sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a4fa9650099a4804f5134efcf8629d466c5e8966331384c28873aeee30a03354 | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_5"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/53af3fb7d6564949bb2cb8129ddadb94/artifacts/final_model"
clinical_dir="/pro... |
b9e02b78526850d01c08e91ef9dbe8b33bb70797be823c70bb160c0f508545ea | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_3"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/35b6574d72bc4ba6ab0aeffd872375c4/artifacts/final_model"
clinical_dir="/pro... |
d003bfab7b04782aa9a6bb904d8763043c0bd719b6352410a3bc400be32356a0 | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_4"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/cb7a0db6883141d7b8c35bc8e9f7ecfd/artifacts/final_model"
clinical_dir="/pro... |
d75b8e9400c6606093ebbbc971ab6cfac955a50eff7f87d35a24e88eeb964753 | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_0"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/21345d0794cc4f96a0bae2f9b9863772/artifacts/final_model"
clinical_dir="/pro... |
eb7d2531b0c0760b8a62a18c2d23386b1ea4548d8b9bbf558b4711c17aa8a2da | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_2"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/2808de27b94245098bfee8b318b98289/artifacts/final_model"
clinical_dir="/pro... |
f9f6ecbdcce43d83336f51a9f82fab41436d43449fc0dc83a71a63b599b5e082 | Shell | 1,004 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ABIDE2_6"
val_list="/project/data/participants_ABIDE2.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/9235ae0b3134441db12eeab8ed71c9c3/artifacts/final_model"
clinical_dir="/pro... |
a0f2393a9cb29f3e55cebf6acd2d8cf940e326c502725a739f366e21c4bd7c0e | Shell | 1,005 | 29 | #!/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 )
cd $SCRIPT_DIR
if [ -z "${RECODIR:-}" ]; then
RECODIR="$(readlink -e $SCRIPT_DIR/../)"
fi
SRC=$RECODIR/21_recos_rt/vol0056_vis1_s... |
31ed6e68a567330972b6c7d17ce88c541d3cb80f65ed5594e529cd652f342dc8 | Shell | 1,006 | 34 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_6.out
source activate mlfold
folder_with_pdbs="../inputs/PDB_homooligomers/pdbs/"
output_dir="../outputs/example_6_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_parsed_chains... |
742c5013d25636542e129efbcfce3b5ec14e68bbba6558c14f02ee4cda4b7e71 | Shell | 1,006 | 29 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR
if [ -z "${RECODIR:-}" ]; then
RECODIR="$(readlink -e $SCRIPT_DIR/../)"
fi
SRC=$RECODIR/21_recos_rt/vol0082_vis1_s... |
0f75285b2eb295ff8df4fd85bc69ff6914e70618452cf31c965b393ea15adcc9 | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_5"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/53af3fb7d6564949bb2cb8129ddadb94/artifacts/final_model"
clinical_dir="/p... |
38dfd61d74958a099189a9bbe184ea5511128bcd84a0c2f5333784f19211bbe0 | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_6"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/9235ae0b3134441db12eeab8ed71c9c3/artifacts/final_model"
clinical_dir="/p... |
413cf9bdd575662f614a4e4edf27950b70cad5c4cc1f4d36aeffb4d47e9bca84 | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_7"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/0eec80ccae54424cab868254b5b16863/artifacts/final_model"
clinical_dir="/p... |
4b1ab4194d3184db340f180a090cea50e6084bced9fd869771661afe9fa187d0 | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_0"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/21345d0794cc4f96a0bae2f9b9863772/artifacts/final_model"
clinical_dir="/p... |
a77fb19758ebcd1b2e70dfd8a1d778bac14f7d87205ce27f61da2b698f862c3c | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_1"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/8a31ee99a94844bda45029a2ad8d9fd6/artifacts/final_model"
clinical_dir="/p... |
bc83fa26f10db708477bfb22e2ca2240fed47a0c3766bed73715d01a5389fefd | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_4"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/cb7a0db6883141d7b8c35bc8e9f7ecfd/artifacts/final_model"
clinical_dir="/p... |
c36d7c3b7eeae4c6ded3b0b5d3030257395b7bfd973758ed470e14d9a30321ba | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_3"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/35b6574d72bc4ba6ab0aeffd872375c4/artifacts/final_model"
clinical_dir="/p... |
d8d0a5225d2bf051c17f9f7ecfcedc957412ba8e1c117fa13dd35cfa3473d97f | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_2"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/2808de27b94245098bfee8b318b98289/artifacts/final_model"
clinical_dir="/p... |
fb9efa9cc72083e6f026eaada09770582167ca697bc9ad43101ce852b862ef8f | Shell | 1,008 | 30 | #!/bin/bash
seed=2
run_dir="get_likelihood_ADHD200_8"
val_list="/project/data/participants_ADHD200.tsv"
latent_resolution="low"
vqvae_uri="/project/mlruns/0/f89cb9ee1a824324b04df9f4b7a8e430/artifacts/final_model"
transformer_uri="/project/mlruns/0/281c9ece0d8f44d6b05f4ce1836fda35/artifacts/final_model"
clinical_dir="/p... |
6b71c8bd7ad99fdb8be3f68ef1f2db59d0fa0a5699318a0ebf94a8a8843925c2 | Shell | 1,012 | 11 | #!/bin/bash
# Here, we're designing binders to insulin receptor, without specifying the topology of the binder a prior
# We first provide the output path and input pdb of the target protein (insulin receptor)
# We then describe the protein we want with the contig input:
# - residues 1-150 of the A chain of the target... |
a7ee67e569693563e803000d95ec2eca54bd10e1f7fe5c9bb86ffb864a090003 | Shell | 1,013 | 34 | #!/bin/bash
#
#SBATCH --mail-type=ALL
#SBATCH --mail-user=tsoelter@uab.edu
#SBATCH --job-name=CellRanger
#SBATCH --ntasks=4
#SBATCH --mem-per-cpu=64000
#SBATCH --nodes=1
#SABTCH --cpus-per-task=4
#SBATCH --time=4-00:00:00
#SBATCH --share
#SBATCH --partition=long
#SBATCH --error=%A_%a.err.txt
#SBATCH --output=S%A_%a.out... |
9e440ef4029d484f6807b941273461aac0a4970c44cfedb861eb3a7acb710b5e | Shell | 1,014 | 26 | # Load the sequenza_conda.yaml environment
# Paths
hg38_ref_path = "" # Path to the reference genome FASTA
ref_dir_path = "" # Path to GC content reference
bam_loc_path = "" # Location of the bam files
results_path = "" # Where you'd like the results to go
# calculate GC content (once)
sequenza-utils gc_wiggle -f ... |
6d3025d76d71c274e9ab9e46407d46074229478461a4ee5f8a28912a538454fd | Shell | 1,017 | 27 | #!/bin/bash
#Purpose: Create SNR maps using fslmaths.
#Input: CBIG2016 preproc output.
#Output: SNR maps.
#Written by M. Peterson, Nielsen Brain and Behavior Lab under MIT License 2023
#PATHS:
CODE_DIR=/fslgroup/fslg_spec_networks/compute/code/Utah_analysis/tSNR/ALL
PREPROC_DIR=/fslgroup/grp_proc/compute/Utah_analys... |
ed748218a81af183de6da047662f687e9eb1937d594500cc244053243f504f2d | Shell | 1,019 | 43 | #eqtl
#nominal
for i in Ast End Mic Ex In Oli Opc Per
do
echo $i
mkdir -p nominal/$i
parallel -j 6 QTLtools cis --vcf geno/snp.{}.vcf.gz \
--bed pheno/$i/$i.chr{}.bed.gz \
--cov cov/$i.xls \
--out nominal/$i/$i.chr{} --nominal 1 --std-err ::: {1..22}
done
#permutation
for i in Ast End Mic Ex In Oli Opc Per
do
echo $i... |
1c7601aa21238fe00da2f95d628c5f64cc0d6015d2ae04d5ad2b9a51bd06f199 | Shell | 1,025 | 47 | #!/bin/sh
gpu=(3 3 3)
PDE='swe'
field_dim=3
scale_factor=2
HR_resolution=128
LR_resolution=$((HR_resolution / scale_factor))
suffix_list=(
"${PDE}_LRinput_supervised_SRCNN_bicubic_init_s_${LR_resolution}to${HR_resolution}"
)
data_frac_list=(
"1/20"
)
for ((i=0; i<1; i++)); do
(
CUDA_VISIBLE_D... |
5d695a32d5c9ca784c3d49e55b2911f11bccd58f86ae0fc2bb5299092e04d978 | Shell | 1,027 | 46 | #!/bin/sh
gpu=(4 0 2)
suffix_list=(
"LRinput_supervised_SRCNN_bicubic_init_s_64_L_2pi_unsupervise_finetune"
)
experiment_dir_list=(
"path to the root folder of the trained model"
)
data_frac_list=(
"1/16"
)
for ((i=0; i<1; i++)); do
(
CUDA_VISIBLE_DEVICES=${gpu[i]} \
python ../src/m... |
20b6d31182c9b442104b59d3504791c672426550bd8ff50936fd7d2e4063e208 | Shell | 1,031 | 20 | #!/bin/bash
# Script to copy NM dicom images to a folder to be shared with SDN Lab
for sub in 1001 1002 1003 1004 1006 1007 1009 1010 1011 1012 1013 1015 1016 1019 1021 1240 1242 1243 1244 1245 1247 1248 1249 1251 1253 1255 1276 1282 1286 1294 1300 1301 1302 1303 3101 3116 3122 3125 3140 3143 3152 3164 3166 3167 3170 ... |
b221436ea2da686d1fbab15142ac69510706b6ade7ee7e14d919485fce28f0e2 | Shell | 1,032 | 45 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
export BART_COMPAT_VERSION="v0.9.00"
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
NET=$(readlink -f $1)
cd $NET
source config.sh
BAS=$(readlink -f basis)
if ! [ -z ${MSK+x} ]; ... |
84534436ecd20e3a512ec2371ca641b282fb0186df13de39b85202ce0f5b91b3 | Shell | 1,034 | 53 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
SVG=$(readlink -f $1)
CONFIG=$($SCRIPT_DIR/53_read_view.sh $2)
OUT=$(readlink -f $3)
shift 3
WORKDIR=`mktemp -d 2>/dev/null || mktemp ... |
06e4a3b64392906cf9016c8af8afdb1ec0c487204474456e4b4f638be49c903e | Shell | 1,038 | 21 | #
# Save TVFC estimates
#
python benchmarks/fmri/tb/rockland/train_models/save_TVFC_estimates.py all correlation SVWP_joint 645
python benchmarks/fmri/tb/rockland/train_models/save_TVFC_estimates.py all correlation sFC 645
python benchmarks/fmri/tb/rockland/train_models/save_TVFC_estimates.py LEOO covariance SVWP_joi... |
62f3470460bd2cd6acda2cb8f4c94302bd411b95f340d45a901e5cb5becf1315 | Shell | 1,040 | 28 | #!/bin/bash
#SBATCH --nodes 1
#SBATCH --time 4:00:00
#SBATCH --mem-per-cpu 50G
#SBATCH --job-name tunnel
#SBATCH --output jupyter-log-%J.txt
## This script runs a jupyter notebook over the cluster. It can also be sent as a slurm job (sbatch run_jupyter.sh)
## get tunneling info
XDG_RUNTIME_DIR=""
ipnport=$(shuf -i800... |
5c9d7aa3d036757606153863ca04783de30ef3a48a4d8c1d2eff91cb3e62a92c | Shell | 1,042 | 34 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 2
#SBATCH --output=example_8.out
source activate mlfold
folder_with_pdbs="../inputs/PDB_monomers/pdbs/"
output_dir="../outputs/example_8_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_bias=$output_dir"/b... |
d28b0cdf44ea7c448ce96065db77c6d27f256a44ee90bd60fd83a091b0d6f13c | Shell | 1,051 | 49 | #!/bin/sh
gpu=(3 3 3)
PDE='diff-react'
field_dim=2
scale_factor=8
HR_resolution=128
LR_resolution=$((HR_resolution / scale_factor))
sw=7
suffix_list=(
"${PDE}_LRinput_supervised_SRCNN_bicubic_init_s_${LR_resolution}to${HR_resolution}_sw_${sw}"
)
data_frac_list=(
"1/20"
)
for ((i=0; i<1; i++)); do
(
... |
0add0eaf11f98a80d61506fd623ccd09cf8263bd95d0d2b4cd64e329c055ac36 | Shell | 1,053 | 10 | #!/bin/bash
# In this example, we generate a D2 symmetric oligomer
# We use the symmetry config, and specify we want a D2 symmetric oligomer, with 10 designs generated
# We specify the output prefix, and also the potential we want to apply
# This external potential promotes contacts both within (with a relative weight ... |
d66950dd497f4a3717ee69944c2a2026cf7a272dc021c8615b33cb2198c72990 | Shell | 1,053 | 10 | #!/bin/bash
# In this example, we generate a C6 symmetric oligomer
# We use the symmetry config, and specify we want a C6 symmetric oligomer, with 10 designs generated
# We specify the output prefix, and also the potential we want to apply
# This external potential promotes contacts both within (with a relative weight ... |
f0479451b31962622bd4e0c7f847db3753d26fa2372cb535f818d778f8869688 | Shell | 1,057 | 29 | #!/bin/bash
# Set your paths here
HOME=/fslgroup/fslg_spec_networks/compute
code_DIR=${HOME}/code/Utah_analysis/CBIG2016_preproc_ALL
data_DIR=/fslgroup/grp_proc/compute/Utah_analysis/Utah_BIDS
# Create that special CBIG subjids text file for each subject (data must be in BIDS format)
# CBIG example format: 001 /fslho... |
25e91e996c5e4be5f3fc3a907bd5cbed1d4e31e9febbe77976baceb824f80474 | Shell | 1,058 | 62 | root_dir='/project/4180000.19/multiRat/datadir'
cd $root_dir/data
output_dir=$root_dir'/export'
mkdir -p $output_dir
dataset_name='dataset01'
ds_type=01
ds_id=001
id=0
ls . | while read line
do
cd $line
sub=$ds_type$ds_id'0'$id
ses='1'
output_sub_dir=$output_dir'/sub-'$sub'/ses-'$ses
mkdir -p $output_sub_dir... |
215e7d49b30ceecb868a416d0d606f8b8ea70d9051cbe7cf4750e58afe1437cb | Shell | 1,059 | 59 | root_dir='/project/4180000.19/multiRat/datadir'
cd $root_dir/data
output_dir=$root_dir'/export'
mkdir -p $output_dir
dataset_name='dataset01'
ds_type=01
ds_id=001
id=0
ls . | while read line
do
cd $line
sub=$ds_type$ds_id'0'$id
ses='1'
output_sub_dir=$output_dir'/sub-'$sub'/ses-'$ses
mkdir -p $output_sub_dir'/a... |
017a1b17e50845b51e225db04b4b01484121f8c1adce894295f70045558e0673 | Shell | 1,060 | 30 | #!/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... |
5bffa35e4902ce4ed5119445bf77e0861bfbe5084ea1e9ec0c671e4bbd244be7 | Shell | 1,060 | 30 | #!/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... |
a7ed580d6a69e76b9f0d3457e8220f2e4d8fb24b6be64bd2f5a8e23a778cd3f4 | Shell | 1,060 | 30 | #!/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... |
86ae43fce7d5d94ff41e8b4916b392107c875ecdbdffe129e057f778973af9a3 | Shell | 1,066 | 14 | #!/bin/bash
# Here, we're running one of the motif-scaffolding benchmark examples, in the presence of a target
# Specifically, we're scaffolding the Mdm2-interacting peptide from p53
# We specify the output path and input pdb (the p53-Mdm2 complex)
# We specify the protein we want to build, with the contig input:
# -... |
d5224fdda5ab4daad6114d385128e66cf5acc33cb1da25b8915afdaf2c275a5b | Shell | 1,072 | 31 | #!/bin/bash
#This script reads the text file listing the ICA components listed as artefacts and removes them using the fslregfilt tool
#data is in pathdir
subjList="sub-01 sub-02 sub-03 sub-04 sub-05 sub-06 sub-07"
condList="LGN-run-01 LGN-run-02 LGN-run-03 LGN-run-04 LGN-run-05 LGN-run-06 LGN-run-07 LGN... |
c221ea5c2e5edbf102a5d23a542bb2e367f1df1940e03fb21fb419500aacb830 | Shell | 1,076 | 39 | #!/bin/bash
module load java/1.8
CONDITIONS=(flu NI)
PSEUDOBULK=(pseudosums_QN)
PCS=(3 6)
TEMP_DIRS=(3expPC_Flu 6expPC_NI)
OUT_DIRS=(filtered_3expPCs_propBimodal filtered_6expPCs_propBimodal)
META=(individual_meta_data_for_GE_with_scaledCovars_with_geneProps.txt)
COUNTS=(corrected_expression.txt)
GENE_POS=(GRCh38.92_... |
675a205e196ed19077020d43cdc04e4b7b78f705bd56e40d5d3616feca6124ac | Shell | 1,077 | 40 | #!/bin/bash
#BSUB -P "perses-tyk2"
#BSUB -J "perses-benchmark-tyk2-5ns-[1-14]"
#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 5:59
#BSUB -o out_%J_%I.stdout
#BSUB -eo out_%J_%I.stderr
#... |
42649322d12b0e5eb8867b39b797ac7218febc511ab63a00e9f8ceb81d221785 | Shell | 1,078 | 40 | #!/bin/bash
#BSUB -P "perses-ripk2"
#BSUB -J "perses-benchmark-rip2-5ns-[1-14]"
#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 5:59
#BSUB -o out_%J_%I.stdout
#BSUB -eo out_%J_%I.stderr
... |
ba3c8902f94b31eee46f5499b8dde6b89b140e05afce517e464d91f483e0f1f4 | Shell | 1,080 | 39 | #!/bin/bash
module load java/1.8
CONDITIONS=(flu NI)
PSEUDOBULK=(pseudosums_QN)
PCS=(2 4)
TEMP_DIRS=(2expPC_Flu 4expPC_NI)
OUT_DIRS=(filtered_2expPCs_propBimodal filtered_4expPCs_propBimodal)
META=(individual_meta_data_for_GE_with_scaledCovars_with_geneProps.txt)
COUNTS=(corrected_expression.txt)
GENE_POS=(GRCh38.92_... |
e45509a0e313ce8c1a10b8827cfc0c96638e56a8514e89069c75c5e2a6c27fdf | Shell | 1,080 | 29 | #!/bin/bash
#This script uses a template (template_postfix_sub) to create individualised fsf files and then run them in FEAT. This will run FEAT on the data that has been cleaned via FIX
subjList="sub-01 sub-02 sub-03 sub-04 sub-05 sub-06 sub-07"
condList="LGN-run-01 LGN-run-02 LGN-run-03 LGN-run-04 LGN-ru... |
ea93086d125ddfb515927da834963f9a8ece80df0b40f962ed099b9ca6a94eda | Shell | 1,080 | 39 | #!/bin/bash
module load java/1.8
CONDITIONS=(flu NI)
PSEUDOBULK=(pseudosums_QN)
PCS=(4 6)
TEMP_DIRS=(4expPC_Flu 6expPC_NI)
OUT_DIRS=(filtered_4expPCs_propBimodal filtered_6expPCs_propBimodal)
META=(individual_meta_data_for_GE_with_scaledCovars_with_geneProps.txt)
COUNTS=(corrected_expression.txt)
GENE_POS=(GRCh38.92_... |
fa8dae3815211c129d27578eb6c705d8a6a6be5346bf0a10335fe5865cf27df4 | Shell | 1,081 | 33 | #!/bin/bash
#SBATCH --time=45:00:00 # walltime
#SBATCH --ntasks=1 # number of processor cores (i.e. tasks)
#SBATCH --nodes=1 # number of nodes
#SBATCH --mem-per-cpu=16384M # memory per CPU core
#SBATCH -J "utah_FS" # job name
# Compatibility variables for PBS. Delete if not needed.
export PBS_NODEFILE=`/fsl... |
ad03c7d46bababc34cfbc50b0b70d9cd432a6b77916ee83d4805e1921a03beaf | Shell | 1,086 | 39 | #!/bin/bash
module load java/1.8
CONDITIONS=(flu NI)
PSEUDOBULK=(pseudosums_QN)
PCS=(2 2)
TEMP_DIRS=(2expPC_Flu 2expPC_NI)
OUT_DIRS=(filtered_2expPCs_propBimodal filtered_2expPCs_propBimodal)
META=(individual_meta_data_for_GE_with_scaledCovars_with_geneProps.txt)
COUNTS=(corrected_expression.txt)
GENE_POS=(GRCh38.92_... |
0592e7e1eb67725165b24b9a8c39013b4b7bac29e7ad33c5284318a0e3ce5223 | Shell | 1,087 | 26 | #!/bin/bash
# Copyright (c) 2008-2026 the MRtrix3 contributors.
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Covered Software is provided under this License on... |
a060dff0879ffa00ae26b6a26010f8fb8a1f1b14ce5635b3a33d712b0bd80c77 | Shell | 1,087 | 29 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/P_net
cd ${root_path}/comparison_methods/P_net
python3 ${root_path}/comparison_methods/P_net/1.model.py \
--label_path ${root_path}/data_TCGA/2.sample_id/sample_cross_stage.txt ... |
3bdedc576d94fc6afb5f61c43b48f97ac7163406f38b61b4ba828331499cb92b | Shell | 1,096 | 39 | #!/bin/bash
module load java/1.8
CONDITIONS=(flu NI)
PSEUDOBULK=(pseudosums_QN)
PCS=(7 10)
TEMP_DIRS=(7expPC_Flu 10expPC_NI)
OUT_DIRS=(filtered_7expPCs_propBimodal filtered_10expPCs_propBimodal)
META=(individual_meta_data_for_GE_with_scaledCovars_with_geneProps.txt)
COUNTS=(corrected_expression.txt)
GENE_POS=(GRCh38.... |
f2705d8f93f31f6d0b92c15ff587d4c160d70da5cedcd866cef2d7ad03e1e98d | Shell | 1,101 | 66 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
SLICE=""
SLICE_POST=""
RSS_POST="_rss"
RSS=""
while getopts "hs:N" opt; do
case $opt in
s)
SLICE=-s$OPTARG
SLICE_POST="_slc$OPTA... |
1086cf1a6e93a5d0cc7d9a7411244f34d167e246f8d9ea765c88fbba1614e986 | Shell | 1,103 | 43 | #!/bin/bash
#BSUB -P "perses-tyk2"
#BSUB -J "perses-tyk2-5ns-[1-100]"
#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 5:59
#BSUB -o out_%J_%I.stdout
#BSUB -eo out_%J_%I.stderr
#BSUB -L /... |
5135525b4ce56132278f8a477971295511dfbb813f99549190831ba114b6c5d3 | Shell | 1,105 | 43 | #!/bin/bash
#BSUB -P "perses-ripk2"
#BSUB -J "perses-ripk2-1ns-[1-182]"
#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 5:59
#BSUB -o out_%J_%I.stdout
#BSUB -eo out_%J_%I.stderr
#BSUB -L... |
c663025c2c67ce04a7febb156a25e3d97142e96e40e40ac33fd7bfa94d22fe35 | Shell | 1,106 | 43 | #!/bin/bash
#
# Pathways:
# BIDSderiv = folder where the processed fieldmaps need to be sent to
#number of subjects = folder names in BIDS
subjList="sub-01 sub-02 sub-03 sub-04 sub-05 sub-06 sub-07"
#conditions = sub-folders in BIDS
timeList="Pre_stim Post_stim_5min Post_stim_2h"
targetList="ontarget off... |
10bac086430116165cf1207ef16f851554105268ab53cc10f66521cb020e8e3f | Shell | 1,108 | 27 | #!/bin/bash
# Usage: bash download_models.sh /path/to/download/directory
set -e
if [[ $# -eq 0 ]]; then
echo "Error: download directory must be provided as an input argument."
exit 1
fi
DOWNLOAD_DIR="$1"
if ! command -v wget &> /dev/null
then
echo "Error: wget could not be found. Please install wget (su... |
85d77b1b1c84a914422b2ba057bcf6338e991729280b498aa96743e3c3533cec | Shell | 1,112 | 33 | #!/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... |
d9e8830a44b62d71d894597a363e18a6a8b1ac16c5fb3b48defb9387c791124c | Shell | 1,112 | 33 | #!/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... |
4292f165dc3b5df58eb531d8d03aa7137e34bdb997f611e187f519dc031e4fc9 | Shell | 1,113 | 26 | #!/bin/bash
#This script uses a template (template_artef_clean_task_sub.fsf) to create individualised fsf files and then run them in FEAT. This will run FEAT on the data that has been cleaned for artefacts
subjList="sub-01 sub-02 sub-03 sub-04 sub-05 sub-06 sub-07"
condList="LGN-run-01 LGN-run-02 LGN-run-03 ... |
a8b2d4c4a579292c7b3c4927fee27be6bcf7b1b94da655d44e0573aba0b35b6d | Shell | 1,113 | 23 | #!/bin/bash
# This script removes the intermediate files generated by nextflow stages on the
# rnaseq and small rna datasets.
# These intermediate files are not tracked by dvc to save space, but are not removed
# at the end of the corresponding stage, in case we want to explore other nextflow
# parameters
rm -rf "da... |
5749435a75d2ae6caaf2cd156cc285eda51fa50de6daeb1d91e30f6888b7baa0 | Shell | 1,116 | 25 | #!/usr/bin/env bash
# Ever changed anything in Ray-X? maybe changed the event ID of something? or maybe the order in the CSV Writer format?
# Many changes like this will cause the __whole__ set-seeded part of the test suite to fail.
# Just because the stored "correct" solution just isn't correct anymore.
# But fear n... |
f5e816bc15421a517982ce6ead369cad44eced8bf0df2cd013b58f4458c76c23 | Shell | 1,120 | 45 | #!/bin/bash
set -x
# Activate conda environment
if [ $USER == 'uai89wz' ]
then
SCRIPT_DIR=$WORK
DIRECTORY_PROJECT=$WORK/results_DMS
module load anaconda-py3/
source activate $WORK/.conda/envs/py37
else
DIRECTORY_PROJECT=/scratch/gvignoud/results_DMS
if [ -z ${OAR_JOB_ID+x} ]
then
export PA... |
f1e76341d31ce470bfb80c871a6cb26772cf5ac32a4057fe262d3b34179be763 | Shell | 1,122 | 10 | # & means run these methods at the same time, and && means run these methods one by one
python -u test_3D.py --root_path ../data/BraTS2019 --exp BraTS2019/Fully_supervised_25 --model unet_3D &&
python -u test_3D.py --root_path ../data/BraTS2019 --exp BraTS2019/Fully_supervised_250 --model unet_3D &&
python -u test_3D.... |
35f00340c1d420145b9d884bf9f4c2bc522ecae2fa2df221b1f7fa65dc033234 | Shell | 1,129 | 29 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/liNN
cd ${root_path}/comparison_methods/liNN
python3 ${root_path}/comparison_methods/liNN/1.model.py \
--label_path ${root_path}/data_TCGA/2.sample_id/sample_cross_stage.txt \
-... |
f22802fa16b74c1925eac31d97746fb18dfcb1925bf730f1a5de12a3c02d207f | Shell | 1,129 | 44 | #!/bin/bash
set -x
# Activate conda environment
if [ $USER == 'uai89wz' ]
then
SCRIPT_DIR=$WORK
DIRECTORY_PROJECT=$WORK/pattern
module load anaconda-py3/
source activate $WORK/.conda/envs/py37
else
DIRECTORY_PROJECT=/scratch/gvignoud/pattern
if [ -z ${OAR_JOB_ID+x} ]
then
export PATH="/scr... |
69154e21682acbbd500817098595ea0885bdd01dc0cf80c432003362ea8de434 | Shell | 1,131 | 32 | #!/bin/bash
#SBATCH -J fithic_ice_bias
#SBATCH -o /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_interactions_fithic/run_fithic_ice_bias.out
#SBATCH -e /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_interacti... |
9a3a50a4abc966a66f415a1c4b7e27e72fa8024c3f249197858945aac580ebf4 | Shell | 1,134 | 41 | #!/bin/bash
set -eu
# ~~~~~~~~~~~ DATA ~~~~~~~~~~~ #
#di=/media/athena-admin/FastSSD/Athena/collabODED/data/01_Toxofilin-Cre
#samples=(4834 4836 4844 4849 4851 4858 4864 4868)
#
#di=/media/athena-admin/FastSSD/Athena/collabODED/data/02_Gra16-Cre
#samples=(4837 4840 4847 4848 4850 4871 4873)
#
#di=/media/athena-admin/... |
ec3ae387a0054bf9b16d300981bbc5b26186ea2442185e07bf41b913832db8f0 | Shell | 1,137 | 29 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/liCNN
cd ${root_path}/comparison_methods/liCNN
python3 ${root_path}/comparison_methods/liCNN/1.model.py \
--label_path ${root_path}/data_TCGA/2.sample_id/sample_cross_stage.txt ... |
5115ab226f7f302dd6526b1659893518e963597f536337c1c879ae7c6fc62b3e | Shell | 1,141 | 30 | ## --------------- Individual X-Rays Expts ---------------
# exp_set="chexpert_80_20 chexpert_80_20_shuffled mimic mimic_shuffled"
# test_datasets="chexpert_80_20 mimic nih"
## --------------- Combined X-Ray Expts ---------------
# exp_set="combined combined_nihmimic combined_shuffled combined_nihmimic_shuffled"
# tes... |
146f6d5ea783e21f539e059d81e999b57e0aebc86dda92a9807245e5b928f009 | Shell | 1,145 | 26 |
echo "unrealistic simulations for juliacon (sim 1)"
echo "case 1: mean = 0.8, pi = 0.1, 8 microbes per sample"
julia simulation/run_simulation.jl -n 1 -m 0.8 -p 0.1 -r 5 -k 8 -j -s 734
echo "case 2: mean = 0.8, pi = 0.8, 8 microbes per sample"
julia simulation/run_simulation.jl -n 1 -m 0.8 -p 0.8 -r 5 -k 8 -j -s 73... |
a7a3445bb1351105b52e72efdde3c4d88add7aa0cafd0822ac14f8950039f388 | Shell | 1,145 | 14 | #!/bin/bash
sbatch mafft_alignment.sbatch ../../../data/bernardo/processed/05.sanger_sequencing/sanger_sequencing_fasta_files/MAFFT_alignment_BambuTx1845_forward.fa \
../../../data/bernardo/processed/05.sanger_sequencing/mafft_alignment_results/MAFFT_alignment_BambuTx1845_forward_OUTPUT.txt
sbatch mafft_alignmen... |
09ec27cf620dce86e0c02af6fef6cfccb2b20ced81592e2b46b734537d705545 | Shell | 1,153 | 29 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/eiNN
cd ${root_path}/comparison_methods/eiNN
python3 ${root_path}/comparison_methods/eiNN/1.model.py \
--label_path ${root_path}/data_TCGA/2.sample_id/sample_cross_stage.txt \
-... |
8d7f3da2b72525948aac74a6f1662a8e3757650b754806485fbf59d32843a90e | Shell | 1,155 | 33 | #!/bin/bash
if [ $# -eq 0 ]
then
echo "Argument 1 should be a port number, argument 2 a string to use as password."
exit 1
fi
# parse config parameters:
source bash/parse_yaml.sh
eval $(parse_yaml config.yaml CONF_)
# ids defined in image for the rstudio user
uid=1000
gid=1000
# subid ranges on host
subuid... |
dff32525aadb99d46d50f173c32669991dbcfc6a58c25dd21c381eeb5bed2301 | Shell | 1,158 | 28 | #!/bin/bash
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to i... |
f26824f2944b1d7dff2ab9f229c5f84ae5438aa1840f891451b98a6e9d0131c8 | Shell | 1,159 | 32 | #!/bin/bash
#SBATCH -J fithic_valid_pairs
#SBATCH -o /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_interactions_fithic/run_fithic_valid_pairs.out
#SBATCH -e /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_int... |
d0bf7f7a179c80af7ec85f4701d0859693fbb8645ac7e0c64b60b4226fd11e91 | Shell | 1,161 | 29 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/eicNN
cd ${root_path}/comparison_methods/eicNN
python3 ${root_path}/comparison_methods/eicNN/1.model.py \
--label_path ${root_path}/data_TCGA/2.sample_id/sample_cross_stage.txt ... |
c0b185b3c1d86be0c24a9eb8f83a5b8fd7ae69d89d94a78bd63b4fede84eb16c | Shell | 1,164 | 15 | #!/bin/bash
module load contrib/homer/4.10
loadGenome.pl -name mmul10 -org mmul -fasta mmul10.dna.assem.fa -gtf mmul10.anno.gtf
# macaque (primary)
findMotifs.pl list-sex-biased-genes.txt mmul10 output_directory -start -1000 -end 300 -bg list-all-expressed-genes.txt -mset vertebrates -nomotif -nogo
findMotifs.pl lis... |
01a2018f6c3874c902e39e058eaed81f09c582ef0e1d0dc07de7316568cb65ac | Shell | 1,168 | 10 | #!/bin/bash
# In this example, we generate a tetrahedral symmetric oligomer
# We use the symmetry config, and specify we want a tetrahedral oligomer, with 10 designs generated
# We specify the output prefix, and also the potential we want to apply
# This external potential promotes contacts both within (with a relative... |
de4948d8a631224e79224d53572f013dd32b757e91101b2d4109d039c0f07b55 | Shell | 1,171 | 8 | CUDA_VISIBLE_DEVICES=0 python test_2D_fully.py --root_path ../data/ACDC --exp ACDC/Fully_Supervised --num_classes 4 --labeled_num 7 && \
CUDA_VISIBLE_DEVICES=0 python test_2D_fully.py --root_path ../data/ACDC --exp ACDC/Entropy_Minimization --num_classes 4 --labeled_num 7 && \
CUDA_VISIBLE_DEVICES=0 python test_2D_ful... |
475affb424b793395896bfcd34af53826c7c4a2f27e360a3f86850be4c3c0d9b | Shell | 1,172 | 11 | #!/bin/bash
# Here, we're asking diffusion to make a TIM barrel, by providing course-grained specification of the fold
# We specify the output path
# We tell RFdiffusion that we want to do scaffoldguided design, and that we are not making a binder to a target (just a monomer)
# We provide a path to a directory of TIM b... |
b3a64a71b8c801ec808e10312113d19dd5d42bd098c716816b066b895191ffa1 | Shell | 1,175 | 31 | #!/bin/bash
mkdir -p genomes
# Fetch fasta from Ensembl
wget -O genomes/Mmul_10.cdna.fa.gz \
ftp://ftp.ensembl.org/pub/release-99/fasta/macaca_mulatta/cdna/Macaca_mulatta.Mmul_10.cdna.all.fa.gz
# Unzip fasta
gunzip genomes/Mmul_10.cdna.fa.gz
# Index reference sequence
samtools faidx genomes/Mmul_10.cdna.fa
# ... |
6d2dfd0eed0f077c7c2bcbbeffede9dfec2574d015f7dcc6e24e4c2df01d601b | Shell | 1,180 | 34 | #!/bin/bash
#List of files that need flipping for the participants who had their right LGN stimulated, so that in the group analysis
filelist=`ls ./ses-offline_*target/*/*.feat/filtered_func_*clean.nii.gz`
for ID in $filelist ; do fslswapdim $ID -x y z ${ID:0:end-7}_flipx.nii.gz; done
filelist=`ls ./ses-offline_*t... |
f4f56ff565988e2514dbc35298797ff82ce97c7ec239c8873ea9bdeb16bc4e54 | Shell | 1,181 | 48 | #!/bin/bash
#$ -S /bin/bash
ROOT_DIR=/project/hippogang_3/sravikumar
ADIR_ROOT=$ROOT_DIR/atlasPHG2019
# PATH to CMREP commands
#cmrep version with meshglm with nuissance variables (fl) and missing data
# and binary mesh_merge_array
CMREP_HOME=$ROOT_DIR/packages/cmrepgccdbg_withfl/
# Cmrep build with lmshoot with PLY... |
35ef3b90d995e7528b46c2fff8b55c69b2f5ddecb35a6e0a5d01d692bfa74f59 | Shell | 1,189 | 32 | #!/bin/bash
#SBATCH -J fithic_valid_pairs
#SBATCH -o /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_interactions_fithic/run_fithic_valid_pairs_test_bias.out
#SBATCH -e /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questio... |
a13bee144a9745d385663fb700043fa7464a93f41e0106ea0015fadc29f988ed | Shell | 1,192 | 32 | #!/bin/bash
#SBATCH -J fithic_ice_bias_test
#SBATCH -o /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_questions/top_interactions_fithic/run_fithic_ice_bias_test_bias.out
#SBATCH -e /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/GhmCN/reviewer_question... |
7d76fac1be42b094e6d1ab833e7b0814dde764323405839dbb63a65fbebd0b37 | Shell | 1,193 | 41 | #!/bin/bash
set -eu
# ~~~~~~~~~~~ DATA ~~~~~~~~~~~ #
#di=/media/athena-admin/FastSSD/Athena/collabODED/data/01_Toxofilin-Cre
#samples=(4834 4836 4844 4849 4851 4858 4864 4868)
#
#di=/media/athena-admin/FastSSD/Athena/collabODED/data/02_Gra16-Cre
#samples=(4837 4840 4847 4848 4850 4871 4873)
#
#di=/media/athena-admin/... |
d147d6210525e3cccc8669fedbf95c4ba0d473b3c5909310d803b10dd557a50f | Shell | 1,195 | 12 | #!/bin/bash
# Here, we're designing binders to the glp1 helical peptide, without specifying the topology of the binder a priori, and without specifying the structure of the peptide (we know peptides can be flexible).
# We first provide the output path and input pdb of the target protein (5uul)
# We then describe the pr... |
9f01059d51076a55a328b7d9f7fd32fd247ddd65268ac494dc2a9cc16339d67f | Shell | 1,202 | 36 | #!/bin/bash
# Define dataset configurations
datasets=("BrainTumor" "Covid")
# Loop through each dataset configuration
for dataset in "${datasets[@]}"; do
# Set number of epochs based on dataset
if [ "$dataset" == "BrainTumor" ]; then
epochs=20
elif [ "$dataset" == "Covid" ]; then
epochs=40... |
1c9d0a8d2400c14df99d9cd320b008dc94df2eb5c0b774b57e7fa611e55b5af4 | Shell | 1,208 | 30 | MATLAB="/afs/ece.cmu.edu/support/matlab/2013a"
Arch=glnxa64
ENTRYPOINT=mexFunction
MAPFILE=$ENTRYPOINT'.map'
PREFDIR="/afs/ece/usr/gustavor/.matlab/R2013a"
OPTSFILE_NAME="./mexopts.sh"
. $OPTSFILE_NAME
COMPILER=$CC
. $OPTSFILE_NAME
echo "# Make settings for GPExpand" > GPExpand_mex.mki
echo "CC=$CC" >> GPExpand_mex.mki... |
b9ed94eec8a66192f0aeba12781f521011fde596c2fab9df6b5b36022c77b954 | Shell | 1,208 | 30 | MATLAB="/afs/ece.cmu.edu/support/matlab/2013a"
Arch=glnxa64
ENTRYPOINT=mexFunction
MAPFILE=$ENTRYPOINT'.map'
PREFDIR="/afs/ece/usr/gustavor/.matlab/R2013a"
OPTSFILE_NAME="./mexopts.sh"
. $OPTSFILE_NAME
COMPILER=$CC
. $OPTSFILE_NAME
echo "# Make settings for GPReduce" > GPReduce_mex.mki
echo "CC=$CC" >> GPReduce_mex.mki... |
b3ba9313a97d7814df5430fde1267afb836552d02e17a90eda68cbd465935ba0 | Shell | 1,214 | 29 | LOCALDIR=/Users/akre96/Documents/github/rrbs_bismark/Index_Genomes
cd $LOCALDIR
if [[ $# -eq 0 ]] ; then
echo 'ERROR: REQUIRED ARGUMENT MISSING'
echo 'Requires 1 argument: local or gcloud'
echo 'For example: bash Bismark_IndexGenomes_Cromwell.sh local'
echo ''
exit 0
fi
## Run on cloud
if [ $1 == '... |
c7cbb623514abaeceb3d0bf31f2a9c532911cd1a98c334e57d9fb198a2b2c02c | Shell | 1,224 | 44 | #!/bin/bash
# Load Local Variables
source ./SET_VARIABLES.sh
# Copy nii files to noisemap directory
echo "Copy nii files to noisemap directory"
cp ${NII_RAW_DIR}/*X${NOISE_SCAN}P1.nii.gz ${NOISEMAP_DIR}/noisemap.nii.gz
# Reshape image matrix to resemble MNI space
echo "Reshape image matrix to resemble MNI space"
pyt... |
ba5dfa82e03a07560df1f7cd7652d71dd0331856a57893f54f53ae1794a1d039 | Shell | 1,225 | 30 | #!/bin/bash
root_path=$"/apps/home/lulab_liuxiaofan/qhsky/project/multi_omics_paper/"
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/MOGAT
mkdir ${root_path}/comparison_methods/Result/BRCA_stage/MOGAT/merge
cd ${root_path}/comparison_methods/MOGAT
python3 ${root_path}/comparison_methods/MOGAT/main.py \
--data... |
1604e7ba408fc24f8f57b80e0ecc31847ef0fa4155755eae11542921fb745088 | Shell | 1,229 | 34 | export API_SERVER_PORT=3100
export API_SERVER_HOSTNAME=localhost
export MONGODB_CONN_STRING=mongodb://root:test@localhost:27017
export DATABASE_NAME=coinstac
export PIPELINE_SERVER_PORT=3200
export PIPELINE_SERVER_HOSTNAME=localhost
export PIPELINE_SERVER_OPERARTING_DIR=/tmp/
export MQTT_SERVER_HOSTNAME=localhost
expor... |
d739bdcd1bdc95b6a4ed3be8527c9fc9c5b49ede92bac13aaf8af31aa7500d53 | Shell | 1,230 | 38 | #!/bin/bash
#SBATCH --time=04:00:00
#SBATCH --nodes=1
#SBATCH --account=rrg-mchakrav-ab
#SBATCH --ntasks=40
# this script is to find a working seed for AROMA-based ICA in difficult datasts
# by default, it will test 100 different seeds and return in working_seed.txt a list of potential seeds to be used.
module load ... |
bf0c146fddb1049d65cd4673cd874275ae0e66d00431559afa8ffb05609c5fa9 | Shell | 1,237 | 29 | #!/bin/bash
#This script runs FIX (automated cleaning tool) on the artef_clean.feat folder. This folder (artef_clean) is the output of the following steps:
#In the task fMRI 4D data, some files had some spiking artefacts, which were identified using ICA and manual labelling. The no-artefact file is listed in the artef_... |
6d16f81413c6194e4233a9f2846fd529b75387189b54c9fd6139198499874e24 | Shell | 1,238 | 20 |
MODELPATH="./runs/classification_finetune"
TRAINED_MODELPATH='./models_MGM_training_resnet34_image10'
MODELNAME="model_gnn_85.pth"
mkdir $MODELPATH
cp src_classification/molecule_finetune_classification.py $MODELPATH
cp $0 $MODELPATH
split=scaffold
batch_size=512
CUDA_VISIBLE_DEVICES=$1 python src_classificatio... |
c3d1dce907746c8f42bae59dd92286fbd3570e8ef4ab6ec15476c2a70e8206fc | Shell | 1,241 | 53 | #!/bin/bash
#Copyright 2023. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
export BART_COMPAT_VERSION="v0.9.00"
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
NET=$(readlink -f $1)
cd $NET
source config.sh
TRNDIR=${TRNDIR:-$SCRIPT_DIR/../00_data}
WORKDI... |
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