sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2716bace2a2026039b70a071e6cf5aa5e955a1a5f92adaf9dce0982c6bf49e2e | Shell | 1,035 | 38 | #!/usr/bin/env bash
# Get UniBind TFBSs for prediction model PWM and peak-caller MACS
UNIBIND="pwm_tfbs.tar.gz"
if [ ! -f ${UNIBIND} ]; then
wget https://unibind.uio.no/static/data/bulk/${UNIBIND}
tar xvfz ${UNIBIND}
fi
# Collapse all TFBSs into a single file
ALLTFBS="tfbs.bed"
if [ ! -f ${ALLTFBS} ]; then
... |
5cff3792c5448cbeccc26c0a5209cefa93cdf9478939ce4765f0e264bdd37ae2 | Shell | 1,036 | 41 | #!/bin/bash
#CONFIG="noscale.toml" #"autoscale.toml"
CONFIG="--configfile singles_multisite_parallel.toml"
RUNTEXT="running the AN Single protocols NoUninnervatedDendrites"
# sequentials:
CELLNAMES="09" # 02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal data_XM13A_nacncoop_pasdend data_XM13A_nacncoop... |
fac2177e47334b608b1ce440665b17054f3e9d650dcc2806693836cd700dcbbd | Shell | 1,037 | 41 | #!/bin/bash
#CONFIG="noscale.toml" #"autoscale.toml"
CONFIG="--configfile singles_multisite_parallel.toml"
RUNTEXT="running the AN Single protocols NoUninnervatedDendrites2"
# sequentials:
CELLNAMES="09" # 02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal data_XM13A_nacncoop_pasdend data_XM13A_nacncoo... |
54c661616be0c3d4380d32073027b265ce60c2178c0af144bba4a17b50ff0f3d | Shell | 1,039 | 36 | #!/bin/sh
# Type of the network to use
NETWORK_TYPE="Attention_Mean"
# NETWORK_TYPE="Arith_Mean"
# NETWORK_TYPE="RNN"
# NETWORK_TYPE="Annotations"
# What to classify:
CLASSIFICATION_KIND="Family" # Compiler Family
# CLASSIFICATION_KIND="Compiler" # Compiler Family + Version
# CLASSIFICATION_KIND="Compiler+... |
5148c14dad5a99550005467a04624c334f873796e5398ccb8bdfef09e492c498 | Shell | 1,041 | 47 |
NET=/home/disk/database/data/ICS_scHIC/f01_frontalCortex/ics_out/UNIQ_LOOP.txt
TAG=N50
MAT=./clst/scATAC_$TAG\_normalized_exp_clustered.txt
INDEX=./clst/scATAC_$TAG\.index
python3 ../src00_ics/step1_BuildIndex.py $NET $MAT $INDEX
nohup python3 ../src00_ics/step2_CalICS_r0.py $INDEX ./clst/scATAC_$TAG\.out.r0 &
... |
923d0c62e90175ec8e75b7e936a4ed87406d40ada8003e91113bda3d9af846b4 | Shell | 1,044 | 45 | #!/usr/bin/env bash
set -e
export REPOSITORY="tpesout"
if [[ ! -z "$1" ]] ; then export REPOSITORY="$1" ; fi
export VERSION="0.1.0"
if [[ ! -z "$2" ]] ; then export VERSION="$2" ; fi
export TAG_KEY="version"
if [[ "$3" == "release" ]] || [[ "$3" == "RELEASE" ]] ; then export TAG_KEY="tag" ; fi
echo "Building and de... |
de4eaed512af7db2e28c981a16acabe64a97e0a6326ad9bf7bf5089c55b3b8b5 | Shell | 1,046 | 27 | #!/bin/bash
IMAGE_NAME="torchserve:1.0"
echo "Starting torchserve:1.0 docker image"
docker run -d --rm -it -p 8080:8080 -p 8081:8081 torchserve:1.0 > /dev/null 2>&1
container_id=$(docker ps --filter="ancestor=$IMAGE_NAME" -q | xargs)
sleep 30
echo "Successfully started torchserve in docker"
echo "Registering resne... |
eaa02ec7132ef0d048cc874e649dfbdd2e7413db4a795ece91cd6bf8be7e1ef2 | Shell | 1,047 | 26 | #!/bin/bash
GLN_START=$(grep "trnF" $2 | awk '{print $2}')
GLN_END=$(grep "trnF" $2 | awk '{print $2}')
GSIZE=$(awk 'BEGIN {FS="\t"} $0 !~ ">" {sum+=length($0)} END {print sum}' $1)
if (( ${GLN_START} > ${GLN_END} )); then
printf "\nThe sequence is likely reversed. Generating reverse-complement.\n\n"
printf "$(se... |
0827cb8ba64d5477472d3a354da5fbbb6f21086d3bdbbb1d0ee993358bf074f0 | Shell | 1,050 | 41 | #!/bin/bash
#CONFIG="noscale.toml" #"autoscale.toml"
CONFIG="--configfile singles_multisite_parallel.toml"
RUNTEXT="running the AN Single protocols Full"
# sequentials:
CELLNAMES="10 17 30" # "09" # 02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_... |
3cf9b48431eff424d52bbcfded3d6b68ffc69d74231b99c1102d039bac07fcfd | Shell | 1,056 | 49 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: map.sh <asm.fasta> <input.fofn> [line_num]"
echo "input.fofn: tab delimited file for R1 and R2 reads. ex. R1.fastq.gz\tR2.fastq.gz"
exit -1
fi
asm=$1
input_fofn=$2
i=$SLURM_ARRAY_TASK_ID
if [ -z $i ]; then
i=$3
fi
if [ -z $i ]; then
echo "No line num provided. Exit."... |
f1cfc036358c612a6a26f7413161f5a15945bc087a93b0b8455f271329f0d8de | Shell | 1,056 | 44 | #!/bin/bash
### CONFIG ###
TARGET_DIR=$1
if [ -z $TARGET_DIR ]; then
echo "Must specify target directory"
exit 1
fi
if [ ! -d $TARGET_DIR ]; then
mkdir -p $TARGET_DIR
fi
file_ids=(
1tPeaQr1cVmSABNCJQsd8OekOZIjpJivj
1apo5VxoZA5m-Ou4GoGR_voUgLN0KKc4g
1yvfjtQV6EnKez6TShMZQq_nkGyY9XA4q
1jvF71hw4ztorvz0FWur... |
1dc19fed7fd4cc8ff626d5669cec68f0f6f486bae14285b567af0010b06b05ed | Shell | 1,061 | 48 | #! /bin/bash
if [ -z $1 ]; then
echo "Usage: ./_submit_mashmap.sh <ref.fasta> <qry.fasta>"
exit -1
fi
fasta1=$1
fasta2=$2
if [ ! -e `basename $fasta1` ]; then
ln -s $fasta1
fi
if [ ! -e `basename $fasta2` ]; then
ln -s $fasta2
fi
genome1=${fasta1/.fasta/}
genome2=${fasta2/.fasta/}
#cpus=32
#mem=24g
cpus=4
me... |
4bd311c503fcaa62d84a8b9318e94bd901483670e156b77153534b8858758925 | Shell | 1,081 | 39 | #!/bin/bash
# name: build.sh
# usage: executed by build.sub
# purpose: streamline the process to build MATLAB code for each job type
# initiate script timing
begin=`date +%s`
# get script to be compiled
job_type=$1
# unpack required code
mkdir func
tar -xzf code.tar.gz --directory ./func
# c... |
68aa393467dce7362e144ffe173791c80b7b161f1f3a84d72de0e9ea7403f9ea | Shell | 1,090 | 21 | # Copyright (C) 2019 Christoph Gorgulla
#
# This file is part of VirtualFlow.
#
# VirtualFlow is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later ve... |
863d8dddc0909bb6cdc7f46e513b144b61f6b4f0d3b391f674840b7ee94ef993 | Shell | 1,094 | 43 | #!/bin/bash
CONFIG="--configfile singles_multisite_parallel.toml"
RUNTEXT="running the PSTH for RevCorr data at 30 dB"
CELLNAMES="02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_actdend"
EXPERIMENT="all" # all=mean max=mean removelargest largestonly... |
64f858a82148f3138b8a4a302dfccdfc45111722c3dc7748736078b2f791c151 | Shell | 1,097 | 43 | #!/bin/bash
CONFIG="--configfile singles_multisite_parallel_0dB.toml"
RUNTEXT="running the PSTH for RevCorr data at 0 dB"
CELLNAMES="02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_actdend"
EXPERIMENT="all" # all=mean max=mean removelargest largesto... |
fce48da08bbb5ef6995ec3560a3048aeff8b4489674b05fc50251f06b071c6e0 | Shell | 1,099 | 41 | #!/bin/bash
#SBATCH --time=24:00:00
#SBATCH --mem=20G
#SBATCH --partition=rbaltman,owners
# # SBATCH --qos=high_p
# Directory definitions
OUT_DIR=/scratch/users/aderry/lmdb/atom3d/small_molecule_properties
XYZ_DIR=$SCRATCH/dsgdb9nsd
START_DIR=$(pwd)
cd $SCRATCH
# Check if the dataset exists already
if [ "$(ls dsgdb... |
a54742f42e21fae8a414a026a2fb03ffa77d7458f297da0dc0fb8e194fab2917 | Shell | 1,102 | 43 | #!/bin/bash
CONFIG="--configfile singles_multisite_parallel_PSTH.toml"
RUNTEXT="running the PSTH for RevCorr data at 30 dB"
CELLNAMES="02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_actdend"
EXPERIMENT="all" # all=mean max=mean removelargest larges... |
283764ea3ff93d59767d37fbaff1ad9e6f2e5ff713c03cc9b1f30ba7c8447682 | Shell | 1,103 | 44 | case $1 in
2a)
python examples/test_mechanisms.py klt
;;
2b)
python examples/test_mechanisms.py kht
;;
2c)
python examples/test_mechanisms.py ka
;;
3)
python examples/toy_model.py
;;
4)
python examples/test_synapses.py ... |
1ca7e3374233c42e374f952db8638422effeb6ab2c5580b9ebb820d38c0451f2 | Shell | 1,104 | 34 | #!/bin/env bash
#
#SBATCH -p all # partition (queue)
#SBATCH -c 1 # number of cores
#SBATCH -t 10 # time (minutes)
#SBATCH -o logs/cnn_preprocess_%j.out # STDOUT #add _%a to see each array job
#SBATCH -e logs/cnn_preprocess_%j.err # STDERR #add _%a to see... |
c21c6afc8791bc41cb6041b2ed765aa2cc018bf9bf115213e96628b610d289d0 | Shell | 1,106 | 25 | # dataset=USPTO50K-aug-untyped
seed=$1
dataset=USPTO50K-aug-untyped_${seed}
dataset_prefix=USPTO50K-aug-untyped
source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate retroxpert_
# don't need for proposing
# python3 $PWD/../../onmt/bin/preprocess.py \
# -train_src $PWD/../../data/${dat... |
2be99f282c6947af8ce1f0ab37602171f1b62f1f67278aa2c2e5d474d6ee6e88 | Shell | 1,110 | 28 | #!/bin/bash -eu
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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 req... |
81fda4ba9f2f7e6dc669a4f19696396fa8911323631e28603bc5623a72ea1140 | Shell | 1,111 | 17 | #! /bin/bash
TMP_DIR=~/.dnnbrain_tmp
mkdir -p $TMP_DIR
# do uva with .nii
db_decode -anal uv -resp $DNNBRAIN_DATA/test/sub-CSI1_ses-01_imagenet_beta_L.nii.gz -bmask $DNNBRAIN_DATA/test/PHA1_L.nii.gz -act $DNNBRAIN_DATA/test/image/sub-CSI1_ses-01_imagenet.act.h5 -dmask $DNNBRAIN_DATA/test/alexnet.dmask.csv -model glm ... |
531ed70ffd908e8f7bb52632a243cafa77c8145e689844aca034b5eaaa36cb46 | Shell | 1,113 | 42 | #!/bin/bash
#CONFIG="noscale.toml" #"autoscale.toml"
CONFIG="--configfile singles_multisite_parallel.toml"
RUNTEXT="running the AN Single protocols Full"
# sequentials:
CELLNAMES="05 06 09 10 11 13 17 18 30" # "02"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_actdend"
DENDRI... |
e6557c10a69777283dbf05f48a195fd9dfcd4642f7254736b4245d21f28edb6f | Shell | 1,114 | 35 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: ./busco.sh <assembly.fasta>"
exit -1
fi
asm=$1
out=`echo $asm | sed 's/.fasta//' | sed 's/.fa//'`
cpus=$SLURM_CPUS_PER_TASK
#source $tools/conda/etc/profile.d/conda.sh
#conda activate busco
module load bamtools
module load blast/2.2.30+ # multithreading ver.
module load... |
e30cc07ac8d8e8619db6f60d3072ed1b307948ebd944ecf3efb38327f9876bd7 | Shell | 1,115 | 17 | #! /bin/bash
TMP_DIR=~/.dnnbrain_tmp
mkdir -p $TMP_DIR
# do uva with .nii
db_encode -anal uv -act $DNNBRAIN_DATA/test/image/sub-CSI1_ses-01_imagenet.act.h5 -dmask $DNNBRAIN_DATA/test/alexnet.dmask.csv -resp $DNNBRAIN_DATA/test/sub-CSI1_ses-01_imagenet_beta_L.nii.gz -bmask $DNNBRAIN_DATA/test/PHA1_L.nii.gz -model glm ... |
8fdb2a639c974b1b8422da1c89daf2fc9aa3fad1f3a95db22077c3d580f193f3 | Shell | 1,120 | 27 | TORCH_VER=1.6.0
CUDA_VER=10.1
CUDA_CODE=cu101
conda create -n rxnebm python=3.6 tensorflow-gpu=1.14 tqdm pathlib typing scipy pandas joblib -y
conda activate rxnebm
conda install -y pytorch=${TORCH_VER} torchvision cudatoolkit=${CUDA_VER} torchtext -c pytorch
conda install -y rdkit -c rdkit
pip install --no-binary :... |
1fe45508fbe12801b7ab114368d01b2fdfb63ad315d5a93094885f57e7deb758 | Shell | 1,139 | 28 | echo "This (experimental) update script will create a new repo according to your config file. It will:"
echo "(1) overwrite your repositories Makefile, ODK sparql queries (your custom queries wont be touched) and docker wrapper (run.sh)."
echo "(2) and add missing files, if any."
set -e
OID=bdso
ROOTDIR=../..
SRCDIR... |
35cd10fed1c4c0c3dad77da72e30835b5e1ffdb4592f4856a4b7671c5702179b | Shell | 1,140 | 29 | #!/bin/bash
id=$1
seq1=$2
seq2=$3
mkdir -p $id
awk '$0 ~ ">" {if (NR > 1) {print c;} c=0;printf substr($0,2,100) "\t"; } $0 !~ ">" {c+=length($0);} END { print c; }' $seq1 | sort -rnk2 > $id/contig_${id}.lengths
longest_contig=$(head -1 $id/contig_${id}.lengths | awk '{print $1}')
awk '/^>/ { print (NR==1 ? "" :... |
511fe527905a490a45a7476c2a0d87a3567b322093da961406aad10c40ba01e5 | Shell | 1,142 | 38 | module load gcc/8.3.0
module load cuda/10.1
source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate openretro_cu101
# second seed
python3 train.py \
--do_train \
--model_name="gln" \
--data_name="schneider50k" \
--log_file="gln_train_vanilla" \
--train_file="./data/gln_schneider50... |
961342063235a7865f35ccc88d94ae2cdc596bfcf4aeb337aac038cd72447117 | Shell | 1,148 | 36 | #!/bin/bash
CONFIG="toml/autoscale_multisite_40dB_parallel.toml"
RUNTEXT="running the individual initialization and running AN PSTH protocols"
CELLNAMES="02 05 06 09 10 11 13 17 18 30"
TABLES="data_XM13A_nacncoop_normal" # " data_XM13A_nacncoop_pasdend data_XM13A_nacncoop_actdend"
EXPERIMENT="all" # all=mean max=mean r... |
f9be141ce330f9a5f89f00bfd1b7c3667105a48984146402effe1bdf1d08e71d | Shell | 1,152 | 42 | #!/bin/bash
name=$1
BMAP1=$2.cmap # BSPQI.cmap
BMAP2=$3.cmap # BSSSI.cmap
ENZYME1=$2 # BSPQI
ENZYME2=$3 # BSSSI
ASM=asm.fasta # ln -s to the asm.fasta
CONFIG=$4
RefAligner=$tools/bionano/Solve3.2.1_04122018/RefAligner/7437.7523rel/avx/RefAligner
module load python/2.7
#### Loading python 2.7
module load perl/5.18.2
#... |
3c5cb943e436d5c300b3e78c53d15bf647597db3d8281a4d5fba8d5d2f1d17fe | Shell | 1,163 | 25 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=2:00:00
#SBATCH --gres=gpu:1 ... |
095616da44615c126532a13992bbca23c40a3f064b02a664cae74865d943f698 | Shell | 1,165 | 25 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=2:00:00
#SBATCH --gres=gpu:1 ... |
1ed4c16193b704c66905b725c48f50c146a63fcf59a4907040dce02780ca9eba | Shell | 1,165 | 22 | #!/bin/bash
python model_run.py VCN_c08 --protocol runANOmitOne --model XM13 -r 10 --sgcmodel cochlea -S MS -a 1.0 --noparallel &
python model_run.py VCN_c09 --protocol runANOmitOne --model mGBC -r 10 --sgcmodel cochlea -S MS -a 1.5 --noparallel &
python model_run.py VCN_c17 --protocol runANOmitOne --model mGBC -r 10 ... |
21d12d1e14e9c2c46725b3d84f61f61cfea06f9a8b690e0412f6abb77615ad5d | Shell | 1,170 | 23 | gmxbacktemp=$GMX_MAXBACKUP
export GMX_MAXBACKUP=-1
gro_file="../ionized.gro"
gro_file=$(readlink -f "$gro_file")
cd $( dirname $(readlink -f "$gro_file"))
echo $gro_file
echo -e 'q' | gmx make_ndx -f $gro_file -o index.ndx
num_groups=$(cat index.ndx | grep "^\[" | wc -l )
SOL_line=$(cat index.ndx | grep "^\[" | awk '/... |
edb756f11a9e08fe7bd841c5f5bf829097bed0c04a006f136fc27148b9ba0762 | Shell | 1,170 | 25 | #!/usr/bin/env bash
# Build the portable Linux x86_64 release archive in Docker.
#
# packaging/linux/build-in-docker.sh [build_release.py options]
#
# Builds the image from packaging/linux/Dockerfile and runs
# packaging/build_release.py --platform linux-x86_64 inside it as the calling
# user. The archive is written ... |
8dc76114f0cd054261ae5bd5cbac33b7e5886f0a76c88891a655223207075940 | Shell | 1,176 | 37 | #!/bin/bash
# Surface based group GLM statistical analysis
# 1. concatenate all subjects
# 2. run glm a simple t test across subjects
# 3. correct for multiple comparision using permutation
# Hengda He, Sept 13 2020
ReD='\033[91m'
YelloW='\033[93m'
EndC='\033[0m'
#codepath="/home/hh2699/Lab/Linbi/Scripts"
#subdir="/h... |
bd4a15f58177007655c6e2db7da7218cb27d8c7db111984652f2ad3d63f52287 | Shell | 1,177 | 33 | #!/bin/bash
# trimmed_bionano_errorneous_N 0.0.1
main() {
echo "Value of input_fastagz: '$input_fastagz'"
echo "Value of species_id: '$species_id'"
echo "${input_fastagz_name: -3}"
if [[ "${input_fastagz_name: -3}" == ".gz" ]]; then
dx download "$input_fastagz" -o input.fasta.gz
... |
c8434768dfd10cc3ed755a3b33a42933e659a611879cde22dbe1672c3b2f8b38 | Shell | 1,177 | 28 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate neuralsym
sym_seed=$1
{
python infer_all.py \
--csv_prefix 50k_1000000dim_2rad_to_32681_csv \
--labels_prefix 50k_1000000dim_2rad_to_32681_labe... |
0959bf90ae183ed86b362be458b345bd8f0ed422b5135fc45a20021ae1cab183 | Shell | 1,185 | 25 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=2:00:00
#SBATCH --gres=gpu:1 ... |
5579f43185af8eae69256896963691758c488d7d1620db38c171562155abf38e | Shell | 1,186 | 25 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=2:00:00
#SBATCH --gres=gpu:1 ... |
e196d89f28ed33a0ccffc87fc9d1abd1223fea6844dc1da2888c2345c9020cf5 | Shell | 1,187 | 25 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=2:00:00
#SBATCH --gres=gpu:1 ... |
ffe4fe7d06283433a6428c41ecd45a6a2dff9d09b43d65774605c657a3ed9f15 | Shell | 1,191 | 47 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: ./_submit_mash.sh <genome>"
echo "Requires: input.fofn"
exit -1
fi
if [ ! -e input.fofn ]; then
echo "Requires: input.fofn"
exit -1
fi
LEN=`wc -l input.fofn | awk '{print $1}'`
genome=$1
mkdir -p logs
partition=quick
cpus=2
mem=2g
name=$genome.mash
script=$VGP_PIPE... |
9ac004dfb94ed7f8c62623243b7f42a4885ddbb077d81e347dd8cf7e3930028f | Shell | 1,192 | 32 | #!/bin/bash
# do only cells with morphology
# ONLY "A" grade cells with complete dendrites:
# gradeA = [2, 5, 6, 9, 10, 11, 13, 17, 24, 29, 30]
FILES="02 05 06 09 10 11 13 17 24 29 30"
proto="initIV"
echo "running the individual initialization or IV protocols"
for f in $FILES
do
echo $f
python vcnmodel/mod... |
8050dc98a92204f4fd1d64eeaf6527b7bd4e5a5a2be6ba934b0e3dc4de97273e | Shell | 1,193 | 36 | #!/bin/env bash
#
#SBATCH -p all # partition (queue)
#SBATCH -c 1 # number of cores
#SBATCH -t 10 # time (minutes)
#SBATCH -o logs/cnn_postprocess_%j.out # STDOUT #add _%a to see each array job
#SBATCH -e logs/cnn_postprocess_%j.err # STDERR #add _%a to s... |
6da1e4d44ee8d9072a5f98d153bacd47597508da9850b76f6a0a58b438872b6b | Shell | 1,194 | 31 | #!/usr/bin/env bash
#
# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... |
a6efb9d9a26985c0bd0e238e7bacbb211aaba7ccc71d5717d99080e24992ef28 | Shell | 1,206 | 37 | #!/usr/bin/env bash
# Copyright (C) 2019 Christoph Gorgulla
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# This file is part of VirtualFlow.
#
# VirtualFlow is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Fre... |
56f31cc5e4c23dea2938cdfd6d98c920e46507e7f73dd9ae344af35c2a6e9ca7 | Shell | 1,220 | 48 | #!/bin/bash
set -e -x -o pipefail
MAX_THREADS=16
main() {
mv gen_histogram.Rscript /usr/scripts/
dx download "${bam}" -o "subreads.sorted.bam"
dx download "${genome}" -o "${genome_name}"
if [[ "${genome_name}" == *.gz ]]; then
dx download "${genome}" -o - | zcat | python check_contigs.py >... |
76ba2febb91cc217e32aed9e14fcea7370421f74331e54ff6d67406f765dd264 | Shell | 1,225 | 41 | # Example:
# scripts/test_IVs_thr.sh run all
#
#######################################################
# Full models are from data/reconstuctions Matthew Kersting sent on
# March 6, 2020.
# Note we do not have a full reconstruction for cell 18
# in that dataset.
# This script runs to get the thresholds for current i... |
14ed0eddfd6808c960d20f3e05f76a2b5fbaace27a37f21a04ba4aa147ccda1d | Shell | 1,235 | 38 | #!/usr/bin/env bash
sudo apt-get install python3.7
sudo apt-get install python3-pip
pip3 install torch==1.6.0+cpu torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
sudo apt-get install git
git clone https://github.com/pytorch/fairseq
cd fairseq
sudo pip3 install --editable ./
cd ..
git clon... |
ccd04be16fd554ffa9b6d6e735972c57c4dc8efb233377dbe2e48576d34f5dc4 | Shell | 1,238 | 40 | #!/bin/bash
PBS_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <reads_dir> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <queue>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on bic"... |
e16aa6eab85b8daa64f2784e55495a18776e17d0c8fc7a7e78b99f903b966438 | Shell | 1,238 | 34 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# multi-GPU is unnecessary for FeedforwardEBM, and in fact slows it down greatly due to inter-GPU communication
# overhead as the model is very large
ebm_se... |
92da80caed6f43c5377b72445dedfcaba90966a0c394d6d70f51cee77a3d1dc8 | Shell | 1,240 | 40 | #!/bin/bash
PBS_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <reads_dir> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <queue>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on bic"... |
bf777c99312ef13369c66afec0ea8de56fd122eb4b3d6f2ed564af80ae0ec01c | Shell | 1,240 | 40 | #!/bin/bash
PBS_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <reads_dir> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <queue>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on bic"... |
16ebaeb2a5d24843e600a53eed54c19499e8bc84d90d1a525bbcf7255e5dc855 | Shell | 1,241 | 50 | #!/bin/bash
echo "Usage: ./ast.sh <input.fofn>"
input=$1
echo $input
if [[ -z $1 ]]; then
echo "input.fofn required. Exit."
exit -1
fi
fln=`wc -l $input | awk '{print $1}'`
echo "$fln bnx found."
if [[ ! -s bn.bed ]]; then
if [[ "$fln" -gt 2 ]]; then
echo ">2 bionano enzymes found."
ls bnx_*/bionano_*.bed > be... |
df5b1ec87c74583a1c71a2659f181f04ff9a53a1acfa32eeb08263664e5097cb | Shell | 1,243 | 40 | #!/bin/bash
PBS_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <amplicon_file> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <queue>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on ... |
9cfac6c1077b19b93e82dc5b2f22ea4281cd2d704d15102948fb103ab264997e | Shell | 1,251 | 33 | #!/bin/bash
# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... |
6f73eb509c7746bfabf904ccde09b02578d4c086f6691253ea0be1cb719f11bd | Shell | 1,255 | 30 |
#TAG=100k
#TAG=200k
#TAG=300k
TAG=400k
SRC=/home/disk/database/data/scHIC/GSE130711_analysis/src/coolLoopCount.py
BEDPE=./scATAC_loop_$TAG\.txt.bed
OUT=./coolCount_$TAG\/
mkdir $OUT
TAG=Astro
COOL=/home/disk/database/data/scHIC/GSE130711_cool/Human_cluster_cool/$TAG\_all_brain.txt_1kb_contacts.cool
nohup python3 $SRC... |
6a666063c3129dbcc3287707378dd2385b907c27c015bc87e1879cf880002df5 | Shell | 1,256 | 33 | #!/usr/bin/env bash
#
# Copyright 2026 The TensorFlow Authors. All Rights Reserved.
#
# 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
#
# Unle... |
fa8453a4d40dab01562d6a6dd82e90807a5f986b14853be81a88ff8d4e0749fd | Shell | 1,260 | 39 | #!/bin/bash
# Assumes we're in the repo directory
# Create subdirectory for data
mkdir data
mkdir data/raw data/seurat data/anndata
# Next, download raw datasets into /raw
cd data/raw
# Mouse data from Tasic et al.
echo "Download dataset 1/4: mouse"
mkdir tasic
cd tasic
wget https://celltypes.brain-map.org/api/v2/w... |
826fc3360006439d0a95c9463343039d9105a08ce2f15aa043498b6f3f4ef8a9 | Shell | 1,267 | 35 | #!/usr/bin/env bash
# Copyright 2026 DeepMind Technologies Limited
#
# 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 ... |
32129e53130b4f1a7346db464e3365bf5278e564654a26750d74d3b6a94098fd | Shell | 1,278 | 37 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# multi-GPU is unnecessary for FeedforwardEBM, and in fact slows it down greatly due to inter-GPU communication
# overhead as the model is very large
ebm_se... |
cf3122031b54e9ba2d3860157363e60aad1541831d67ab1130556d386dcaba24 | Shell | 1,281 | 30 | #!/usr/bin/env bash
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# 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
#
# Unle... |
51850fb96bcaec2aed10ad48014efbbb35d217f3667e38b1298a5e2d09fc9dd3 | Shell | 1,288 | 36 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# multi-GPU is unnecessary for FeedforwardEBM, and in fact slows it down greatly due to inter-GPU communication
# overhead as the model is very large
ebm_se... |
1aa4c803d1e2996d52d35e194affac4996f8453eb28311828c66cd69b73621e9 | Shell | 1,290 | 33 |
:<<!
python3 ../src00_ics/step1_BuildIndex.py net.txt mat.txt ics_out/this.index
python3 ../src00_ics/step2_CalICS_mean.py ics_out/this.index ics_out/this.out.mean
python3 ../src00_ics/step2_CalICS_hmean.py ics_out/this.index ics_out/this.out.hmean
python3 ../src00_ics/step2_CalICS_ori.py ics_out/this.index ics_... |
916dd52789ff88f8fd464d29238d36e52dd8b0fedae46937f9374c419b80e943 | Shell | 1,291 | 25 | #!/bin/bash
function analyze {
python generate_mini_dataset.py \
-p ${PROTEIN} \
-c ${CHROM} \
-g ${GENOME} \
--prefix ${PREFIX}
}
PROTEIN=/lisc/scratch/molevo/dts/ODP_genomes/GenDB_annotated_chr/odp_ncbi_genome_db/output/source_data/annotated_genomes/GCF_022113875.1/GCF_022113875.... |
b913e6aaa71ee4b840c8838372109d17eed7823d07be98c99a2c221bc4369d23 | Shell | 1,293 | 32 | #USAGE
# bash gromacs_scripts/make_psf.sh ionized.pdb ionized.psf
#may need to edit globs or membs to specify right tpr file
gmx editconf -f ions.tpr -o ionized.pdb -conect
cat $1 | grep -v END | grep -v SOL | grep -v "\sK\s" | grep -v "\sCL\s" | grep -v "\sNA\s" > connected.pdb
cat ionized.pdb | grep -v END | grep -E ... |
4d97b9a7547e2709e9c081021c7ad169d13a2b6193234821f15499a9a59cda61 | Shell | 1,294 | 39 | set -e # force failure if anyting fails in script - ensuring completion
set -o errexit
ENVNAME="vcn_venv"
if [ -d $ENVNAME ]
then
echo "Removing previous environment: $ENVNAME"
set +e
rsync -aR --remove-source-files $ENVNAME ~/.Trash/ || exit 1
set -e
rm -R $ENVNAME
else
echo "No previous enviro... |
4ce323122fe03d8782db1b2c3cdc96ece10feffd6071d04f695565f4da6a4624 | Shell | 1,300 | 36 | #!/usr/bin/env bash
# Check that a macOS release binary is portable.
#
# packaging/macos/check_binary.sh <bin/baysor> <deployment-target>
#
# Fails unless the binary is arm64, its minimum macOS version (LC_BUILD_VERSION
# minos) is at most <deployment-target>, and every linked dylib is a system
# library (/usr/lib, /... |
8176fff7dfa79eb170bb3f007124a92a3e9332b5960c41067cb59fcfbf366bf5 | Shell | 1,300 | 36 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# multi-GPU is unnecessary for FeedforwardEBM, and in fact slows it down greatly due to inter-GPU communication
# overhead as the model is very large
ebm_se... |
c6b2c2cebacd43a169c3cd2625078a333dc3b1200d72b81d368b6a2f6af0c05a | Shell | 1,305 | 37 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: ./meryl_build.sh <k-size> <input.fofn> [num_line]"
exit -1
fi
num_line=$SLURM_ARRAY_TASK_ID
if [ -z "$num_line" ] ; then
num_line=$3
fi
k=$1
fastq=`sed -n ${num_line}p $2 | awk '{print $1}'`
name=`echo $fastq | sed 's/.fasta.gz$//g' | sed 's/.fq.gz$//g' | sed 's/.fasta... |
628784e5f12453063b85be3ba5eb6061e1cc4a0d7739aa686b3154c87076f5bd | Shell | 1,311 | 49 | #!/bin/bash
folder_name=${1%/}
UpdateLog.sh $folder_name delete_tracks HEAD_NODE START Deleting_Analysis_Files
declare -a files_removed
count=0
files_to_remove=(
'tracks.mat'
'processed.avi'
'processed.mp4'
'embeddings.mat'
'spectra.mat'
)
# remove all the files in the analysis folder
if ... |
620048a32bc83790af8be9b86163388113d417b6f73965bd605625c2a7714584 | Shell | 1,333 | 27 | #!/bin/bash
# python model_run.py VCN_c08 -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
# python model_run.py VCN_c09 -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
# python model_run.py VCN_c09h -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
#python model_run.py VCN... |
5aeaabacafd28cb17336d4c6f6b9e058794347415957d19d5bcc39448e2d05ab | Shell | 1,337 | 42 | #!/bin/bash
BMAP1=BSPQI.cmap # DSPQI.cmap
BMAP2=BSSSI.cmap # BSSSI.cmap
ENZYME1=BSPQI # BSPQI
ENZYME2=BSSSI # BSSSI
ASM=asm.fasta # ln -s to the asm.fasta
CONFIG=/data/Phillippy/tools/bionano/Solve3.2.1_04122018/HybridScaffold/04122018/TGH/hybridScaffold_two_enzymes.xml
RefAligner=/data/Phillippy/tools/bionano/Solve3.... |
94a095204d48abb8869575fdc587e1cfb712746a43af4ab7b0b94d372660ab26 | Shell | 1,338 | 42 | #!/bin/bash
BMAP1=DLE1.cmap # DLE1.cmap
BMAP2=BSSSI.cmap # BSSSI.cmap
ENZYME1=DLE1 # DLE1
ENZYME2=BSSSI # BSSSI
ASM=asm.fasta # ln -s to the asm.fasta
CONFIG=/data/Phillippy/tools/bionano/Solve3.2.1_04122018/HybridScaffold/04122018/TGH/hybridScaffold_two_enzymes_DLE1.xml
RefAligner=/data/Phillippy/tools/bionano/Solve3... |
6b5ecfd7d80745660e3484ba33fbaba6c4b11f02073318c3eb41b8333e0a15fb | Shell | 1,341 | 43 | set -e # force failure if anyting fails in script - ensuring completion
set -o errexit
ENVNAME="vcn_venv"
if [ -d $ENVNAME ]
then
echo "Removing previous environment: $ENVNAME"
set +e
rsync -aR --remove-source-files $ENVNAME ~/.Trash/ || exit 1
set -e
rm -R $ENVNAME
else
echo "No previous enviro... |
c2cddbfd0a64eee77870d6b0af34a2ff5939fee23d4038d848c88e85a81563ad | Shell | 1,344 | 42 | #!/bin/bash
set -e
echo "Usage: ./dedup.sh <alignment.bam> <threads>"
module load samtools/1.9
module load picard/2.9.2
bam=$1
mkdir -p sort_dedup
bam_prefix=`basename $bam`
sort_bam='sort_dedup/'${bam_prefix/.bam/.sort.bam}
dp_bam=${sort_bam/.bam/.dp.bam}
resort_bam=${dp_bam/.bam/.sort_n.bam}
threads=$2
#:<<'END... |
cbc9250c5cfb0384213993599270f153e0cdb8225b28796782b87ece371c6001 | Shell | 1,348 | 43 | #!/bin/bash
SLURM_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <reads_dir> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <qos>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on tars... |
7708e2e9fc4ab713a281f912cbd2c7364dd4017e69b84e18ec5db14732e8c531 | Shell | 1,349 | 29 | #!/bin/bash
#minimisation
gmx grompp -f memb0.mdp -o memb0.tpr -c ionized.gro -r converted.gro -p topol.top
gmx mdrun -v -deffnm memb0
#eq
#for i in $(seq 1 15);
#do
# echo $i
# gmx grompp -f memb$i.mdp -o memb$i.tpr -c memb$(( $i - 1 )).gro -r converted.gro -n index.ndx -p topol.top 2>&1 | tee memb$i\_set... |
274333bd9dfaded10160ba5e6d0a04fe0e673011bd165134442f6bc08b10cc94 | Shell | 1,350 | 44 | #!/bin/bash
SLURM_SCRIPT=$HOME/masque_submission.sh
#Check arguments
if [ $# -ne 7 ]
then
echo "Usage: $0 <reads_dir> <output_dir> <contaminants> <project-name> <nb_cpu> <email> <qos>"
echo "contaminants: danio,human,mouse,mosquito,phi (add contaminants separated by comma)"
echo "nb_cpu: max is 12 on tars... |
6829aa58280344c2720e1dfe68368a85204a69a36abc573c5694a84dbb153526 | Shell | 1,351 | 33 | #!/bin/bash
mkdir -p ${3}
mkdir -p ${3}/alignments
mkdir -p ${3}/counts
LN=$(tail -1 $1 | tr -d "\n" | wc -c)
JUMP=10
python edit.py ${1} ${2} ${3} ${JUMP}
original=$(( $(wc -l ${4} | awk '{print $1}') / 4 ))
original_gbp=$(awk 'BEGIN{sum=0;}{if(NR%4==2){sum+=length($0);}}END{print sum;}' ${4})
printf "\nstarting... |
da67b3f464eba45d4f4da6c0ce63bbb6c7cff9a7cd855c9de8921e57e50e1429 | Shell | 1,352 | 44 | # ensure conda is properly initialised, such as using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# for multi-GPU, choose any number (0-65535) for port
ebm_seed=$1
python trainEBM.py \
--ddp \
--nodes 1 \
--gpus 4 \
--nr 0 \
--port 42213 \
--mod... |
839c4f9107dee3acb681aeeee0fa0edc2e89ae780262900c0ccd0ad5fd250110 | Shell | 1,367 | 43 | #!/bin/bash
# Originally from https://github.com/edenton/svg,
# Modified by Ani Karapetyan and further modified here.
TARGET_DIR=$1
CLASSES="boxing handclapping handwaving jogging running walking"
IMG_SIZE=64
IMG_STR="${IMG_SIZE}x${IMG_SIZE}"
### DOWNLOAD ###
if [ -z $TARGET_DIR ]; then
echo "Must specify target d... |
a63ce81586b8542f544182bd737ee21bea28696b6f1f72e11e226489713fa3fe | Shell | 1,370 | 33 | #!/bin/bash
#initialization, here, is unbiased
count=0
for x in phantomAwmgm.jpg phantomBwmgm.jpg phantomCwmgm.jpg phantomDwmgm.jpg phantomEwmgm.jpg phantomFwmgm.jpg phantomGwmgm.jpg phantomHwmgm.jpg
do
count=`expr $count + 1` # Increment the counter
echo " count is $count and file is $x "
ANTS 2 -m P... |
55b25d3a00ffc2b7efe9fa863628589675a759f7ece9b41ebdcf663e4891c2ec | Shell | 1,378 | 36 |
NET=/home/disk/database/data/scHIC/Blood/analysis/scATAC_loop.txt
MAT=/home/disk/database/data/scHIC/Blood/analysis/scATAC_normalized_exp_clustered.txt
INDEX=/home/disk/database/data/ICS_scHIC/f02_blood/ics_out/this.index
python3 ../src00_ics/step1_BuildIndex.py $NET $MAT $INDEX
nohup python3 ../src00_ics/step2_... |
d81cdabc3b1a6e0a4ddd8abe22b98242d17306d53f72dd009c3561619601fb08 | Shell | 1,397 | 49 | #!/usr/bin/env sh
# run at NIF-Ontology commit: 4594e88e4127886a850353d138bf8ec24f20804a
WD=~/git/NIF-Ontology/ttl/
FILES="NIF-Molecule-Role-Inferred.ttl
NIF-Molecule.ttl
NIF-Chemical.ttl
NIF-Molecule-Role-Bridge.ttl"
old_chebi="@prefix chebi: <http:\/\/purl.obolibrary.org\/obo\/chebi.owl#> ."
new_chebi="@prefix CHEB... |
5a04766b210c6353c336b3e7fcee15d17714f5a1d1a070460514c8c2a35a725c | Shell | 1,399 | 24 |
BEDPE=PDGFRA_TSS_hg19.1k.LOOP.tss.bed.demo.bed
SRC=/home/disk/database/data/scHIC/GSE130711_analysis/src/coolLoopCount.py
OUT=./demo_signal/
TAG=Astro
COOL=/home/disk/database/data/scHIC/GSE130711_cool/Human_cluster_cool/$TAG\_all_brain.txt_1kb_contacts.cool.fithic/matrix_10k.h5.norm.cool
nohup python3 $SRC $COOL $BE... |
1c9ef46776dc42999745b9a8f68735db1e64bdfec986984a6d7dbffefd31aebe | Shell | 1,425 | 34 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=24:00:00
#SBATCH --gres=gpu:1 ... |
360daec4a29c80113d99a033fd25a02241b7b0353b0086db1555c97aabf16fe5 | Shell | 1,425 | 49 | #! /bin/bash
if [ -z $1 ]; then
echo "Usage: ./_submit_purge_haplotigs.sh <name> [lmh]"
echo -e "\tRequires aligned.bam"
echo -e "\t[lmh]: file with l m h values on the beginning of each line."
exit -1
fi
mkdir -p logs
if ! [ -e aligned.bam ]; then
echo "Requires aligned.bam. Exit."
exit -1
fi
waitfor=""
if !... |
8ea0c808255cf6ddedf0c7161237ac54b2fa4746e1a96f1ea8813f3fb6460ddc | Shell | 1,429 | 47 | # ensure conda is properly initialised, such as by using the line below
# source /cm/shared/engaging/anaconda/2018.12/etc/profile.d/conda.sh
conda activate rxnebm
# for multi-GPU, choose any number (0-65535) for port
ebm_seed=$1
python trainEBM.py \
--ddp \
--nodes 1 \
--gpus 4 \
--nr 0 \
--port 29912 \
--... |
3795009ef7d4c29439d915e05ffa20fb2ef9794686179182ce39b460fa517fc2 | Shell | 1,437 | 52 |
MAT=/home/disk/database/data/scHIC/GSE130711_analysis/scATAC_normalized_exp_clustered.txt
TAG=100k
NET=./scATAC_loop_$TAG\.txt
INDEX=./ics_out/scATAC_$TAG\.index
#python3 ../src00_ics/step0_uniqNet.py $NET $NET\.uniq
nohup python3 loop2bedpe.py $NET\.uniq $NET\.bed &
#python3 ../src00_ics/step1_BuildIndex.py $NET\.u... |
2d64ab827858d927d27de390a5a944b186fdb41f3d97edcf340bf1f4a1548539 | Shell | 1,441 | 49 | #!/bin/bash
k=$1
prefix=$2
filelist=$3
for file in $(cat $filelist); # if file must be merged by $prefix: $(grep --color=never $prefix $filelist)
do
name=${file/.fastq.gz/}
name=${name/.fq.gz/}
name=${name/.fastq/}
name=${name/.fq/}
indb=$indb" -s $name.$k"
done
mrg=$prefix.k$k
if ! [ -e $mrg.mcdat ]; then
ec... |
80feabeffb54cd157add5c9e2b5a243b0fd06cb3c9ccb3fdd5e5af978abf4bbd | Shell | 1,448 | 47 | # Example:
# scripts/test_IVs_thr.sh run all
#
#######################################################
# Full models are from data/reconstuctions Matthew Kersting sent on
# March 6, 2020.
# Note we do not have a full reconstruction for cell 18
# in that dataset.
# This script runs to get the thresholds for current i... |
76214b51492cd2e9179640c671783b9c53af86785fa7ebdd765f005aa7ca61a4 | Shell | 1,455 | 63 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: ./minimap2 <ref>"
echo " Assumes we have <ref> and <input.fofn> in the same dir"
exit -1
fi
module load minimap2/2.11
module load samtools
ref=$1
ref=`echo $ref | sed 's/.fasta$//g' | sed 's/.fa$//g' | sed 's/.fasta.gz$//g' | sed 's/.fa.gz$//g'`
preset="$3"
if [ -z ... |
9cc352a28fbf8409530a8e367e02a3482bf4263069a5c21cbcc54b72e1f414a6 | Shell | 1,459 | 36 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=10:00:00
#SBATCH --gres=gpu:1 ... |
66550d92b459f7f7c2ef9d2637373ed5eb0e54639560d4f0ab151c47d4fcd162 | Shell | 1,464 | 50 | #!/bin/bash
if [ -z $1 ]; then
echo "Usage: ./ast.sh <gaps.bed> [mean_cov]"
echo " When [mean_cov] is not provided, ast_10x will run twice to get the mean_cov"
exit -1
fi
ls aligned.bam
gaps=$1
mean_cov=$2
platform=10x
if [[ -z $mean_cov ]]; then
echo "First round to get mean_cov"
if [[ -s $platform.bed ]]... |
6f4fad70c4010186552b14b8f9f521156c3c9683945b93b783bc70dc0af24513 | Shell | 1,469 | 37 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=35:00:00
#SBATCH --gres=gpu:2 ... |
773543933dbe1471ad6e8d8c41942627749dfa9d65e126adec7658972bec16af | Shell | 1,473 | 28 | #!/bin/bash
# python model_run.py VCN_c08 -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
# python model_run.py VCN_c09 -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
# python model_run.py VCN_c09h -M ${model} -T Bushy --sgcmodel cochlea -S MS -r 20 -P initAN &
#python model_run.py VCN... |
5c8cab0dedfb456c63b66a1f1a3996ad1b7107e6528deefbcc56aeaec09d5f23 | Shell | 1,474 | 37 | #!/bin/bash
#SBATCH -n 1 # number of comands issued in batch script at any times
#SBATCH --cpus-per-task=8 # number of cores to allocate each task
#SBATCH -N 1 # Request 1 node
#SBATCH --time=35:00:00
#SBATCH --gres=gpu:2 ... |
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