sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4e0d8656cca61943091d1baf0611875205908b73fee0d3210e781e6fabecb52a | Shell | 217 | 1 | python test_subg.py --data_path data/inat2018_test.pkl --model_filename checkpoint/inat.ckpt --knn_k 10 --tau 0.1 --level 10 --threshold prob --faiss_gpu --hidden 512 --num_conv 1 --gat --batch_size 4096 --early_stop
|
c107d63d5c6cd2537416b92fa7f8c3e5dc07bddf8751577d207a62fee49f123e | Shell | 220 | 7 | #!/usr/bin/env bash
set -euo pipefail
: "${JITCONFIG:?JITCONFIG not set - this image must be started by the host launcher}"
cd /home/docker/actions-runner
jit="$JITCONFIG"
unset JITCONFIG
exec ./run.sh --jitconfig "$jit" |
e75e644b0c131a59ad12da46886b4302f14c68ad7bdc93b98007034f2a4de30c | Shell | 222 | 3 | # install libraries for python package on ubuntu
#pip2 install nose numpy cython scipy networkx matplotlib nltk requests[security] tqdm
pip3 install nose numpy cython scipy networkx matplotlib nltk requests[security] tqdm
|
0107108a448557852da266e8befbec2bafcb012300ca2fd0b7ccc178a7cc0202 | Shell | 224 | 10 | #!/usr/bin/env bash
#SBATCH --output=logs/%j-glm_contrasts.out
#SBATCH -p psych_day
#SBATCH -t 5:00:00
#SBATCH --mem 50GB
#SBATCH -n 1
module load miniconda
conda activate "./myenv"
python "./GLM-condition/glm_contrasts.py" |
5076aeb97440064c7eed29397e8ed4b7d65910020b133a62e325edc47bfd1e34 | Shell | 234 | 10 | #!/usr/bin/env bash
#SBATCH --output=logs/%j-glm_beta_analysis.out
#SBATCH -p psych_day
#SBATCH -t 5:00:00
#SBATCH --mem 100GB
#SBATCH -n 1
module load miniconda
conda activate ""./myenv"
python "./GLM-condition/glm_beta_analysis.py" |
7e57b1f73f79fcb0552938de362f06cd5079509a47c8371c0445e0587319d45f | Shell | 237 | 10 | #!/bin/bash
mapfile -t ENTRIES < cy-calls.$1.bed
#
for line in "${ENTRIES[@]}" #
do
#
POSITIONS=`echo $line | awk '{ print $3 }'`;
# echo "POS:$POSITIONS";
cat ../system_files/cy_halotype_data.csv | grep "$POSITIONS";
done
|
123d8f91a795de2c3b086b5e548e0a47aa2420011240a0ccdf808a89d68c4acf | Shell | 239 | 1 | python train_subg.py --data_path data/inat2018_train_dedup_inter_intra.pkl --model_filename checkpoint/inat.ckpt --knn_k 10,5,3 --levels 2,3,4 --faiss_gpu --hidden 512 --epochs 250 --lr 0.01 --batch_size 4096 --num_conv 1 --gat --balance
|
5829007f4307f347f7bdf1eb6421992aacb5cffc0949637817c48d11b9da8cad | Shell | 239 | 8 | git submodule init
git submodule update --recursive
mkdir build
cd build
cmake -DUSE_CUDA=$USE_CUDA -DUSE_OPENMP=ON -DCUDA_ARCH_NAME=All ..
make
cd ../python
$PYTHON setup.py install --single-version-externally-managed --record=record.txt
|
e02f1af505fed8159b738e23b55abe2dd718bac731bb1c79a6a7d76279291740 | Shell | 239 | 8 | #!/bin/bash
set -o errexit -o nounset
set -o pipefail
apt-get update && apt-get install -y openjdk-8-jdk maven
test -d "/usr/lib/jvm/java-8-openjdk-amd64/jre"
echo "export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre" >> /etc/profile
|
76c985749a7100285e7da6e91f4c3696a4c107bc2525e2d37e0b8fc4a81cb90e | Shell | 244 | 1 | python test_subg.py --data_path data/inat2018_test.pkl --model_filename checkpoint/inat_resampled_1_in_6_per_class.ckpt --knn_k 10 --tau 0.1 --level 10 --threshold prob --faiss_gpu --hidden 512 --num_conv 1 --gat --batch_size 4096 --early_stop
|
aabba98724f0c6dc3e147ffa8e384a60753ad3bfaf915fb418f55280ffe467b3 | Shell | 247 | 8 | #!/bin/bash
source activate quagmir
#pip install --upgrade git+https://github.com/infoscout/weighted-levenshtein.git
snakemake -j
source deactivate
find ./results/ -size 0 -print0 |xargs -0 rm
find ./group_results/ -size 0 -print0 |xargs -0 rm
|
13ecd80d7fffc24d27a5828d4c35d905a8835b446931a30dc0645958c7ba4b95 | Shell | 248 | 5 | layer=$1
kernel=$2
chen2meme layer$layer/kernel-$kernel-redict.chen > layer$layer/kernel-$kernel-redict.meme
tomtom --norc layer$layer/kernel-$kernel-redict.meme layer$layer/kernel-$kernel-redict.meme -oc layer$layer/kernel-$kernel-redict-redict
|
e31c76bdd822aa21a00c49f1c1972ad7869be709634300297c3ebfa8ad14b178 | Shell | 263 | 9 | #!/bin/bash
#
echo -e "\e[34m[TRACESPipe]\e[32m Downloading Reference Human mithocondrial genome (mtDNA.fa) from NCBI ...\e[0m";
#
rm -f mtDNA.fa;
efetch -db nucleotide -format fasta -id "NC_012920.1" > mtDNA.fa
#
echo -e "\e[34m[TRACESPipe]\e[32m Done!\e[0m";
#
|
d7495cf5dacef42d67ed64f1af3373e9a5abb1726edd9c62d56d30be8cd3e673 | Shell | 268 | 17 | #!/usr/bin/bash
echo "Installing things"
sudo pacman -S --needed git base-devel
cd
echo "Installing Yay"
cd
sudo pacman -S --needed git base-devel
git clone https://aur.archlinux.org/yay.git
cd yay
makepkg -si
cd
sudo rm -r yay
echo "Installing Kafka"
yay -S kafka
|
5d575cb67d8688c14bf4115af0250496c4e574171517ad2bce6c9cc14945a915 | Shell | 270 | 4 | python tf_simulation.py FS-cell CONFIG1 -s --SEED 4 --tstop 10
python theoretical_tools.py -f data/FS-cell_CONFIG1.npy --With_Square
python tf_simulation.py RS-cell CONFIG1 -s --SEED 4 --tstop 10
python theoretical_tools.py -f data/RS-cell_CONFIG1.npy --With_Square
|
618e6642e37d08613f0f99ba883ae8a822bfce9b37f5d45c7410803321831e5c | Shell | 270 | 1 | python test_subg.py --data_path data/subcenter_arcface_deepglint_imdb_features.pkl --model_filename checkpoint/deepglint_sampler.pth --knn_k 10 --tau 0.8 --level 10 --threshold prob --faiss_gpu --hidden 512 --num_conv 1 --batch_size 4096 --early_stop --use_cluster_feat
|
b3186ceb9b526d70f220d855548c4b5f0fdf58943dcbe34e362f50c5a9829f08 | Shell | 272 | 1 | python test_subg.py --data_path data/subcenter_arcface_deepglint_hannah_features.pkl --model_filename checkpoint/deepglint_sampler.pth --knn_k 10 --tau 0.8 --level 10 --threshold prob --faiss_gpu --hidden 512 --num_conv 1 --batch_size 4096 --early_stop --use_cluster_feat
|
563a3c92101415dab6141cb952e7972ae8f5db9be54be64f5865b197e89b4a14 | Shell | 280 | 6 | rm requirements.txt
pipreqs --savepath requirements.txt --force openbci_stream
sed -i '/kafka==/d' requirements.txt
sed -i '/pyEDFlib==/d' requirements.txt
sed -i 's/==.*//' requirements.txt
python -c "[print(f'\'{line[:-1]}\',') for line in open('requirements.txt').readlines()]" |
af8b1a0f231c4db052f72902ae2fc6ee03c8f3881f50cd17feea6bec9ae764cc | Shell | 282 | 1 | python train_subg.py --data_path data/subcenter_arcface_deepglint_train_1_in_10_recreated.pkl --model_filename checkpoint/deepglint_sampler.pth --knn_k 10,5,3 --levels 2,3,4 --faiss_gpu --hidden 512 --epochs 250 --lr 0.01 --batch_size 4096 --num_conv 1 --balance --use_cluster_feat
|
72c1418d59b60ad911051f14cfcad436e716d537218e76dbe98806e8a789e18f | Shell | 283 | 1 | python train_subg.py --data_path data/inat2018_train_dedup_inter_intra_1_in_6_per_class.pkl --model_filename checkpoint/inat_resampled_1_in_6_per_class.ckpt --knn_k 10,5,3 --levels 2,3,4 --faiss_gpu --hidden 512 --epochs 250 --lr 0.01 --batch_size 4096 --num_conv 1 --gat --balance
|
096bcabc319b2eb778260a7d4c19ca7148e5be670cfa948706e41f8e51db0fd5 | Shell | 287 | 20 | #!/bin/bash
info_loc=$(which 3dinfo)
target=$1
# Pass in the desired dataset to get basic info for
if [[ $info_loc =~ "not found" ]]
then
echo "Cannot find 3dinfo; is AFNI installed?"
exit 1
fi
3dinfo \
-n4 \
-d3 \
-tr \
-space \
-obliquity \
$target
|
35160f2f63d21cfbca428321a8f9e13970c27ba155d1d8e70e98f69cb289987a | Shell | 288 | 10 | #!/usr/bin/env bash
set -euo pipefail
ARTIFACT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
for pid_file in "$ARTIFACT_DIR/payload_store.pid" "$ARTIFACT_DIR/bb.pid"; do
if [[ -f "$pid_file" ]]; then
pid="$(cat "$pid_file")"
kill "$pid" >/dev/null 2>&1 || true
fi
done
|
e9cb6195c07bf32e19903b11fbbd52a3cc717cb477b477d4d4ce334fbc5b2788 | Shell | 294 | 9 | python Smooth_AP/src/evaluate_model.py \
--dataset Inaturalist \
--bs 384 \
--source_path ~/code/Smooth_AP/data/ --embed_dim 128 \
--resume $CHECKPOINT_PATH \
--class_num 948 --loss smoothap \
--trainset lin_train_set1.txt \
--testset Inaturalist_test_set1.txt \
--linsize 29011 --uinsize 18403 |
7419805ddf69f30369abf71888fea2b606b453695cc414bf8bda913c8ff268ca | Shell | 299 | 1 | python test_subg.py --data_path data/subcenter_arcface_deepglint_imdb_features_sampled_as_deepglint_1_in_10.pkl --model_filename checkpoint/deepglint_sampler.pth --knn_k 10 --tau 0.8 --level 10 --threshold prob --faiss_gpu --hidden 512 --num_conv 1 --batch_size 4096 --early_stop --use_cluster_feat
|
f06a323c0bdb7dfb89d57f11d2d04d9bd484a8b0c702791c67b26ce6f39ca714 | Shell | 301 | 2 | MXNET_CUDNN_AUTOTUNE_DEFAULT=0 CUDNN_AUTOTUNE_DEFAULT=0 MXNET_GPU_MEM_POOL_TYPE=Round MXNET_GPU_MEM_POOL_ROUND_LINEAR_CUTOFF=28 python train_faster_rcnn.py \
--gpus 0,1,2,3,4,5,6,7 --dataset visualgenome -j 60 --batch-size 8 --val-interval 20 --save-prefix faster_rcnn_resnet101_v1d_visualgenome/
|
cfe4ffce0d36b2dae34b2f41aef7f623527068103fa66c3d35af69768278ae29 | Shell | 310 | 8 | #!/bin/bash
#
# $1 -> NUMBER OF THREADS
#
rm -f o_fw_pr.fq.gz o_fw_unpr.fq.gz o_rv_pr.fq.gz o_rv_unpr.fq.gz;
#
trimmomatic PE -threads $1 -phred33 FW_READS.fq.gz RV_READS.fq.gz o_fw_pr.fq o_fw_unpr.fq o_rv_pr.fq o_rv_unpr.fq ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:25
#
|
ccfc2ceaa61058f444299cad3a6ebd28b11f79b2c3cf29ccd2308eb5b860fe31 | Shell | 311 | 11 | #!/bin/bash
#
# ==============================================================================
# GET HUMAN HOST INDEXES
#
rm -f hg19.zip
wget ftp://ftp.ccb.jhu.edu/pub/data/bowtie2_indexes/hg19.zip
unzip hg19.zip
./make_hg19.sh
#
# ==============================================================================
|
974da31c01f4965bb30f03358ad734ffe3b4ee578a107a37e99fabd709363f35 | Shell | 312 | 10 | genome_fasta=$1
reps_to_mask_bed=$2
rep_consensus_fa=$3
genes_gtf=$4
output_name=$5
bedtools maskfasta -fi $genome_fasta -fo temp.fa -bed $reps_to_mask_bed
cat temp.fa $rep_consensus_fa > $output_name.fa
cellranger mkref --genome=$output_name --fasta=$output_name.fa --genes=$genes_gtf --nthreads=16
rm temp.fa
|
3cba71d2f4f8586bb622a99cf262c055e20a8e263e1f219ff7578f1faafcafeb | Shell | 313 | 9 | #!/bin/bash
#
echo -e "\e[34m[TRACESPipe]\e[32m Downloading Phix reference genomes (F_PHIX.fa) from NCBI ...\e[0m";
#
#gto_fasta_extract_read_by_pattern -p "phiX174" < VDB.fa > F_PHIX.fa
efetch -db nucleotide -format fasta -id "J02482.1,NC_001422.1" > F_PHIX.fa
#
echo -e "\e[34m[TRACESPipe]\e[32m Done!\e[0m";
#
|
6226745f59d41fad5de8b60e46440bd22f9cf96c1a4b2faa798b8703d32e2168 | Shell | 313 | 12 | #!/bin/bash -xve
# cibuildwheel runs docker containers as root, and when running as uid 0, pip refuses to use a cache
# directory that is not owned by uid 0.
PIP_CACHE_DIR="$1"
if [ ! -z "${PIP_CACHE_DIR}" ]; then
mkdir -p "${PIP_CACHE_DIR}"
chown $UID "${PIP_CACHE_DIR}"
chmod 777 "${PIP_CACHE_DIR}"
fi
|
8756093240a54eee146fbef39d895a8dd02b258dcd84140a40215d83759fa752 | Shell | 317 | 16 | #!/bin/bash
CONFIGFILE=$1
if [ $# -eq 0 ] ; then
echo "Configfile path not supplied."
else
sh run_processing.sh $CONFIGFILE &&
sh run_training.sh $CONFIGFILE &&
sh run_beam_generation.sh $CONFIGFILE &&
sh run_final_ranking.sh $CONFIGFILE &&
sh run_boxplot.sh $CONFIGFILE &&
sh run_tsne_plot.sh $CONFIGFILE
fi
|
fcebad616a87bd68dd467c7bbaa9dbbf96f17cfec0730fc64b76dd4eaacd1d69 | Shell | 320 | 9 | #!/bin/bash
# generate benchmark data and decompose them into mosaic tandem repeats
bash test_gendata_decompose.sh
# Compute the accuracy of predicting mosaic tandem repeats, say U_i V_j W_k with allowing the values of i, j, and k can differ from the true values at most 1%, 2%, and 3%.
bash test_allowance.sh
exit 0
|
beaad5f936ddad8fb6abfaef4efe37393e99cd6e613705ba0ae0f5f84e944a3d | Shell | 323 | 14 | # install python and pip, don't modify this, modify install_python_package.sh
apt-get update
apt-get install -y python-dev python3-dev
# install pip
cd /tmp && wget https://bootstrap.pypa.io/get-pip.py
python2 get-pip.py
python3 get-pip.py
# santiy check
python2 --version
python3 --version
pip2 --version
pip3 --versi... |
dfde1f1bca646ace008f14f20a70764ec4910946f17b433253849c8ec1a1479e | Shell | 324 | 13 | #!/bin/bash
#
declare -a INDIVIDUALS=('1' '3' '4' '6' '7' '8' '12' '14' '15' '16' '18' '19' '29' '30');
#
for x in "${INDIVIDUALS[@]}"
do
echo "Running I$x ...";
cd novaseq_1/I$x/tracespipe_template/src/
./TRACESPipe.sh --run-meta --run-mito --run-all-v-alig --run-hybrid
cd ../../../../
echo "Done!";
don... |
68feb55d483236388075aca2dafdb2703c7a6634279ea81e2fd5d9f8b11a1ffd | Shell | 325 | 10 | #!/bin/bash
#
echo "Downloading Reference Human Y chromosome (cy.fa) from NCBI ..."
#
rm -f hs_ref_GRCh38.p12_chrY.fa.gz
wget ftp://ftp.ncbi.nlm.nih.gov/refseq/H_sapiens/H_sapiens/Assembled_chromosomes/seq/hs_ref_GRCh38.p12_chrY.fa.gz
gunzip -f hs_ref_GRCh38.p12_chrY.fa.gz
mv hs_ref_GRCh38.p12_chrY.fa cy.fa
#
echo "Don... |
03f19098d5a4c076885853624904531af13fcbaa13aff28708841bdba64aa0cc | Shell | 327 | 4 | MXNET_CUDNN_AUTOTUNE_DEFAULT=0 python validate_reldn.py \
--pretrained-faster-rcnn-params faster_rcnn_resnet101_v1d_visualgenome/faster_rcnn_resnet101_v1d_custom_best.params \
--reldn-params params_resnet101_v1d_reldn/model-8.params \
--faster-rcnn-params params_resnet101_v1d_reldn/detector_feat.features-8.... |
447e1ec5758c0626c921209000150ba0ad5212eae11c6985d2a629d953d3352b | Shell | 329 | 13 | #!/bin/bash
#
declare -a INDIVIDUALS=('1' '3' '4' '6' '7' '8' '12' '14' '15' '16' '18' '19' '29' '30');
#
for x in "${INDIVIDUALS[@]}"
do
echo "Running I$x ...";
cd novaseq_1_no_duplications/I$x/tracespipe_template/src/
./TRACESPipe.sh --run-meta --run-all-v-alig --remove-dup
cd ../../../../
echo "Done!";
... |
a483173da8e9e825e2458a25530a9465bfac627d6eb28791174dfabef5a2ac30 | Shell | 329 | 17 | #!/bin/bash
#
# check if $2
FIRST_SYMBOL=`head -c 1 $2`;
#echo "First symbol: $FIRST_SYMBOL";
#
if [ "$FIRST_SYMBOL" = ">" ]
then
echo "Adding the FASTA file to the $1 database";
cat $1 $2 > tmp-add-fasta-$1
mv tmp-add-fasta-$1 $1
echo "Done!"
else
echo "ERROR: the file $2 is not a FASTA file!";
exit 1... |
ecbd07763b89b20bfef0cb1da10394995b468e623c651a00e3b68e88b8c12603 | Shell | 333 | 10 | #!/bin/bash
# Iterate over each file in the current directory
for file in examples/modular-transformers/modular_*; do
# Check if it's a regular file
if [ -f "$file" ]; then
# Call the Python script with the file name as an argument
python utils/modular_model_converter.py --files_to_parse "$file... |
cabd45f69c8b4625b3185579551ff7cfd6034722bd3702bb7827cc3a67644dad | Shell | 336 | 11 | #!/bin/bash
/usr/bin/zookeeper-server-start.sh /etc/kafka/zookeeper.properties &
while ss -ltn | awk '$4 ~ /:2181$/ {exit 1}'; do sleep 10; done
/usr/bin/kafka-server-start.sh /etc/kafka/server.properties &
while ss -ltn | awk '$4 ~ /:9092$/ {exit 1}'; do sleep 10; done
sudo pip install -U bci-framework
sudo -u use... |
ce19264d10ee90d9a3c479c9c6b20b169091789b3b49f37116707d6885b7ac25 | Shell | 336 | 17 | #!/bin/bash
# Script to download all the benchmarking Nanopore data
# usage:
# bash download_all.sh OUTPUT_DIR
# make the output dir if does not exists
if [ ! -d $1 ]
then
mkdir $1
else
echo "Download directory exists"
fi
source download_jain.sh "$1/jain"
source download_verm.sh "$1/verm"
source download_w... |
dc97483df0976b9c757607ec8fec9fadb5a6cc4b37ae194f25f459a24f7eb118 | Shell | 341 | 12 |
# bash run.layer.sh <layer> <the number of kernels> <threads> <optional: the number of flexible motifs> &> .layer<layer>.log
bash run.layer.sh 1 5 28 &> .layer1.log
bash run.layer.sh 2 5 28 &> .layer2.log
bash run.layer.sh 3 6 28 &> .layer3.log
bash run.layer.sh 4 6 28 &> .layer4.log
bash run.layer.sh 5 1 ... |
e906a05741194117e3e90bf5582fe9d3b2ee69e252ebc72fdca0923f1e3d7501 | Shell | 343 | 11 | # Install cmake with minimum required version.
version=3.18
build=0
mkdir ~/temp
cd ~/temp
wget https://cmake.org/files/v$version/cmake-$version.$build-Linux-x86_64.sh
sudo mkdir /opt/cmake
sudo sh cmake-$version.$build-Linux-x86_64.sh --prefix=/opt/cmake --skip-license
sudo ln -s /opt/cmake/bin/cmake /usr/local/bin/c... |
2898356eccfc8805441061fbe8843e15856ec8ae249b487ebc3eedbd890835a8 | Shell | 346 | 8 | #!/bin/bash
subjDir=/fslhome/mpeter55/fsl_groups/fslg_csf_autism/compute/HBN_Project/output/release1-7
for i in `cat /fslhome/mpeter55/fsl_groups/fslg_csf_autism/compute/HBN_Project/code/subjids/release1-7_ids.txt`; do
c3d ${subjDir}/${i}/FinalMasking/${i}_T1_stx_stripped_EMS_withoutVent_MID02.nrrd -o ${subjDir}/${i... |
ff4d99293e5deeac7c1a73f7f245abeff9dfd7a75dc53f87d4c08d5c17a593d0 | Shell | 346 | 6 | layer=$1
kernel=$2
chen2meme layer$layer/kernel-$kernel-unified-dict.chen > layer$layer/kernel-$kernel-unified-dict.meme
chen2meme layer$layer/kernel-$kernel-segs.chen > layer$layer/kernel-$kernel-segs.meme
tomtom --norc layer$layer/kernel-$kernel-segs.meme layer$layer/kernel-$kernel-unified-dict.meme -oc layer$layer... |
ba17796f57a612cb43339f2110a7f45c209358f8deaad0382ce5ec58175809f9 | Shell | 347 | 11 | #!/bin/bash
for subj in `cat /fslhome/mpeter55/fsl_groups/fslg_csf_autism/compute/HBN_Project/code/subjids/release1-7_ids.txt`; do
sbatch \
-o ~/logfiles/${1}/output_${subj}.txt \
-e ~/logfiles/${1}/error_${subj}.txt \
~/fsl_groups/fslg_csf_autism/compute/HBN_Project/code/freesurfer_code/freesurfer_stats_table2.s... |
324e50fe64b954ab152afd31ffd9ef839747bc28f2cef640e53b25b89d52b8c0 | Shell | 348 | 10 | #!/bin/bash
# cpplint
echo 'Checking code style of C++ codes...'
python3 tests/lint/lint.py dgl cpp include src || exit 1
python3 tests/lint/lint.py dgl_sparse cpp dgl_sparse/include dgl_sparse/src || exit 1
# pylint
echo 'Checking code style of python codes...'
python3 -m pylint --reports=y -v --rcfile=tests/lint/py... |
861a9118149ee9af5eb32b24ed3b664f461f235d8ccb4ceabaff653b2c36b1ad | Shell | 355 | 11 | #!/bin/bash
GenDir=/fslhome/mpeter55/fsl_groups/fslg_csf_autism/compute/HBN_Project
ResultsDir=${GenDir}/output
time=release1-7
for i in `cat ${GenDir}/code/subjids/${time}_ids.txt`; do
cmtk statistics ${ResultsDir}/${time}/${i}/FinalMasking/${i}*_MID02.nrrd > ${ResultsDir}/${time}/${i}/${i}_FinalStats.txt
echo Cal... |
d342401ad32e25877d119b6507279fb2c0aac04b1430998058ecd2e8bf63f22b | Shell | 355 | 6 | # install libraries for building c++ core on ubuntu
apt update && apt install -y --no-install-recommends --force-yes \
apt-utils git build-essential make wget unzip sudo \
libz-dev libxml2-dev libopenblas-dev libopencv-dev \
graphviz graphviz-dev libgraphviz-dev ca-certificates \
systemd... |
1d4f20f0c5dd6eca40b753627590870817592a96595002864c93b4ca34687b22 | Shell | 362 | 29 | #!/bin/bash
SRC=$1
TRG=$2
FSRC=all_${1}-${2}.${1}
FTRG=all_${1}-${2}.${2}
echo "" > $FSRC
for F in *${1}-${2}.${1}
do
if [ "$F" = "$FSRC" ]; then
echo "pass"
else
cat $F >> $FSRC
fi
done
echo "" > $FTRG
for F in *${1}-${2}.${2}
do
if [ "$F" = "$FTRG" ]; then
echo "pass"
... |
8f8673f4b74b2033db41af58beb6c2ca671d5ea3a64a91bb875b20a8d4262e3d | Shell | 368 | 17 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "NC_012920.1" -e "NC012920.1" \
| awk '{ if($3 > 0 && $2 > 10000 && $2 < 20000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}'`;
if [ -z "$RESULT" ]
then
echo -e "-\t-";
... |
0cfb43305b33d69edafdf84b63f89d90b040aabd9bb0b2d2fb7c95d857a5809b | Shell | 369 | 9 | #!/bin/sh
git lfs install
git lfs clone --recurse-submodules https://github.com/perslab/CELLECT.git
rsync -a --remove-source-files STEAP/* CELLECT
rm -rf STEAP
mv CELLECT/ STEAP/
cd STEAP
conda env create -f environment_steap.yml # create conda env needed for running STEAP
conda env create -f ldsc/environment_munge_... |
30c6c24b8f3d399084fcabfcc8eb95d418567df225bfc371852a8785cb8bf142 | Shell | 369 | 10 | #!/bin/bash
#SBATCH -J res
#SBATCH --array=1-12
#SBATCH -n 4
#SBATCH --mem=128G
#SBATCH -t 1:00:00
#SBATCH -e /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.err
#SBATCH -o /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.out
module load matlab/R2021a
matlab-threaded -... |
2a0468eb07b4290eb137e308561008fd05e4d36679ed6e356c8fa73ead7bc2f1 | Shell | 372 | 4 | wget http://people.csail.mit.edu/ingraham/graph-protein-design/data/cath/chain_set.jsonl
wget http://people.csail.mit.edu/ingraham/graph-protein-design/data/cath/chain_set_splits.json
wget http://people.csail.mit.edu/ingraham/graph-protein-design/data/SPIN2/test_split_L100.json
wget http://people.csail.mit.edu/ingraham... |
e5f0d14359df311ef2dac5e2a5e4e675b1171c3b9953af40769943181f4a9220 | Shell | 377 | 11 | #!/bin/bash
export CIBW_SKIP="cp27-* cp36-* cp310-* pp* *_i686 *-win32"
export CIBW_TEST_EXTRAS="test"
export CIBW_TEST_COMMAND="python -m pytest {project}/python/tests -vv -s --skip-browser-tests"
export CIBW_MANYLINUX_X86_64_IMAGE=manylinux2014
script_dir="$(dirname "$0")"
root_dir="${script_dir}/../.."
cd "${root_... |
6b9c34c84e02be1662e135daa909a9ab27dd779b36e3115f51759c3fd1c2b8da | Shell | 378 | 10 | #!/bin/bash
#SBATCH -J 1-p1a
#SBATCH --array=1-70
#SBATCH -n 2
#SBATCH --mem=8G
#SBATCH -t 1:00:00
#SBATCH -e /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.err
#SBATCH -o /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.out
module load matlab/R2021a
matlab-threaded -... |
5861210a8952feb03e4ab28d658cbe58100c21d117fae1db6292ae38074f7456 | Shell | 381 | 17 |
# bash run.layer.sh <layer> <the number of kernels> <threads> <optional: the number of flexible motifs>
bash run.layer.sh 1 128 20
bash run.layer.sh 2 128 20
bash run.layer.sh 3 160 20
bash run.layer.sh 4 160 20
bash run.layer.sh 5 256 20
bash run.layer.sh 6 256 20
bash run.layer.sh 7 384 20
bash run.layer.sh 8 38... |
d51e95cb0d72445e649536a9201d4fd14882cd1f58b7fb7056d907ae0894cc5f | Shell | 381 | 12 |
layer=$1
kernel=$2
mkdir layer$layer
lk=layer$layer/treelock$kernel
if [[ ! -e $lk ]]; then
mkdir layer${1}/treelock${2}
python build_segment.py $layer $kernel
python build_dict.py $layer $kernel
CUDA_VISIBLE_DEVICES=-1 python build_tree.py $layer $kernel
tomtom layer$layer/kernel-$kernel-unified-d... |
68cbbd9180b8afc5ed1837ebb9fe5c8814620f7b33330860dbabc52ddbf37b04 | Shell | 383 | 17 |
# bash run.layer.sh <layer> <the number of kernels> <threads> <optional: the number of flexible motifs>
bash run.layer.sh 1 128 20
bash run.layer.sh 2 128 20
bash run.layer.sh 3 160 20
bash run.layer.sh 4 160 20
bash run.layer.sh 5 256 20
bash run.layer.sh 6 320 20
bash run.layer.sh 7 512 20
bash run.layer.sh 8 64... |
7c5c9deeba496842ae7dbf8c3c615504c5a2b892b6fa633cd59bc5152393224e | Shell | 386 | 21 | #!/usr/bin/env bash
set -eo pipefail
if ! command -v micromamba >/dev/null 2>&1; then
echo "micromamba is required for CI setup" >&2
exit 1
fi
eval "$(micromamba shell hook --shell bash)"
if ! micromamba env list | awk '{print $1}' | grep -qx 'smcore'; then
micromamba create -y -f env.yaml
fi
set +u
micromamb... |
7df590324f890ec52cf7697e710145005dc7c1ebcbceac1c90d45d07c8476302 | Shell | 386 | 10 | #!/bin/bash
#SBATCH -J p1a-p2c
#SBATCH --array=1-59
#SBATCH -n 2
#SBATCH --mem=16G
#SBATCH -t 1:00:00
#SBATCH -e /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.err
#SBATCH -o /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.out
module load matlab/R2021a
matlab-threade... |
49b27bfcd56ace31b597e45fde550e2556598d3b7ebc6216421f5be1f233a86f | Shell | 387 | 17 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "cutavirus" -e "Cutavirus" \
| grep -a -e "omplete" \
| awk '{ if($3 > 0 && $2 > 3000 && $2 < 6000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}'`;
if [ -z "$RESULT" ]
then
... |
44a30dd63f804345aa3c6644b3f4604b0c91a86deefecfb22ac22bc11a8b0946 | Shell | 389 | 10 | #!/bin/bash
#SBATCH -J p1a-p3a
#SBATCH --array=1-59
#SBATCH -n 2
#SBATCH --mem=16G
#SBATCH -t 1:00:00
#SBATCH -e /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.err
#SBATCH -o /users/jlee123/scratch/job/adp-1-3xtg-cortex/Immunofluorescence/%J--%a.out
module load matlab/R2021a
matlab-threade... |
862de91c930b334f58610e97789873f122c0c3b5cb02552c99ee10b5c12f0203 | Shell | 389 | 12 |
layer=$1
kernel=$2
mkdir layer$layer
lk=layer$layer/treelock$kernel
if [[ ! -e $lk ]]; then
mkdir layer${1}/treelock${2}
python build_segment.py $layer $kernel
python build_dict.py $layer $kernel
CUDA_VISIBLE_DEVICES=-1 python build_tree.py $layer $kernel
tomtom --norc layer$layer/kernel-$kernel-u... |
6b81f37d165fa61f1a1558b28d182aa8275e16f17ef8f16ba6b23f14566a06ab | Shell | 400 | 15 | #! /bin/bash
imagename=nhp-abcd-bids-pipeline
datestamp=$( date +%Y%m%d )
tarfile=${imagename}_${datestamp}.tar
pushd /mnt/max/shared/code/internal/utilities/dcan-stack_dockerfiles/${imagename}
docker build . -t dcanlabs/${imagename}
popd
pushd /mnt/max/shared/code/internal/utilities/docker_images
docker save -o ${ta... |
8b3f646895617e770b861b15e3f6388c9641ac6c2249e80035ed4fb79bf3361b | Shell | 403 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "Enterovirus" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 4000 && $2 < 12000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}'`;
if [ -z "$RE... |
defef366b162e9faa7034b3e228e5198d8559b38233883070dbfcae80b6e73df | Shell | 410 | 19 | #!/bin/bash
ORGAN=$1; shift
TopFile=$1; shift
#
RESULT=`cat $TopFile \
| grep -a -e "cutavirus" -e "Cutavirus" \
| grep -a -e "complete" \
| awk '{ if($3 > 0 && $2 > 3000 && $2 < 6000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}'`;
if [... |
dfc81116cdeb3d25bf0a316507ebc3ae3ad855f2c3e8b5de32b483caa6b79c17 | Shell | 412 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "SEN-V" -e "SEN virus" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 1500 && $2 < 10000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}'`;
if ... |
a56213ad348cc55faf5a9bac8df1f844e679d9d2c0187fb06f1bdfcbac372c8f | Shell | 419 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "hepatitis D" -e "Hepatitis D" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 1200 && $2 < 5000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}... |
dad95b120cc596135371d9a3987875a4f3fd1113123190db2e5207d47e972b2f | Shell | 419 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "hepatitis B" -e "Hepatitis B" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 1500 && $2 < 8000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;}... |
04c8a1aa4e65ed4baad9ddb0018e61528463b46b29612e179ae93f868baa4a1d | Shell | 420 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "hepatitis A" -e "Hepatitis A" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 6000 && $2 < 12000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;... |
47b1f2c8bd47a401c07e60ff4f7f137aa24c869c266518a47fb82f79759ac499 | Shell | 420 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "hepatitis C" -e "Hepatitis C" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 7500 && $2 < 12000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;... |
c0e1f07aef3ca831d2f851678988675d8684db13362670814121117747ca91ac | Shell | 420 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "hepatitis E" -e "Hepatitis E" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 5000 && $2 < 12000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"\t"$2;... |
efba12feef7425c55de2b0173ebab5c5f30eb2f1a6169597824dd8b0aa4cfb00 | Shell | 426 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e " VARV" -e "variola" -e "Variola" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 100000 && $2 < 300000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t' \
| awk '{ print $1"... |
5c19373993f197d30c1c7fc86eafbc4b89df007c31e34eb91cad8d6abc509cd8 | Shell | 435 | 13 | #!/bin/bash
#
# TO SEE OTHER DATABASES: update_blastdb.pl --showall
#
# INSTALL ======================================================================
#
mkdir -p ../system_files/blast_dbs
mkdir -p ../system_files/blast_dbs/nt
cd ../system_files/blast_dbs/nt/
update_blastdb.pl --decompress --passive --timeout 500 --for... |
c847e231c51a12251f778a470c30d20f99cf58f8949b3b0451697bed33900a98 | Shell | 445 | 7 | #!/bin/bash
#
echo -e "\e[34m[TRACESPipe]\e[32m Generating adapters file (adapters.fa) ...\e[0m";
#
printf ">PrefixPE/1\nTACACTCTTTCCCTACACGACGCTCTTCCGATCT\n>PrefixPE/2\nGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT\n>PE1\nTACACTCTTTCCCTACACGACGCTCTTCCGATCT\n>PE1_rc\nAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTA\n>PE2\nGTGACTGGAGTTCAGACGTGT... |
9db9529ee85ad96e9e2b4ec07255e4612a1352063162791f5ff628432a7426fc | Shell | 446 | 16 | #!/bin/bash
#SBATCH -p general
#SBATCH -n 1
#SBATCH --mem=20g
#SBATCH -t 7:00:00
i=$1
#for j in {1..22}
#do
# awk '{print $1,$2,$3,FILENAME}' /pine/scr/n/i/nil1/trans-QTL/progenitor/chr${i}/P*chr${j}-*.ps > /pine/scr/n/i/nil1/progenitor_big_trans_chr${i}_${j}.txt
#done
cat /pine/scr/n/i/nil1/progenitor_big_trans_c... |
6a7956eb0cf4634c4916b2c5341292504843bece3c24cd937ccb2490e0ff8ce5 | Shell | 448 | 16 | ### Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease
### GSE147672
## GSM4441827 scATAC Control Substantia Nigra 1 (SRR11442505)
wget https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos3/sra-pub-run-19/SRR11442505/SRR11442505.1
## GSM4441828 scATAC Control Substantia... |
c0aa57f380ce4a0b9bc7c20f3729927cea6661564f68096bcc8aa7e5fcc32180 | Shell | 448 | 20 | #!/bin/bash
ORGAN=$1; shift
TopFile=$1; shift
#
RESULT=`cat $TopFile \
| grep -a -e " VARV" -e "variola" -e "Variola" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 100000 && $2 < 300000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_' '\t... |
dbb2b9850e8f0663be04ff607bf296af46242a0dbd077991da7ebe7c6b0ac6db | Shell | 448 | 14 | #!/bin/bash
# Will download in- and out-of-facility data. For detailed requirements,
# consult the comments in the shell scripts mentioned below.
# Note that this will download roughly 1TB of sequencing data!
IN_FACILITY_PATH="./In_facility_mutation_calling_pipeline_mouse.sh"
KOTANI_PATH="./Out_of_facility_mutation_c... |
a05314335be95ebf63cc5ec84f44a05cddc27a51b4a969b8d87f2aed8ae8ee0c | Shell | 453 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -e "Severe acute respiratory syndrome coronavirus 2" -e "SARS-CoV-2" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 25000 && $2 < 31000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
| tr '_... |
70769c64d9481976f61bd747b900205cf403daffc66ac3115975286a06d46e94 | Shell | 454 | 12 | #!/bin/bash
#SBATCH -J cobel # A single job name for the array
#SBATCH -n 1 # Number of cores
#SBATCH -N 1 # All cores on one Node
#SBATCH --mem 20000 # Memory request
#SBATCH -t 1-00:00 # Maximum execution time (D-HH:MM)
#SBATCH -o cobel_%A_%a.out # Standard output
#SBATCH -e cobel_%A_%a.err # Standard error
#module l... |
8b972bca8a3445e685b175a54db652ad35d25830052e6876278a37215f9d49ea | Shell | 457 | 20 | #!/bin/bash
set -e
# Default building only with cpu
DEVICE=${DGL_BENCH_DEVICE:-cpu}
pip install -r /asv/torch_gpu_pip.txt
# build
# 'CUDA_TOOLKIT_ROOT_DIR' is always required for sparse build as torch1.13.1+cu116 is installed.
CMAKE_VARS="-DUSE_OPENMP=ON -DBUILD_TORCH=ON -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda"
if ... |
a75d01b473bd313d976c5980347fcbc5e333185b05de00b76f8c29f5b555f9a2 | Shell | 458 | 12 | #!/bin/bash
#
echo -e "\e[34m[TRACESPipe]\e[32m Download Reference Human Y chromosome (cy.fa) from NCBI ...\e[0m";
#
efetch -db nucleotide -format fasta -id "NC_000024.10" > cy.fa
#
#rm -f hs_ref_GRCh38.p12_chrY.fa.gz
#wget ftp://ftp.ncbi.nlm.nih.gov/refseq/H_sapiens/H_sapiens/Assembled_chromosomes/seq/hs_ref_GRCh38.p1... |
47acb1f8770a568a82532d6f18822e4c6f2116e605e168090d677a08f9943e03 | Shell | 459 | 19 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e " HPV" -e "_HPV" -e "apillomavirus" \
| grep -a -e "human" -e "Human" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 5000 && $2 < 10000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-/" \
|... |
f5a498b72a041ce4bd5a3879235c63d10d411b2b5f9df4aaeb80d6f21ab40aac | Shell | 461 | 14 | #!/bin/bash
#
# ==============================================================================
#
rm -f alg_tot.fasta alg_pa_tot.fasta alg_tot.fasta alg_pa_tot.fasta
#
wget https://www.hmtdb.uniba.it/download_file?dataset=alg_tot.zip -O alg_tot.zip
wget https://www.hmtdb.uniba.it/download_file?dataset=alg_pa_tot.zip -O ... |
54343088f7b487db732c3c8664987c1c4e862d5e505cf810a0740d7a3994a427 | Shell | 463 | 20 | #!/bin/bash
# Script to download all the benchmarking Nanopore data
# usage:
# bash download_all.sh OUTPUT_DIR
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
# make the output dir if does not exists
if [ ! -d $1 ]
then
mkdir $1
else
echo "Download directory exists"
fi
source "... |
ad17a439eea4d3b594ba03b899081a9ca096d7395ef666f47108d19058e4a24a | Shell | 464 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "HBoV " -e "bocavirus isolate" -e "HBoV1" \
| grep -a -e "human" -e "Human" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 4000 && $2 < 6000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC-... |
1bf90d8f20a739f1349318fbe80e1e3a81a9a16a542bb624831e6f9431f81c37 | Shell | 465 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "Adeno-associated virus" -e "Adeno associated virus" \
| grep -v "Adenovirus" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 2000 && $2 < 9000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC\_/NC... |
b6a2d8df0a8f2bd45414ef40816ab12e763a414d58b3dcc44f514062dbffdb0d | Shell | 466 | 14 | #!/bin/bash
#
cat VDB.fa | grep -a -e "B19 " -e "parvovirus" -e "rythrovirus" -e "rythroparvovirus" | grep -a -v "olyomavirus" | grep -a -v "otavirus" | grep uman | tr ' ' '\t' | awk '{print $1;}' | sed 's/^.//' > access_codes_b19.txt
mapfile -t CODES < access_codes_b19.txt
#
rm -f B19_REFS.fa;
for xcode in "${CODES[@]... |
4964fa38f8b689c36ef500bdbfabe8032a4049e58074fc9fe554d393073af4f5 | Shell | 471 | 21 | #!/bin/bash
#
# DOWNLOAD: https://www.ncbi.nlm.nih.gov/genome/viruses/
#
# https://www.biostars.org/p/259792/
#
# CHECK ALSO THIS: https://www.viprbrc.org/brc/vipr_allSpecies_search.spg?method=SubmitForm&decorator=vipr
#
tail -n +3 ../system_files/taxid10239.nbr > DATA.nbr
#
rm -f VDB.fa
#
mapfile -t ENTRIES < DATA.nbr... |
5b5047ee8f1f4fa8dc73c04ccf91a8bb9d2b60e5784913e1eeec69209afd7325 | Shell | 471 | 21 | #!/bin/bash
ORGAN=$1; shift
TopFile=$1; shift
#
RESULT=`cat $TopFile \
| grep -a -e " HPV" -e "apillomavirus" \
| grep -a -e "human" -e "Human" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 5000 && $2 < 10000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "s/NC... |
752c3f490f8e40b3811951b2c312c8a1e9981cdd40d68f571102c856d123ec7c | Shell | 474 | 7 | layer=$1
kernel=$2
chen2meme layer$layer/kernel-$kernel-dict.chen > layer$layer/kernel-$kernel-dict.meme
#chen2meme layer$layer/kernel-$kernel-test-dict.chen > layer$layer/kernel-$kernel-test-dict.meme
#tomtom --norc layer$layer/kernel-$kernel-test-dict.meme layer$layer/kernel-$kernel-test-dict.meme -oc layer$layer/k... |
86bb99de5e166210225610a1f65c5610f91939aba542cc7cceb85f37e1ce86b8 | Shell | 474 | 19 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "Adenovirus" \
| grep -v "Adeno-associated virus" \
| grep -v "Adeno associated virus" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 3000 && $2 < 7000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "... |
ad542b66383115f7baa084b188d6a4de47d729a33c57719ac7c6945a639952be | Shell | 475 | 19 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e " HERV" -e "endogenous retro" -e "endogenous_retro" \
| grep -a -e "human" -e "Human" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 7000 && $2 < 12000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}' \
| sed "... |
be3985e986f4b894aab32cb03661080c5c2a918ae5c9a4d1218e5bc390c713e6 | Shell | 477 | 8 | #!/bin/sh
# Last steps of installing the `transformers` clone at `/<workdir>/transformers`, shared by the GPU images.
set -e
# `kernels` may give different outputs (within 1e-5 range) even with the same model (weights) and the same inputs
python3 -m pip uninstall -y kernels
# When installing in editable mode, `transfor... |
e5fecbda795a75249029907c0256ffdaa6050bc71396a3742e2dade137b8cf0c | Shell | 486 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "imian virus 40" -e "imian_virus_40" -e "imian_Virus_40" -e "imian Virus 40" -e "simian virus 40" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 2000 && $2 < 6000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;}... |
eae41ab822e9a28068cbdcad93428cab9f33cfbdd9aa52e271e842ef39034754 | Shell | 486 | 20 | #!/bin/bash
ORGAN=$1; shift
TopFile=$1; shift
#
RESULT=`cat $TopFile \
| grep -a -e "HBoV " -e "bocavirus isolate" -e "HBoV1" \
| grep -a -e "human" -e "Human" \
| grep -a -e "omplete genome" -e "omplete_genome" \
| awk '{ if($3 > 0 && $2 > 4000 && $2 < 6000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;... |
eb73715ee981ddc53722b15a9bb7f71be6a1c1b7138e92a79c92773e7a7c655a | Shell | 486 | 20 | #!/bin/sh
tapfile=$1/results.tap
logfile=$2
rm -f $tapfile
rm -f execution_log2.txt
cat $logfile | tr '\\' '/' | sed 's/C://g' | sed 's/://g' >execution_log2.txt
awk -f $1/_automation_tools/create_tap.awk execution_log2.txt
test_count=` grep -n "EXAMPLES_test" execution_log2.txt | wc -l`
# test_count=`wc -l $tapfi... |
4b45ede7efd0bab706d17e314c3473779ec15adb4bef5daf0e1d982e76427063 | Shell | 487 | 18 | #!/bin/bash
#
RESULT=`cat top-metagenomics.csv \
| grep -a -e "BK_polyoma" -e "BK polyoma" -e "BK_virus" -e "BK virus" -e "BKPyV" -e "NC_001538" -e "NC001538" \
| grep -a -e "complete genome" -e "complete_genome" \
| awk '{ if($3 > 0 && $2 > 3000 && $2 < 7000) print $3"\t"$4; }' \
| head -n 1 \
| awk '{ print $1"\t"$2;... |
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