sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
fb4431178a0930edf0cde22d60304ea8a3e2de1487af18ff323d38f3f926e874 | Shell | 21 | 1 | python ./predict.py
|
ec629df11c1bd635d2f4aa7287a548b25ff544237da63709defd0d79607f2c84 | Shell | 42 | 2 | #!/bin/bash
echo "Hello from file script"
|
a182da31cc3c50dcf128d57d5ab180d285fa92535c9f4b62ea81be9ded3da547 | Shell | 45 | 3 | #!/usr/bin/bash
sleep 10
nextflow clean -f $1 |
8b8fb13b821b77be0d5dc66d64f363917983732b30a4e22543df923d7f7c3e89 | Shell | 52 | 2 | ./run_feature_extraction.sh
./run_classification.sh
|
2c909a839eb852d0d36c2996d176c0a83beec08e6e94fa48f6a57484646aef3a | Shell | 55 | 2 | #!/bin/bash
exec /app/groupica /app/gica_bids_app.m $@
|
e7d3307f87ec132a1435f4e87764a074f96f1ca577a534821e77b1ec34b53010 | Shell | 61 | 1 | python celltype_ibl/iclr/train/acg_VAE_training_seed_sweep.py |
d582517ea7bc418769f51d18fc7854f7b665b74ee6b58370f149acc0e7f7d9ef | Shell | 63 | 4 | #!/bin/sh
make distclean PLATFORM=octave
make PLATFORM=octave
|
5e571aae6783bcd893901eace96aa45c7861e43c4c36c6613cbc8f1ddd6ba259 | Shell | 64 | 3 | #!/bin/sh
rm -rf results/*
python src/simulation_encoder/main.py |
c6ef8fe379faabaf0aa7f3381e466bd627a621fe06edecad91e8bd0ea7e75452 | Shell | 66 | 4 | #!/bin/sh
#remove multiarch
R CMD INSTALL --no-multiarch ./peer
|
37fdfb8e4c62be650293409535621460bbf172c8b1717b6ee38427a664515f65 | Shell | 67 | 1 | grep "seg id" | sed 's/<seg id="[0-9]\+">//g' | sed 's/<\/seg>//g'
|
4a74a398aa10279c0dd07e49f004270cb122de443f3217268ff00d6ec8d44268 | Shell | 67 | 1 | python celltype_ibl/iclr/eval/ibl_label_ratio_MLP.py --fine_tuning
|
85a5e49ff25a880c06bc5904979a2da874d462b0036bfd4fcc06d7fd6da98165 | Shell | 67 | 1 | signalp -fasta nextflow_results/V47/orfanage/orfanage_peptide.fasta |
268488703cc433073b093d04f714d2f5caf42edb80f569a858d12417426505f5 | Shell | 73 | 3 | #!/bin/bash
gdown --id 13onLk6fg7kjrquhh6Xs1dfbArNr-s--B
unzip aMNIST.zip |
70aa7352c5fbb07ac4c41de8582e438e5f3c9a9639256c7e242083146e7360bb | Shell | 74 | 3 | #!/bin/bash
gdown --id 1EN3Cqf_DMnnOX-H3GWrPGS-KG_Aeu44t
unzip aEMNIST.zip |
6c25b3d79442824deaf788ab8615f10eb1077d4696c41a01b1438c58cc85701d | Shell | 85 | 4 | #!/bin/bash -xve
cd /src
wasm-opt -O3 /src/jxl_decoder.wasm -o /src/jxl_decoder.wasm |
d1bcf0a6e9552e0f59317efe2da5ba4ae7f9accaf68535056c89563afabd3d0d | Shell | 90 | 3 | . setup.sh
java index.IndexCreator $MONQ/medline/2019/annotated $MONQ/medline/2019/index
|
c93ab6110004bfb51827e12bde2cdde29ec0310184b5dedabacbf8406c497020 | Shell | 97 | 5 | #!/bin/bash
set -e
psql -v ON_ERROR_STOP=1 --username username --dbname postgres <<-EOSQL
EOSQL
|
01f89b531567b3091d49c93b1b189953c3f09fa7a849c191cb09ca70157923c7 | Shell | 99 | 5 | #!/bin/bash
python submit.py 5k3f 130185
python submit.py 5k3f 260822
python submit.py 5k3f 290988 |
b87ee493e573aec644a0299497a9d23b7ac76dddf07478a252ec1f417d877d2c | Shell | 99 | 3 | . setup.sh
java index.IndexCreator $MONQ/medline/2016/baseline_annotated $MONQ/medline/2016/index
|
4cbcbcc1e087765f370ae821d01daf04454aff652f0f70d8be6a5f0717142886 | Shell | 102 | 8 | #!/bin/sh
export VARIANT=ubasan
export TOOLSET=clang
export TRAVIS=0
export BOOST_ROOT="`pwd`"
"$1"
|
66a207d761ae07cc39e7238309be2e585721d9bc099a8d459b4a1b977992b778 | Shell | 103 | 7 | #!/usr/bin/env bash
set -ex
conda install posix --yes
source scripts/build.sh
source scripts/test.sh
|
9b85c157c1ea40fc784de2f6abbec71451168054d1d8df18d9ab9ddc13eb6fac | Shell | 108 | 6 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.42 -Z -B
|
5b063d4723938a2c05691f0ab64cfe5d6c0aed6b10746c5ae4bbb7888c4ad3b7 | Shell | 111 | 3 | #!/bin/sh
curl -fsLO https://raw.githubusercontent.com/scijava/scijava-scripts/main/ci-build.sh
sh ci-build.sh
|
dffb5f1387e9bc0720c95fa901c8739d1cd6ec7c584cac0b3a02a9de0252f2d9 | Shell | 111 | 2 | python -m train --batch_size 32 --patch_size 64 --mouse 638850 \
--rna_slc 4 --data_path Data/MERFISH_50 |
e869f7e68513d6e0c1eeb2ea49f466b72e67de29bd760c5f25479767bc1da2ca | Shell | 112 | 6 | for dz in $(ls -d $HOME/Code/TWAS_data/*/*twas.txt)
do
echo $dz
Rscript $HOME/Code/twas_sig.r $dz
done
|
fecf7e79ad37a6cc864b70ca96241c865848f50a4585cda0747b2898709bfc75 | Shell | 113 | 9 | #!/usr/bin/env bash
for i in {1..3}
do
$1 "${@:2:99}" && exit 0;
export BEAST_RETRY="true"
done
exit 1
|
db58a6cfadefaad8533cad4567de06b8304a0b16b0d2d4f7f571d18f8daf3982 | Shell | 116 | 1 | java index.CitationFinderASCII | java index.MedlineTriggerAdder | DistFilter svr=sentenciser svr=doid svr=bncfilter
|
2170628016ae1e556d8e7649cc6d243c4965413b2cfb3456fe68eb10d03f41da | Shell | 121 | 7 | #$ -l mem_free=50G,h_vmem=50G
#$ -cwd
#$ -m e
#$ -M shicks19@jhu.edu
module load conda_R/devel
python3 sce_spatialDE.py
|
cf341e088c8be361c3d486ada4bb4014d8a1f4970407fa82d96a6dace974ca99 | Shell | 121 | 1 | java index.CitationFinderASCII | java index.MedlineTriggerAdder | DistFilter svr=sentenciser svr=swissprot svr=bncfilter
|
1b6ec41a98178a11e12ea1eab2a0b0a9b18e2c89961a04cc5fc78a186c7aa140 | Shell | 122 | 6 | #!/bin/bash
d=clip_data
for p in `cat data/${d}/all.list`
do
python -u tools/generate_dataset.py $p 1 5 data/$d
done
|
162dbb2528488cb504b339f38a7c2963901868b78e2736dfb2e6f3a17aa0aaee | Shell | 123 | 1 | cat $MONQ/medline/2019/baseline/example.xml | sh preprocessMEDLINE.sh | gzip > $MONQ/medline/2019/annotated/example.xml.gz
|
a3f39aa894dca7e5c94d4fd57c2734f6483c822833851ca7f9e77a9c6f7c8f86 | Shell | 123 | 6 | python celltype_ibl/src/celltype_ibl/models/bimodal_embedding_main.py \
-e 3000 \
--seed=42 \
-k 5 \
-k 1
\ |
b5be55d510d02a3f3840ac05c70abf0cad47a8c3cfea01bb3443c2a11af4b16f | Shell | 125 | 3 | pip install --no-cache-dir -r requirements.txt
pip install gradio_client==1.13.0
conda install pytorch::faiss-gpu=1.8.0 --yes |
38e5a0a08a1d696997c5811135ce64727ad1265b7340484e6c5eb5f7985dedcc | Shell | 129 | 5 | #!/bin/bash
python submit.py 5k3f-Asp134Ala 130185
python submit.py 5k3f-Asp134Ala 260822
python submit.py 5k3f-Asp134Ala 290988 |
4424b113176a8797a9c8cb8a6590ee103972de19f6482157e609300fe2d39ee5 | Shell | 129 | 3 | #!/usr/bin/env bash
previous_tag=$(git tag --sort=-creatordate | sed -n 2p)
git shortlog "${previous_tag}.." | sed 's/^./ &/'
|
4093d742f076352fb449c99a587c524908785c07ca6e557bef511b250faa4add | Shell | 134 | 1 | bash /dcl01/lieber/ajaffe/Emily/RNAseq-pipeline/sh/rnaseq-run-all.sh --experiment "He" --prefix "Layers" --reference "hg38" --cores 2
|
4bfb2c1a66a3b13e17a3a29f844610497ddc237ab2942e3213491c444bfed8e4 | Shell | 137 | 1 | bash /dcl01/lieber/ajaffe/Emily/RNAseq-pipeline/sh/rnaseq-run-all.sh --experiment "Hafner" --prefix "VGLUT" --reference "mm10" --cores 3
|
9d655aa85f56057cde40aec11233a2ad6356dbff07d0fbed0745c832b7b6cb98 | Shell | 141 | 3 | #!/bin/sh
curl -fsLO https://raw.githubusercontent.com/scijava/scijava-scripts/main/ci-setup-github-actions.sh
sh ci-setup-github-actions.sh
|
9906abadd1448c56888cc63554e79e402d3a874a50e386b8950a6ea8ba974791 | Shell | 145 | 6 | # make before running experiment
cd ../../build
make
cd ../ARGos_simulation/data_generation_scripts/
argos3 -c ../experiment/kilogrid_stub.argos |
01ed755e0701bf523d10e4cc5d2ec4d332a0dae585ec4837205e6223fca31ad0 | Shell | 148 | 5 | #!/bin/bash -e
CCFILES="components.cc max_flow.cc orderings.cc searches.cc shortest_path.cc
spanning_trees.cc statistics.cc layouts.cc planar.cc"
|
aaa88aa9ed8d3606ff0701cf500b64c2bba06d7f421dcf9eb5073a1dc29a65af | Shell | 148 | 4 | #!/bin/sh
wget --no-check-certificate https://github.com/precimed/simu/releases/download/v0.9.4/simu_linux
chmod +x simu_linux
cp simu_linux /bin/
|
f0d7fb607631e7b9d9c5c76ba96b326b2909030c80c4a91f80f9709a15acc482 | Shell | 150 | 7 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.4 -g -0.1 -B
rm ${outDir}${name}_brain_mask.nii.gz
|
b7bb9a07462c3857e47ba66d7eb3c8464b3649f609956612d12a767ace9e3df9 | Shell | 154 | 5 | #!/bin/sh
sed -i 's/^.li.*MatrixBase\<.*gt.*a.$/ /g' $1
sed -i 's/^.li.*MapBase\<.*gt.*a.$/ /g' $1
sed -i 's/^.li.*RotationBase\<.*gt.*a.$/ /g' $1
|
4565167de6fd867f29d54119311311169285ead65c5b8ddace9942854796070b | Shell | 164 | 4 | #!/bin/bash
set -e # exit on error
wget -N -c https://storage.googleapis.com/encode-pipeline-genome-data/hg38/GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz
|
5c8c369bab1853fbb93b990721947fb0c40de8c6273eed07668351c4f51a0414 | Shell | 171 | 7 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.45 -B
rm ${outDir}${name}_brain_mask.nii.gz # remove intermediate files
|
bd1b19c10a998c1628f8ba683b52a4ee0932c804039185f0f3d8885a5868ea02 | Shell | 171 | 7 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.43 -B
rm ${outDir}${name}_brain_mask.nii.gz # remove intermediate files
|
c1a454e4e150a8e09be6b0770be5136a83940d2dbd714f3fb230bb6e5e6d3938 | Shell | 171 | 7 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.55 -B
rm ${outDir}${name}_brain_mask.nii.gz # remove intermediate files
|
c274914957fdd403aa6c182e04588b1d1b53623931444899d5eb80e68c549256 | Shell | 172 | 7 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
bet ${img} ${outDir}${name}_brain.nii.gz -f 0.375 -B
rm ${outDir}${name}_brain_mask.nii.gz # remove intermediate files
|
d9bb80dee0db4245223635bcb09d999f117b49c94b18a5f57b916af1eec9a93c | Shell | 174 | 6 | #!/bin/bash -xve
cd /src
cargo build --target wasm32-unknown-unknown --release
cp /src/target/wasm32-unknown-unknown/release/jxl_wasm.wasm /src/jxl_decoder.wasm
rm -r target |
a27b653f1a630c6064486b56a6d79ab1a5f27eeded863a1de5c2f37ba24bab20 | Shell | 178 | 9 | #!/bin/bash
#SBATCH --job-name=salmon_illumina
#SBATCH --output=salmon_illumina.out
#SBATCH --time=0-5:0
#SBATCH --nodes=1
#SBATCH --ntasks=1
conda activate SQANTI3.env
salmon
|
2985e93ff6491395e1a73ad4c13c08cff8f28280c1a8d2c2dd1a54778cccb990 | Shell | 188 | 9 | #!/bin/sh
# launch MATLAB
if [ "$ARCH" == "Linux" ]; then
/mnt/MATLAB/$MATLAB_VER/bin/./matlab -nodesktop -nosplash -r "fprintf('Hello ARTENOLIS.\n'); quit();"
fi
CODE=$?
exit $CODE
|
7d85dacda5937f9d36f3b6809d438eb542ac52ecc80d5636d7f523c225453e49 | Shell | 190 | 9 | #!/usr/bin/env bash
#SBATCH --job-name=get_cds
#SBATCH --output=slurm_logs/get_cds.out
#SBATCH --time=0-12:0
#SBATCH -n 1
#SBATCH -N 1
mamba activate patch_seq_spl
python scripts/get_cds.py |
37e06918d21d9fe5576f2ba0089d14e2c26372fc8a201be3393eb248941b340f | Shell | 193 | 11 | #!/bin/bash
set -eux
eval "$(PS1="${PS1-}" conda shell.posix activate)"
bash scripts/build.sh
# shellcheck disable=SC2154
if [[ "${ARCH}" == "$(uname -m)" ]]; then
bash scripts/test.sh
fi
|
a4986ac2dcfad91b40ab4baccfcfae45dd9c8c4daa10a838d8adff92eabb5c12 | Shell | 194 | 8 | #!/bin/bash
bad_qual_f="bad_qual_070519.csv"
while read i_h2 i_p_c i_p_nc i_s2 i_repeat; do
sbatch run_optimize.e1.sh ${i_h2} ${i_p_c} ${i_p_nc} ${i_s2} ${i_repeat};
done < ${bad_qual_f}
|
b70855336e071879686f51392fd752bd95c9f9cf81d33fa05dad806e1d121279 | Shell | 199 | 2 | #!/bin/bash
python ./suppa.py generateEvents -i ./code/IsoformSwitchAnalyzeR/input/ORF_gene_id_replaced_tr_exon.gtf -o ./code/AS_APA/output/output/APA_AS_corr/ORFanage_events -e SE SS MX RI FL -f ioe |
eb1a9947b1e12aa931279060fb5347576a5bcd10c373a1bc8787d2a5765d14f9 | Shell | 205 | 5 | wget --no-check-certificate https://vu.data.surfsara.nl/index.php/s/lxDgt2dNdNr6DYt/download -O magma_v1.10_static.zip && \
unzip magma_v1.10_static.zip && \
chmod +x magma && \
cp magma /bin
|
6ef7db2bd808d1bfe218010dee650727c2c057ced50c615acdf9ac7f09c2884b | Shell | 208 | 9 | python celltype_ibl/src/celltype_ibl/models/bimodal_embedding_main.py \
-e 6000 \
-k 10 \
--log_every_n_steps 100 \
--dataset c4 \
--test_data c4_labelled \
--from_h5 \
--seed 46
|
35f2785a39cbfd50ebb303871db5e82c3679cfa33dd26de81edbd27272a310fd | Shell | 209 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../part1_pMFM_main/
rm -r output
|
2f294ea8ba6d615f6fd3c426f049710afa4ce43964bea7236a71d464f34e15e9 | Shell | 219 | 8 | #!/bin/bash
python scripts/video_feature_extractor/extract.py \
--vdir <path_to_video_folder> \
--fdir data/feat/feat_how2_s3d \
--type=s3d --num_decoding_thread=4 \
--batch_size 32 --half_precision 1
|
655d4d33cc05772200b67873d55c567f3f691c683490238a5bc61f9467df8d1c | Shell | 222 | 10 | #!/bin/bash
for f in results/*; do
if [[ ! `compgen -G "$f/pytorch_model*"` ]]; then
echo rm -rf $f
rm -rf $f
echo rm -rf "logs/$(basename $f)"
rm -rf "logs/$(basename $f)"
fi
done
|
5004441f5fe6147343e52a61d9d1d0ee087c2e449ac18e5dbbc4566f5e60b737 | Shell | 228 | 11 | python celltype_ibl/models/bimodal_embedding_main.py \
--n_runs 100 \
--log_every_n_steps 50 \
--dataset Ultra \
--test_data Ultra \
-k 5 \
-k 10 \
-e 6000 \
--adjust_to_ultra \
--seed $seed
\ |
1314fa75e2179f5d409ae13c690ea5dbdeefa5d693eb90fbb55c4c89567fe6ed | Shell | 232 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/FC_cost/
rm -r output
|
7f3441a74f3b6d379edacb83676a0f3795c3b41197eee2b3308f4008b0b17966 | Shell | 233 | 8 | #!/bin/bash
#SBATCH --job-name=submit_comet
#SBATCH --output=slurm_logs/submit_comet_2.out
#SBATCH --time=0-1:0
#SBATCH --nodes=1
#SBATCH --ntasks=1
~/tools/comet.linux.exe -Pproc/comet/comet.params.transdecoder data/tc-1154/*.mzXML |
4420db1ce70ef644f6de71a4ab8cad83f5bcec2e862fcdbfe52e602f2cbe2d48 | Shell | 235 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Constant_I/
rm -r output
|
4e358aaa1fdce5b7ac89ad919f2f3f4d3c42bc5d343af61575cd5bc330729285 | Shell | 235 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Constant_W/
rm -r output
|
03b888a57e1c0c78ae84815b3be0b2ca5c768fa8b928ea1c0e92eb928f20d078 | Shell | 237 | 8 | #!/bin/sh
#PBS -l walltime=1:00:0
#PBS -l mem=4gb
standard_space_roi ${img} ${outDir}${name}_roi.nii.gz -b
bet ${outDir}${name}_roi.nii.gz ${outDir}${name}_brain.nii.gz -f 0.3
rm ${outDir}${name}_roi.nii.gz # remove intermediate files
|
6cabea856c128e9d84b7ad4acb827032a04ba356def7fd416d52a24da2839421 | Shell | 237 | 3 | #!/bin/bash
python smd.py 2cht-rcsb-aligned 5667 2cht-rcsb-aligned --ligand chorismate-aligned --fix --minimization 10
python smd.py chorismate 1 --ligand chorismate-aligned --fix --minimization 10 |
c33df643c6bd50beebefc44fae7a7b46196e2d926f84fcf232abee18c2ca2929 | Shell | 237 | 10 | #!/bin/sh
# output directory for the index
OUTPUT_DIR=$1
QUERY_LIST=$2
while read QUERY; do
echo "building index for ${QUERY}"
python3 ./build_soma_idx.py --query-name ${QUERY} --output-dir ${OUTPUT_DIR}
done < ${QUERY_LIST}
|
050aec7c5fcdde912ed46067f7abab30a38b985e9ccaa41db45823b584dd6f76 | Shell | 238 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Gradient_only/
rm -r output
|
163de33bf7dd20c734f35ecd48d4f749c625875e60fd30b857f931464180d76a | Shell | 238 | 8 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
standard_space_roi ${img} ${outDir}${name}_roi.nii.gz -b
bet ${outDir}${name}_roi.nii.gz ${outDir}${name}_brain.nii.gz -f 0.4
rm ${outDir}${name}_roi.nii.gz # remove intermediate files
|
1a90966f86f4f3724a18f5d3de7f814e12df380da2369594c87a2f93a9fbf35a | Shell | 238 | 8 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
standard_space_roi ${img} ${outDir}${name}_roi.nii.gz -b
bet ${outDir}${name}_roi.nii.gz ${outDir}${name}_brain.nii.gz -f 0.5
rm ${outDir}${name}_roi.nii.gz # remove intermediate files
|
8ca01cc3640b466937b8f8ed009d554b607a73fefc0343e32509b4c6452c3eae | Shell | 238 | 8 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
standard_space_roi ${img} ${outDir}${name}_roi.nii.gz -b
bet ${outDir}${name}_roi.nii.gz ${outDir}${name}_brain.nii.gz -f 0.3
rm ${outDir}${name}_roi.nii.gz # remove intermediate files
|
394d880f37234f87f693a2273b249dd7e27f187aebe027dd0a8554f7f37f1a5e | Shell | 239 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Non_parametric/
rm -r output
|
7e39805bb444f0887af28bd68157abcb9e3a3c887c0ff5f86a47c37d66cdf4db | Shell | 239 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Constant_sigma/
rm -r output
|
9b043f7251dc6ba74bc0fca30665dea58a270f1285ee6bd5ce228c180cbc9495 | Shell | 239 | 8 | #!/bin/sh
#PBS -l walltime=01:00:0
#PBS -l mem=4gb
standard_space_roi ${img} ${outDir}${name}_roi.nii.gz -b
bet ${outDir}${name}_roi.nii.gz ${outDir}${name}_brain.nii.gz -f 0.32
rm ${outDir}${name}_roi.nii.gz # remove intermediate files
|
b098231efe91a13ff7ecc4870e0e9b15a4cc79ce2e4ec3fe067c2b285a698ad0 | Shell | 239 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/SOMA_algorithm/
rm -r output
|
d137410442633a43c0c4996b759756d791086be9ce322d5dc4a56c1a44342f9f | Shell | 239 | 7 | python3 -m venv software/venv
source software/venv/bin/activate
pip install --upgrade pip
pip install pandas psutil tqdm duckdb matplotlib
pip install snakemake snakemake-executor-plugin-cluster-generic
pip install --no-cache-dir pyspark |
697eff9618effb846ff05e97b47fc48c36a9df74da43e67c485819d2fd8a0f41 | Shell | 240 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/High_resolution/
rm -r output
|
7f63c169387cdcb5beaa0e2c019bea1c899b0ffc1acf36edb199224d37bd102c | Shell | 243 | 14 | #! /bin/sh
# input should be a directory
path=$1
# for loop all the files and check the license
for file in $path/*
do
echo $file
sh $CBIG_CODE_DIR/setup/check_license/CBIG_check_license_matlab_file.sh $file
clear
done
exit 0;
|
9a5f636a592849a48fdd315b01489211b7e973c06008a9b44e9df5f3e44d4601 | Shell | 243 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Constant_parameter/
rm -r output
|
5aa7040578a0999ac5b8bd7c8079ffda4a6d59abc85e11c8ba643e33a50f8f16 | Shell | 247 | 11 | #!/bin/bash
# Written by Nanbo Sun and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
inList=${1}
suffix=${2}
outList=${3}
# append suffix to each line of a list
sed "s/$/${suffix}/" ${inList} > ${outList}
|
601e432916d92ff8de2d67d6d6dd379d67dab9255bc3a9cda411f40b2495bd70 | Shell | 248 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/Different_window_length/
rm -r output
|
a2526289db63295d8b74779a650633865ac3070e62fe8a309e74d587d90b5627 | Shell | 249 | 4 | python -m test_attn --batch_size 1 --patch_size 64 \
--data_path Data/MERFISH_50 --mouse 638850 --port 18850 \
--ckpt_pth checkpoints/638850_64_229_all_4_ours/last.ckpt \
--out_dir MBA/0_vis/timestep --region -1 --path GLUT --calc_attn
|
c8607d1d0ef75c9f85f1739b8207a11d42f947e60988bd2da47b59511fce9991 | Shell | 249 | 4 | python -m test_attn --batch_size 1 --patch_size 64 \
--data_path Data/MERFISH_50 --mouse 638850 --port 18850 \
--ckpt_pth checkpoints/638850_64_229_all_4_ours/last.ckpt \
--out_dir MBA/0_vis/timestep --region -1 --path DOPA --calc_attn
|
b4c2f5667078d4b2b1b088e51eed9a38646b56374da8c23995c76d65cc017874 | Shell | 251 | 6 | #!/bin/bash
# this file is used to clean up the repo
# Written by Kong Xiaolu and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
cd ../../../../part2_pMFM_control_analysis/STDFCD_permutation_Desikan/
rm -r output
|
8afe84539e0bdcfae92e8c03aab40daa40e6053d61f7c8652df0853cbe14339e | Shell | 252 | 9 | #!/bin/bash
#SBATCH --job-name=salmon_index
#SBATCH --output=slurm_logs/salmon_index.out
#SBATCH --time=0-1:0
#SBATCH --nodes=1
#SBATCH --ntasks=1
mamba activate patch_seq_spl
salmon index -p 30 -t proc/merged_collapsed.fasta -i proc/salmon_index_full |
e657b908c0be0e0ea253d9bacae90736c901138c488aad2590e18aa33c4e1178 | Shell | 255 | 4 | python -m test_brn --port 38850 --batch_size 1 --patch_size 64 \
--data_path Data/MERFISH_50/ --mouse 638850 \
--ckpt_pth checkpoints/638850_64_229_all_4_ours/last.ckpt \
--out_dir MBA/0_final/timestep --hst 256 --wst 256 --hnm 286 --wnm 414 |
825d46e5222dcbd5c94636e506f021d87a5e7a3158a68e8590d57ca9bd57ff6a | Shell | 257 | 11 | #!/usr/bin/env bash
bash build_minimal_data_requirements.sh
if [[ ! -f data/GWAS.tar.gz ]]; then
wget https://s3.amazonaws.com/imlab-open/Data/MetaXcan/1000G-WB/data/GWAS.tar.gz -O data/GWAS.tar.gz
cd data
tar -xzvpf GWAS.tar.gz
cd ..
fi
|
246ba8e0bbce917d848c0fbbdb7ec97100a5641bb089ed5443185056fcc7cb84 | Shell | 260 | 13 | #!/bin/bash -xve
# This script builds `libpng.wasm` using emsdk in a docker container.
cd "$(dirname "$0")"
docker build .
docker run \
--rm \
-v ${PWD}:/src \
-u $(id -u):$(id -g) \
$(docker build -q .) \
./build_wasm.sh
|
b1cef916c1d9ef05d1724b86a91c4b8798f47dfa40a5c131b68e3db8c7dc2f59 | Shell | 261 | 8 | #!/bin/bash
#SBATCH --job-name=submit_comet_PacBio_search_db
#SBATCH --output=slurm_logs/submit_comet_PacBio_search_db.out
#SBATCH --time=0-1:0
#SBATCH --nodes=1
#SBATCH --ntasks=1
~/tools/comet.linux.exe -Pproc/comet/comet.params.high-low data/tc-1154/*.mzXML |
114049e9ce3208b733e92f121fcb1f9fe9866b1ca43bbdcf1346407138690a60 | Shell | 263 | 13 | #!/bin/bash -xve
# This script builds `libcrackle.wasm` using emsdk in a docker container.
cd "$(dirname "$0")"
docker build .
docker run \
--rm \
-v ${PWD}:/src \
-u $(id -u):$(id -g) \
$(docker build -q .) \
./build_wasm.sh |
cf024006a5d4c533d102a6b75260ac67296045e53caf2320474088b5d112adf8 | Shell | 263 | 13 | #!/bin/bash -xve
# This script builds `compresso.wasm` using emsdk in a docker container.
cd "$(dirname "$0")"
docker build .
docker run \
--rm \
-v ${PWD}:/src \
-u $(id -u):$(id -g) \
$(docker build -q .) \
./build_wasm.sh
|
ab37a0a4ec515136e97151de484002f3ea781b40aec8ca326d2ba4d6ceb2e487 | Shell | 264 | 9 | #!/bin/sh
set -euo pipefail
# plink
version=20250819
wget --no-check-certificate https://s3.amazonaws.com/plink1-assets/plink_linux_x86_64_$version.zip && \
unzip -j plink_linux_x86_64_$version.zip && \
rm -rf plink_linux_x86_64_$version.zip
cp plink /bin |
f8cdbd0e00a88a9fcbaf084b90a685d645351a6dec4364fa883f0ccad7ab313f | Shell | 269 | 6 | python -m infer_brn --gdir MBA/0_final/timestep_15 --odir MBA/gen_0 \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_col --is_gen
python -m infer_brn --gdir MBA/0_final/timestep_15 --odir MBA/gen_0 \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_mba --page 5 |
7ad7dfd39e2f89214f71466d8dfcb38c601b79ae905da6c17cd06cfa0c128cb3 | Shell | 272 | 5 | python -m infer_attn --gdir MBA/0_vis/timestep_GLUT --odir MBA/0_vis/attn_GLUT \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_col
python -m infer_attn --gdir MBA/0_vis/timestep_GLUT --odir MBA/0_vis/attn_GLUT \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_mba |
7be71c0e0b45c16c1fa9ec8de6c2cbdc40e4140c9a4578009efd7251766d9520 | Shell | 272 | 13 | #!/bin/bash -xve
# This script builds `neuroglancer_draco.wasm` using emsdk in a docker container.
cd "$(dirname "$0")"
docker build .
docker run \
--rm \
-v ${PWD}:/src \
-u $(id -u):$(id -g) \
$(docker build -q .) \
./build_wasm.py
|
ba79cb689e8f73bfb3d91fc49dc0d1aa1e28e3b230079bbfebb43007713c984d | Shell | 272 | 5 | python -m infer_attn --gdir MBA/0_vis/timestep_DOPA --odir MBA/0_vis/attn_DOPA \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_col
python -m infer_attn --gdir MBA/0_vis/timestep_DOPA --odir MBA/0_vis/attn_DOPA \
--hst 256 --wst 256 --hnm 286 --wnm 414 --gen_mba |
2dd450e10c19cfcd1a7fef3dc9d9e358f6d7036c49480c6cf39333dd8710ca49 | Shell | 276 | 10 | #!/bin/bash
CONDA_ENV_PY3=encode-atac-seq-pipeline
CONDA_ENV_PY2=encode-atac-seq-pipeline-python2
CONDA_ENV_OLD_PY3=encode-atac-seq-pipeline-python3
conda env remove -n ${CONDA_ENV_PY3} -y
conda env remove -n ${CONDA_ENV_PY2} -y
conda env remove -n ${CONDA_ENV_OLD_PY3} -y
|
ce7c480170bc9e47c06aa00714aadeebac12b330616115028a979bf7702112ac | Shell | 277 | 8 | SCRIPT=$(dirname $(readlink -f "$0"))
if [[ "$@" == *"-train"* ]]; then
# 调用训练脚本，并传递所有参数
sh ${SCRIPT}/script/train/run_train.sh "$@"
else
# 调用预测脚本，并传递所有参数
sh ${SCRIPT}/script/predict/run_predict.sh "$@"
fi |
057d7146ac3b5557feeffb8544472cd22ab44c6e91aa2d44b714c80ac45adcc5 | Shell | 281 | 11 | #!/bin/bash
set -e
for wdl in test_*.wdl
do
json=${wdl%.*}.json
result=${wdl%.*}.result.json
./test.sh ${wdl} ${json} ${1}
python -c "import sys; import json; data=json.loads(sys.stdin.read()); sys.exit(int(not data[u'match_overall']))" < ${result}
rm -f ${result}
done
|
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