=/data/projects/istart-socdoors/derivatives/fsl
for modelnum in 2 3; do
for type in "act" "ppi_seed-VS_thr5" "nppi-dmn"; do
#cp run_randomise.s... |
bf0b77eace7b6264ee15818553db8dde3d78934d75dc0dc4782b160a6b1e43f3 | Shell | 705 | 26 | # bert base
ROOT_PATH=""
model_path="$ROOT_PATH/outputs/promoter/train_inf_bert_base_step1/checkpoints/val/sei_promoter.ckpt"
python -m train \
experiment=hg38/promoter \
wandb.mode=online \
wandb.group=Promoter \
wandb.name=genfull_bert_base_temp \
hydra.run.dir="./outputs/promoter/genfull_bert... |
e75f19339a109863567db256d3a64476017ba8855ab0bea939ee7da0cb157def | Shell | 707 | 24 | #!/bin/bash
#Copyright 2024. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR/..
RAWDIR=${RAWDIR:-$SCRIPT_DIR/../00_data/10_raw_data}
if [ -z "${RECODIR:-}" ]; then
RECODIR="$SCRIPT_DIR/../"
... |
73c8762226ad3c272eee254e806519c47b58dad0469e70a1733c69880e3eb6a1 | Shell | 710 | 19 | #prepare for genotype file
for i in {1..22}
do
#selcet sample
bcftools view -S ../RNA_WGS2.txt --force-samples ROSMAP/WGS/"DEJ_11898_B01_GRM_WGS_2017-05-15_"$i.recalibrated_variants.vcf.gz -Oz > rna.chr$i.vcf.gz
gunzip rna.chr$i.vcf.gz
vcftools --vcf rna.chr$i.vcf --plink --out rna.chr$i
rm rna.chr$i.vcf
plink --file r... |
0d5578fb0e611cd54c0c6206653d8d56f59947a50e30a28f9ec0210eec00d1e0 | Shell | 711 | 17 | #!/bin/bash
# Global variables
SEQUENCE_FILE=03_sequences/analyzed_genes.fasta
SWISSPROT_RESULT=04_blast_results/analyzed_genes.swissprot
SWISSPROT_HITS=04_blast_results/analyzed_genes.hits
SWISSPROT_DB=~/Software/blastplus_databases/swissprot
# Blast all sequences against swissprot (must be installed locally)
# WARN... |
63fcab65c7b0b34fc50d9a15aa2f23b3567dcb032691c809f7c58e7398632cfe | Shell | 711 | 16 | #!/bin/bash
GWAS="/ceph/projects/v4_phase3_paper/inputs/sz_gwas/pgc2_clozuk/map_phase3/zscore/tabix/fine_mapped_loci/torus_pip"
SOFTWARE="/ceph/opt/fastenloc/src"
VCF="../../../../../vcf/_m"
## Prepare probabilistic eQTL annotation
$SOFTWARE/summarize_dap2enloc.pl \
-dir ../../_m/dapg_out/ -vcf $VCF/genotypes_chr... |
b0e242de5539c1b45717b8470f707df6b6f9eb83d65294b8b4dc4f8604a238a4 | Shell | 721 | 14 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
25d481812ee1d35775903f7793a36a563bd9f7b168f8b402cbcaec44c1a4af62 | Shell | 728 | 31 | ROOT_DIR="/tmp/thchs-tts"
# Update package list
sudo apt update
# Install Python 3.8
sudo apt install python3-pip python3.10 python3.10-dev python3.10-distutils python3.10-venv -y
# Empty "ROOT_DIR"
rm -rf "$ROOT_DIR"
mkdir -p "$ROOT_DIR"
# Create virtual environment
# All tools will be installed there and can only... |
94a3ebcdb69d72feca9a1eb7153f7ed80a7663eb58a2f3e4fe0c29abb266055c | Shell | 729 | 29 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 2
#SBATCH --output=example_7.out
source activate mlfold
folder_with_pdbs="../inputs/PDB_monomers/pdbs/"
output_dir="../outputs/example_7_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_parsed_chains=$outp... |
2f6e0715a88abffd6a35fe4686dcbb076a0353cb3128de9f995085225aeca7bb | Shell | 733 | 18 | #!/bin/sh
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
python3 ${root_path}/data_preprocessing_TCGA/2.sample_filtering/1.sample_all_filter.py \
--raw_data_path ${root_path}/data_TCGA/1.raw_data/ \
--save_path ${root_path}/data_TCGA/2.sample_id/ \
--cancer BRCA
python3 ${root_path}/data_p... |
2fa2b6a8fa5c5835536c1efe33bb0b0cd7c2a334af0ff2323e6273b94e39e5f8 | Shell | 736 | 24 | mkdir tbss
mkdir tbss/MD
mkdir tbss/RD
mkdir tbss/L1
for j in $(cut -f1 dwi_over_55_ctl.tsv); do
cp diff_model_fit/$j/dti_FA.nii.gz tbss/ctl_${j}.nii.gz
cp diff_model_fit/$j/dti_MD.nii.gz tbss/MD/ctl_${j}.nii.gz
cp diff_model_fit/$j/dti_RD.nii.gz tbss/RD/ctl_${j}.nii.gz
cp diff_model_fit/$j/dti_L1.nii.gz tbs... |
e52bd4930084105bcb7d2d6c52344e9354b54149ee7836150e4ba3bf4a4f9484 | Shell | 737 | 21 | #!/bin/sh
mkdir -p "database/stringdb"
echo "downloading uniprot to string id mappings:"
export ftp_proxy=${http_proxy}
wget \
"https://string-db.org/mapping_files/uniprot/mouse.uniprot_2_string.2018.tsv.gz" \
-O "database/stringdb/mouse.uniprot_2_string.2018.tsv.gz"
wget \
"https://string-db.org/mapping_files... |
83b76376d1d3e5fb36f4ab0f8a01f93aea14b4b2cce4aba483fe5f42f64b0431 | Shell | 738 | 23 | #!/bin/bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to i... |
7f933908bcf371ae9d03934b5ae0979d473d13bd82d7b126fdd36c746dbece09 | Shell | 743 | 23 | #!/bin/bash
seed=2
run_dir="sample_brain_93d86cda9d064414885645a907ab4a83_aaee864e3e83473eb56953d8645ac991"
vqvae_uri="/project/mlruns/0/93d86cda9d064414885645a907ab4a83/artifacts/final_model"
transformer_uri="/project/mlruns/0/aaee864e3e83473eb56953d8645ac991/artifacts/final_model"
vbm_img=1
runai submit \
--name s... |
583c6ed74e0da8043b74cba8cfcb32cfb1c72817b122db8a52b16adf20611847 | Shell | 746 | 4 | cd C:/Users/Admin/Git/repo/ZS-DeconvNet/Fiji_Plugin/TransferTFModelToPluginFormat
# python TransferZSDeconv2DModelToPluginFormat.py --load_weights_path 'D:/ZS_DeconvNet/submit_NM_20230523/isotropic_concern_by_R3_fromNBT/SIM_MT/MT-deconv-rotation-ImgJointNorm&Recorrupt/MT-weightes-anti-rotation.h5' --out_path 'D:/ZS_De... |
47b56c19307fe10a597f288a670abd24efcca73c35cc7b73ad1249bbebb2a84a | Shell | 748 | 17 | #!/usr/bin/env bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
maindir="$(dirname "$scriptdir")"
for sub in `cat ${maindir}/code/newsubs.txt`; do
# ROI name and other path information
for ROI in VS_thr5; do
... |
18d07bd1597c49463b7985b48100c7837e9662ac053707bc0f31175ab3b4743f | Shell | 753 | 28 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
NET=$(readlink -f $1)
cd $NET
source config.sh
WORKDIR=`mktemp -d 2>/dev/null || mktemp -d -t 'mytmpdir'`
trap 'rm -rf "$WORKDIR"' EX... |
62907fdfef069bf9d7a42c01d6f14d36f6b0e8dc42d103f8c98e74783a265eaa | Shell | 753 | 28 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
NET=$(readlink -f $1)
cd $NET
source config.sh
WORKDIR=`mktemp -d 2>/dev/null || mktemp -d -t 'mytmpdir'`
trap 'rm -rf "$WORKDIR"' EX... |
7e97d98d3cee4513192ff743a31cd7c842829b1140f6801b4dcd5e5b6bd1aa20 | Shell | 758 | 29 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --mem=20G
#SBATCH --partition=rondror
#SBATCH --gres gpu:1
#SBATCH --constraint=GPU_MEM:12GB
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=mvoegele@stanford.edu
#SBATCH --qos=high_p
mkdir -p pca
mkdir -p plots
mkdir -p results
python ../scripts/calculate_combined_princi... |
364c9fb74cedcd4a67b6d5c733dc27d1aed8b559ad185d3ad00179154212bde8 | Shell | 762 | 14 | #!/bin/bash
wget https://huggingface.co/datasets/sywang/CNNDetection/resolve/main/progan_train.7z.001 &
wget https://huggingface.co/datasets/sywang/CNNDetection/resolve/main/progan_train.7z.002 &
wget https://huggingface.co/datasets/sywang/CNNDetection/resolve/main/progan_train.7z.003 &
wget https://huggingface.co/data... |
9ee126bb1ca4cb4f2fa64f0c5960758276a66282bb50732e8d500009f3ba0930 | Shell | 764 | 31 | # Example speedseq commands on a small slice of chromosome 20
# 1. Align with BWA
../bin/speedseq align \
-o example \
-M 3 \
-p \
-R "@RG\tID:NA12878\tSM:NA12878\tLB:lib1" \
data/human_g1k_v37_20_42220611-42542245.fasta \
data/NA12878.20slice.30X.fastq.gz
# 2. Detect SNVs and indels
../bin/sp... |
c38a3584a8e0a807eff7527f5cdeae6d04d9fe7618f0c62170e715db4fc25c75 | Shell | 767 | 17 | #!/usr/bin/env bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... |
71734ebd901bbb8f2cde81c616e6ef7bed216c163e5185d4a729cdd029cacd58 | Shell | 768 | 19 | #!/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")"
# compile cope and zstat images for doors and social to one directory
for sub in `cat ${scriptdir}/newsubs.txt`; do
#for s... |
0dab7c61f56276d9f634739269417248bfe016a2983ee3b1136cde765c19fbef | Shell | 770 | 30 | #!/bin/bash
#BSUB -P "tyk2-benchmark"
#BSUB -J "perses-benchmark-[1-24]"
#BSUB -n 1
#BSUB -R rusage[mem=8]
#BSUB -R span[hosts=1]
#BSUB -q gpuqueue
#BSUB -sp 1 # low priority. default is 12, max is 25
#BSUB -gpu num=1:j_exclusive=yes:mode=shared
#BSUB -W 24:00
#BSUB -m "lu-gpu lg-gpu lv-gpu ld-gpu lt-gpu lp-gpu ls-gpu... |
6d465ec9eb68ad8284a500830bdee377dcdb5eda436cf0fca81ee1a36a7d05ae | Shell | 772 | 30 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_3_from_fasta.out
source activate mlfold
path_to_PDB="../inputs/PDB_complexes/pdbs/3HTN.pdb"
path_to_fasta="/home/justas/projects/github/ProteinMPNN/outputs/example_3_outputs/seqs/3HTN.fa"
output_dir="../ou... |
cc8d31217fbdbacb1b751ad74065b82d553ffb422e148a86299e78e6d9033e78 | Shell | 772 | 39 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -l mem_free=10G,h_vmem=10G,h_fsize=100G
#$ -N coloc_supp
#$ -o ./summary.log
#$ -e ./summary.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${JOB_NAME}"
echo "Hostname: ${HOSTNAME}"
## List current modules ... |
17730b5d03bbf16d3cb37b2b65a464dc3685d899ed3df4735c79f9224cd460b8 | Shell | 774 | 28 | #!/bin/bash
# Ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
basedir="$(dirname "$scriptdir")"
nruns=1
#for task in socialdoors; do
for task in doors socialdoors; do
for ppi in 0; do # 0 "VS_thr5" "dmn"; do # putting... |
ba51954d206615304c834a79cba795734929b99ed20ecce8d2fcb44b9892de78 | Shell | 774 | 8 | cd lasagna
mkdir results
# python program.py <dataset> <column_index_of_label> <result_location> <id_for_embeddings: 0=onehot, 1=a_c, 2=a_{ph}, 3=[a_c,a_{ph}]> <hidden_dim> <epochs_per_fold>
CUDA_VISIBLE_DEVICES=4 python rcnn.py ../../../string/preprocessed_balanced/protein.actions.SHS27k.tsv 4 results/SHSs_wvctc_rcnn_... |
68ec5d2afca789d0508564264bd09ed6b41244e300e812d7b9c7edb35c345233 | Shell | 777 | 48 | #!/usr/bin/env bash
# definitions
workDir=/vols/Scratch
scriptDir=/vols/Scratch/comparative_scripts
mkdir -p $workDir/connectivity_maps_humans
subjList="HCP01
HCP02
HCP03
HCP04
HCP05
HCP06
HCP07
HCP08
HCP09
HCP10
HCP11
HCP12
HCP13
HCP14
HCP15
HCP16
HCP17
HCP18
HCP19
HCP20"
seedList=""
premotorList=""
template="$FS... |
441608545eab5085fe34915d0a026858ac7f95dd95a67847a9649bc8c4d68dfc | Shell | 781 | 26 | DB_NAME='maps'
GPU_ID=1
DISPLAY_ID=1
NET_G=resnet_6blocks
NET_D=basic
MODEL=cycle_gan
SAVE_EPOCH=5
ALIGN_DATA=0
LAMBDA=10
NF=64
EXPR_NAME=${DB_NAME}_${MODEL}_${LAMBDA}
CHECKPOINT_DIR=./checkpoints/
LOG_FILE=${CHECKPOINT_DIR}${EXPR_NAME}/log.txt
mkdir -p ${CHECKPOINT_DIR}${EXPR_NAME}
DATA_ROOT=./datasets/$DB_NAME al... |
7093a776d18a8e10f81d034c96fa6cc2123e7f65e144059d1b5efc7049472daa | Shell | 782 | 17 |
REGRSSION_MODELPATH="runs/regression_finetune"
TRAINED_MODELPATH='save_regression_models'
MODELNAME="model_gnn_5.pth"
mkdir $REGRSSION_MODELPATH
cp src_regression/molecule_finetune_regression.py $REGRSSION_MODELPATH
cp $0 $REGRSSION_MODELPATH
split=scaffold
batch_size=256
CUDA_VISIBLE_DEVICES=0 python src_regres... |
11a17d3ab2b2c3ecbe7a984e95ba39037d337347943120c9de1b1a67dd14bbd5 | Shell | 785 | 24 | export CLOUDINARY_UPLOAD_PRESET=
export CLOUDINARY_API_KEY=
export CLOUDINARY_API_SECRET=
export CLOUDINARY_UPLOAD_URL=
export CLOUDINARY_DELETE_URL=
export COINSTAC_REPOSITORY_NAME=
export GITHUB_ACCESS_TOKEN=
export GITHUB_BOT_USERNAME=
export SENDGRID_API_KEY=
export API_SERVER_PORT=3100
export API_SERVER_HOSTNAME=a... |
f01af15128b94325cfd0cf4753664d22d5966e6b4ffc5b49b50f564ad8762ca9 | Shell | 787 | 11 | ###########################################################################
## Author: Youtao Lu <luyoutao@sas.upenn.edu>
##
## Copyright (c) 2021-2023, Youtao Lu and Junhyong Kim, Department of Biology, University of Pennsylvania
## Copyright (c) 2021-2023, James Eberwine, Perelman School of Medicine, University of ... |
142e4b5a53608932f0f3d80e35efe04e3b47631945fc760b9ee88e1872f7722a | Shell | 791 | 15 | ### Unzipping on SSD is much faster!!!
#!/bin/bash
# download and extract the CrossDocked2020 molecular structures
wget https://bits.csb.pitt.edu/files/crossdock2020/CrossDocked2020_v1.1.tgz -P data/crossdock2020/
tar -C data/crossdock2020/ -xzf data/crossdock2020/CrossDocked2020_v1.1.tgz
# download the train and te... |
b8d952984714e98bfff7d6ca1727eea7b3e082c9871ff0e4020bf0de2c235231 | Shell | 791 | 26 | #!/bin/bash
echo "Test started. Container is running..."
slide_path=$1
models_path=$2
BASE_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)"
SLIDE_BASE_DIR=$(echo $slide_path | cut -d'/' -f1,2)
MODELS_BASE_DIR=$(echo $models_path | cut -d'/' -f1,2)
docker run \
--name MutilsTest \
--gpus '"device=0,... |
c0cd1aace4c8d6bfb53477f60f59ed48efbaad279714944b0fdbf93355184698 | Shell | 792 | 30 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --mem=20G
#SBATCH --partition=rondror
#SBATCH --gres gpu:1
#SBATCH --constraint=GPU_MEM:12GB
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=mvoegele@stanford.edu
#SBATCH --qos=high_p
mkdir -p plots
mkdir -p clusters
python ../scripts/calculate_combined_clusters.py --writ... |
90b2be0c998adcabfe21acab545d24c152e7fc50893571a380da62a9109daaef | Shell | 793 | 19 | #!/usr/bin/env bash
###############################################################################
# This script builds the Dockerfiles in the dockerfiles/ directory.
# assumes that the dockerfiles/ directory is a sibling of the scripts/ directory, and the script is being run
# from the scripts/ directory
set -eux
c... |
0a47fc07149a6653d7b490f9bf82ace39b2bbd27cc44e87f758aa62ffed63836 | Shell | 798 | 36 | #!/usr/bin/bash
wkdir=$1
line=$2
N=$3
pv=$4
burnin=$5
Nmcmc=$6
# summary stat directories
LDdir=$7
Scoredir=$8
# Input files
hfile=$9
start_pos=${10}
end_pos=${11}
target_chr=${12}
toolE=${13}
rand_seed=$RANDOM
# echo Curerent working directory
# pwd
#echo Run Estep with $line $N $pv $hfile $start_pos $end_pos $ta... |
95203fa039fa87535f1f790f0d44ec2a1fa46feb9925c1f6f9e1bcbe9ee0bbb5 | Shell | 802 | 10 | #!/bin/bash
# Here, we're making some unconditional designs
# We are also applying a Radius Of Gyration potential which encourages the design to be more compact
# We specify the path for the outputs
# We tell RFdiffusion that designs should be 100-200 residues in length (randomly sampled each design)
# We generate 10 s... |
b7603dbd3a87d80b9aade2c7ec1712bff413d39460f1e28f30a0a6605a45ac2e | Shell | 804 | 31 | #!/bin/bash
mkdir -p genomes
# Fetch fasta from Ensembl
wget -O genomes/Mmul_10.dna.fa.gz \
ftp://ftp.ensembl.org/pub/release-101/fasta/macaca_mulatta/dna/Macaca_mulatta.Mmul_10.dna.toplevel.fa.gz
# Unzip fasta
gunzip genomes/Mmul_10.dna.fa.gz
# Index fasta
samtools faidx genomes/Mmul_10.dna.fa
# Fetch gtf from E... |
359bde1eadd5a29fe02802fb2ad8296a171abd51c76a9c9a69b8296bd6582c87 | Shell | 807 | 38 | #!/bin/bash
#$ -cwd
#$ -R y
#$ -l h_fsize=50G
#$ -N norm_expression
#$ -o ./summary.out
#$ -e ./summary.out
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${JOB_NAME}"
echo "Hostname: ${HOSTNAME}"
## List current modules for reproducibility
... |
a3a4148116fd7e180df3adacb3144bc4fbc239e1ca33ec0f3433eff2cd19a051 | Shell | 810 | 28 | #!/bin/bash
# Following FSL and CUDA Version need to be active
# CUDA --version 8.0
# FSL --version 5.0.11
# Load Local Variables
source ./SET_VARIABLES.sh
echo "Copy Data to Bedpost Folder"
cp ${DIFF_DATA_DIR}/data_debias_denoise_degibbs_driftcorr_detrend_eddy.nii.gz ${DIFF_DATA_BEDPOSTX_DIR}/data.nii.gz
cp ${D... |
32f64920431ba5f235b1f605d7f6a504fa8f0983490c082d1e044a64055f66fd | Shell | 815 | 31 | # Used to run rrbs pipeline
# Replace values with those for your own machine
LOCAL_PIPELINE_DIR=/Users/akre96/Documents/github/rrbs_bismark
CROMWELL_PATH=/Users/akre96/cromwell/cromwell-36.jar
cd $LOCAL_PIPELINE_DIR
if [[ $# -eq 0 ]] ; then
echo 'ERROR: REQUIRED ARGUMENT MISSING'
echo 'Requires 1 argument: l... |
37747ae06295572ffd6e42ae1d244fb30f7afe810dccc9a4fafd2223a9b2cf13 | Shell | 823 | 29 | #!/usr/bin/env bash
REPOSITORY=$1
JSONTOKEN=$(wget -q -O - "https://auth.docker.io/token?service=registry.docker.io&scope=repository:$REPOSITORY:pull")
PARSEDTOKEN=$(echo $JSONTOKEN | python3 -c 'import json,sys;print(json.load(sys.stdin)["token"])')
code=$?
if [ $code != 0 ]; then
>&2 echo $PARSEDTOKEN
>&2 ech... |
ca6347de39fb72eb801c51f9b5e29912f1d50bef5af5a5eba308b77091f6b85a | Shell | 823 | 13 | #!/usr/bin/env bash
mkdir featureCounts rsem_results qc_report
gsutil -m cp -r gs://my-bucket/rna-seq/sinai/batch5_20191031/rnaseq_pipeline/*/call-rsem_quant/shard-*/rsem_reference/*.genes.results rsem_results/
gsutil -m cp -r gs://my-bucket/rna-seq/sinai/batch5_20191031/rnaseq_pipeline/*/call-featurecounts/shard-*/*.... |
3cc802c778eaa2aafeb4a30365107a84dc4c9944eb976e0a65f61d96852df88b | Shell | 832 | 34 | #!/bin/bash
#$ -cwd -V
#$ -l h_fsize=50G
#$ -N dd_dapg_prep
#$ -e processing.log
#$ -o processing.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${JOB_NAME}"
echo "Hostname: ${HOSTNAME}"
## List current modules for reproducibility
module... |
9b7cecb087b25699c8e26425e324be452575d4e385f274817063ed2c39833829 | Shell | 832 | 28 | #!/bin/bash
## This script assumes PLINK2 is in your PATH
PHENO="/PATH/TO/PHENOTYPE/INFORMATION"
BFILE="/PATH/TO/GENOTYPE/BFILES"
echo "Starting ... $(date +'%Y/%m/%d %H:%M:%S')"
awk -F',' '$2=="Male"{print $18}' $PHENO | \
grep -f - $BFILE/LIBD_Brain_TopMed.fam > keepMale.fam
plink2 --bfile $BFILE/LIBD_Brain_... |
acbe30a1250949f97d0ae2c7265738cfa4c63a5aebd5402e5507c6cf34d23fcc | Shell | 833 | 10 | #!/bin/bash
# Here, we're partially noising and denoising from a starting structure, to generate diversity around this fold
# We first specify the output path, and the path to the 79aa input pdb, 2KL8
# We then specify the contig corresponding to what we want to noise.
# In this case, we want to noise the whole structu... |
f3b718ec13b895ae2d57602cea2ddedc6a2b6e84742fd54556235d53ba335785 | Shell | 834 | 34 | #!/bin/bash
#$ -cwd -V
#$ -l h_fsize=50G
#$ -N cc_dapg_prep
#$ -e processing.log
#$ -o processing.log
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job name: ${JOB_NAME}"
echo "Hostname: ${HOSTNAME}"
## List current modules for reproducibility
module... |
fc6bfadd9cfc3cf08ca67026108df8c82b9ea752ca25910b031b27486705f8bc | Shell | 835 | 29 | #!/bin/bash
gpu=0
top_k=90
temp=0.7
epoch=2000
CUDA_VISIBLE_DEVICES=${gpu} \
python train_3D/generate.py \
--run_name frag2seq \
--batch_size 32 \
--max_epochs 250 \
--root_path ./seq/two_digit_smiles_reorder_cutoff_15_ligand_only_frag/train_frag_seq \
--output_tokenizer_dir ./seq/storage/two_digit_smiles_reorder_c... |
a7ef402c34fdafb33b2504cdc6a8916c88a5212b9d6bf4cdc94fd233f31d1933 | Shell | 836 | 12 | # update DSET to targetfolder of prepared data:
DSET=data/N500-percentile_max-block-20/
# To train previous model with new data:
python train_segmentation_frompretrained.py --batch_size=1 --lr_min=1e-7 --lr_max=1e-4 --dataset_folder ./${DSET} --epochs 50 --restarts 1 --outdir models-replicate/ --n_levels 4 --downsamp... |
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