sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
28eb409468dae211a96a280c27deda008f0b3084c156addb50abfa773a90114c | Perl | 6,905 | 268 | #!/usr/bin/env perl
use warnings;
# Copyright 2015 Tokyo Institute of Technology (Authors: Takafumi Moriya and Takahiro Shinozaki)
# 2015 Mitsubishi Electric Research Laboratories (Author: Shinji Watanabe)
# Apache 2.0
# Acknowledgement This work was supported by JSPS KAKENHI Grant Number 26280055.
# Thi... |
d5a4919861662dd018415d827ebc542a4558595bd8e27fa6482d88d9d3ab3c5a | Perl | 6,945 | 304 | #!/usr/bin/env perl
# Oct 21, 2015 : Gaurav Kumar (Johns Hopkins University)
# GNU General Public License, v3.0
#
# This script was modified under GPL and is being distributed with
# Kaldi. It requires the preference and rule files
# (under LDC copyright) from LDC96L16. The main changes were
# - Outdated usage of per... |
6db8f470156f51d9dfda0e066db4a0e82e2fb5dfd39063ba83c3a44025be074f | Perl | 6,973 | 264 | #!/usr/bin/perl
use strict;
use File::Basename;
my $dirname = dirname(__FILE__);
my $infile = $ARGV[0];
my $heatmap = $ARGV[1];
my %core_cluster;
my %samples;
my %sequences;
my %matrix;
my %hash;
my $cl_num = 0;
my $nb_strains = 1;
open(M,">$heatmap.accessory_01matrix.txt");
open(PAN,">$heatmap.pangenes_01matrix.txt... |
57b22652f29f7b7bbe840c7aaa6f477f6872430d61da6f72a2e5642b924c8a08 | Perl | 7,000 | 219 | #!/usr/bin/env perl
#===============================================================================
# Copyright 2015 (Author: Yenda Trmal <jtrmal@gmail.com>)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy o... |
2925b01cfc12e3fcf91cc1307303d5473b260158cf2345a88e2750aadc2ccac7 | Perl | 7,202 | 187 | #!/usr/bin/perl
use MakeFasta_vert;
use RunSplash_vert;
use ProcessSplash_vert;
use ComposeClusters_vert;
use PrintOutput_vert;
use SP_vert;
foreach (@ARGV){
($key,$value) = split(/-/,$_);
$value =~ s/\.ds\./-/g;
$value =~ s/\.s\./ /g;
$properties{$key} = $value;
}
$properties{'ANNOTATION'} = "annotations/"... |
9fe99bce679a0d1615eae4128dc04f078fb86ad1c4a8b9b67d49b6bf6950942f | Perl | 7,468 | 224 | #!/usr/bin/perl
use locale;
use strict;
use ClusterManager;
## Model name ##
my $BASE_ID = $ENV{'TRAIN_NAME'};
defined($BASE_ID) || die("TRAIN_NAME environment variable needs to be set.");
## Path settings ##
my $BINDIR = $ENV{'TRAIN_BINDIR'};
defined($BINDIR) || die("TRAIN_BINDIR environment variable needs... |
36be2cd8808c1038e9eb180c9615d0f0d504da8779b0e4f2e5b6b404146b6093 | Perl | 7,733 | 204 | #!/usr/bin/env perl
# This program creates suggested suffix rules from a dictionary.
# It outputs quadruples of the form:
# suffix,base-suffix,psuffix,base-psuffix
# where "suffix" is the suffix of the letters of a word, "base-suffix" is
# the suffix of the letters of the base-word, "psuffix" is the suffix of the
# pr... |
768cf40272ea50da66286ec58a6f12e559dd6770e424c33b89871db3190a07a5 | Perl | 8,152 | 187 | #!/usr/bin/env perl
# This script takes three command-line arguments (typically files, or "-"):
# the suffix rules (as output by get_rules.pl), the rule-hierarchy
# (from get_rule_hierarchy.pl), and the words that we want prons to be
# generated for (one per line).
# The output consists of candidate generated pronu... |
02aef305cb71254cb20d28968f85a76d1a823f3c237243e50ced761fa1c174ec | Perl | 8,226 | 212 | #!/usr/bin/env perl
use warnings; #sed replacement for -w perl parameter
# Copyright 2010-2011 Microsoft Corporation
# 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/... |
80704de53db804168ccdea476e47ae0eb956c33f1ff0e4490147120a318acb7a | Perl | 8,247 | 198 | #!/usr/bin/env perl
# Copyright 2014 Johns Hopkins University (Author: Sanjeev Khudanpur), Vimal Manohar
# Apache 2.0
################################################################################
#
# This script was written to check the goodness of automatic segmentation tools
# It assumes input in the form of tw... |
1a6e617300a41fc79cf5c905d321e1eda03bbc2ff00121d54bfafd419fd6b340 | Perl | 8,317 | 219 | #!/usr/bin/perl -w
use strict;
use warnings;
use diagnostics;
use File::Glob ':glob';
use File::Basename;
use Getopt::Long;
####Variables
my $help;
my $inputFile;
my $outputFile;
my $GQ;
my $callRate;
my $removeNoGT;
my $writeOnlyPass;
####Get options
GetOptions(
"h" => \$help,
... |
f5c5ca19f2d1cc97ad607458531594d9d4b4720393b4967cfedbaa626ad2eb34 | Perl | 8,523 | 381 | #!/usr/local/bin/perl
my $sv_path = $ARGV[1];
if(-d $sv_path){
print "The folder for saving results is confirmed. \n";
}else{
mkdir($sv_path);
}
# print "save path is: $sv_path\n";
open SEQ, "$ARGV[0]" or die $!;
$sequence="";
while (<SEQ>) {
chomp;
$sequence=join(" ",$sequence,$_);
}
close SEQ;
#print "$seq... |
36c2735f732478e680bec075340f2e36daed8c933fdc6fae80c49357f4cb62a1 | Perl | 8,669 | 268 | #!/usr/bin/perl
# This script performs discriminative training using the Extended Baum-Welch
# algorithm. Supported discriminative criteria: MMI, MPE, MWE, MPFE.
# Prerequisites:
# - Trained ML model, which is used to initialize the discriminative training
# - Denominator lattices (hmmnets) generated with generate... |
b866557a54aa164db5bfc23c006dade5dd4712d3016430413701ee656fb837c7 | Perl | 9,038 | 393 | #!/usr/bin/perl
#
###########################################################
#
# This script is used to generate data for average graph.
#
###########################################################
# step 1, readin coordinate info
# and determine which genes to include
use List::Util qw(first max maxstr min minst... |
bdb4a496c039c88ddb04b9842bb8de103e7a1807becf8cf7270de581943cbfb4 | Perl | 9,137 | 320 | #!/usr/bin/perl
use strict;
use YAML qw(LoadFile);
use Data::Dumper qw(Dumper);
use File::Basename;
my $dirname = dirname(__FILE__);
my %continents;
open(F,"countries.txt");
<F>;
while(my $line =<F>){
chomp($line);
my ($continent,$country) = split(/,/,$line);
$continents{$country} = $contine... |
0dbe85d9ecebf104fa09f576411d4c6c59379c12a17615fa21c72fe309a57530 | Perl | 9,406 | 232 | #!/usr/bin/env perl
use Getopt::Long;
################################################################################
# Convert a CTM file produced by decoding a long segment, typically several min
# long, into a sequence of shorter segments of duration 10-15 seconds. Produce
# a segments file of the form used for K... |
7fb973d76e3fc174dafc4bd0be6af1def1cf893ab0ba289fec4017e938a098dc | Perl | 9,410 | 232 | #!/usr/bin/env perl
use Getopt::Long;
################################################################################
# Convert a CTM file produced by decoding a long segment, typically several min
# long, into a sequence of shorter segments of duration 10-15 seconds. Produce
# a segments file of the form used for K... |
a7f3da0812c184f1ac954681bf9483be8e2fa89a9928445e34428a7103b3985c | Perl | 9,693 | 360 | #!/usr/bin/env perl
#===============================================================================
# Copyright 2016 (Author: Yenda Trmal <jtrmal@gmail.com>)
#
# 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 o... |
56c82bf7b776cc4b30352dc5ddb11a6ebc12d1a6c677d5aa582cb2b966705247 | Perl | 10,463 | 347 | #!/usr/bin/perl
use strict;
use File::Basename;
my $dirname = dirname(__FILE__);
system("wget https://ftp.ncbi.nlm.nih.gov/genomes/GENOME_REPORTS/prokaryotes.txt");
system("wget https://ftp.ncbi.nlm.nih.gov/genomes/GENOME_REPORTS/eukaryotes.txt");
my %continents;
open(F,"countries.txt");
<F>;
while(my $line =<F>){
... |
1d4a7ff2acf6d6d707f1666fca150f5e5252a9bd9a9064ac2b67f18eb39d8edd | Perl | 10,859 | 340 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<trunc_seq.pl> - truncate sequence files
=head1 SYNOPSIS
C<perl trunc_seq.pl 20 3500 seq-file.embl E<gt>
seq-file_trunc_20_3500.embl>
B<or>
C<perl trunc_seq.pl file_of_filenames_and_coords.tsv>
=head1 DESCRIPTION
This script truncates sequence files ac... |
c2ac1df4285c40d2b36a8a10fe88790197fc35f9eb860e57e8ed8fd063e962e6 | Perl | 11,105 | 326 | #!/usr/bin/env perl
#===============================================================================
# Copyright 2015 (Author: Yenda Trmal <jtrmal@gmail.com>)
#
# 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 o... |
a7a91a98b2f2cd8422ed7cb7945dec7a24a511df33f876aac8fb2f70608fb1a7 | Perl | 11,630 | 422 | #!/usr/bin/env perl
#===============================================================================
# Copyright 2016 (Author: Yenda Trmal <jtrmal@gmail.com>)
#
# 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 o... |
67d5b29d7781d080b4d340ccd5cbe29e45e7131009c56c81a2beae8238ba9717 | Perl | 11,897 | 339 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<prot_binary_matrix.pl> - create a presence/absence matrix from
C<prot_finder.pl> output
=head1 SYNOPSIS
C<perl prot_binary_matrix.pl blast_hits.tsv E<gt> binary_matrix.tsv>
B<or>
C<perl prot_finder.pl -r report.blastp -s subject.faa | perl prot_binary_m... |
7c6fb0f6f1175e3d6d6c2ba70bbddada2f36b3e1958b6dd7ab606a73b055a0ed | Perl | 12,816 | 339 | #!/usr/bin/perl
use warnings;
use strict;
use Getopt::Long qw(GetOptions);
# Super script Mulispecies machine learning
my $outfile="All_summarised_GOLD\.tsv";
open(my $out, ">", $outfile) or die "Could not open $outfile \n";
my $version;
my $background;
my $foreground;
my $helpFlag;
my $expr_data="Experimental_data... |
98d57c3c382a5f08407c72325d443a7a4c042221de15ec89810f4d7a6ff85f41 | Perl | 13,211 | 311 | #!/usr/bin/env perl
use Getopt::Long;
use Encode;
################################################################################
#
# Script to prepare a NIST .stm file for scoring ASR output. Based on the files
# that are naturally created for Kaldi acoustic training:
#
# - data/segments: contains segmentID, reco... |
75d71f39657065b34ba2c7baf07329d1c79a35aa557e4d79ff39eb523b8605e7 | Perl | 13,436 | 415 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<cdd2cog.pl> - assign COG categories to protein sequences
=head1 SYNOPSIS
C<perl cdd2cog.pl -r rps-blast.out -c cddid.tbl -f fun.txt -w whog>
=head1 DESCRIPTION
The script assigns COG (L<cluster of orthologous
groups|http://www.ncbi.nlm.nih.gov/COG/>) ca... |
051d7707dd348cb175f4c327991764a885b680d50ad25db43da95bdf691201b6 | Perl | 13,814 | 327 | #Copyright 2006-2012 Annaliese Beery
#[MIT Open Source License]
#Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the #"Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify,... |
7acd417b4e649be4c5aa590e2b46fe9435edffe2007d101a750e07133f283b24 | Perl | 13,829 | 390 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<order_fastx.pl> - order sequences in FASTA or FASTQ files
=head1 SYNOPSIS
C<perl order_fastx.pl -i infile.fasta -l order_id_list.txt
E<gt> ordered.fasta>
=head1 DESCRIPTION
Order sequence entries in FASTA or FASTQ sequence files according to
an ID list ... |
0d202bbd331366edc93144a4fb9859aa2a74b4616ce3b377ec71c333f27adeed | Perl | 14,785 | 405 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<sample_fastx-txt.pl> - random subsampling of FASTA, FASTQ, or TEXT files
=head1 SYNOPSIS
C<perl sample_fastx-txt.pl -i infile.fasta -n 100 E<gt> subsample.fasta>
B<or>
C<zcat reads.fastq.gz | perl sample_fastx-txt.pl -i - -n 100000
E<gt> subsample.fastq... |
21c2412753a01c55671ec171578591ebbfbff75aa2ea5080f746656705ee6e49 | Perl | 14,893 | 342 | #!/usr/bin/env perl
use Getopt::Long;
use Encode;
################################################################################
#
# Script to prepare a NIST .stm file for scoring ASR output. Based on the files
# that are naturally created for Kaldi acoustic training:
#
# - data/segments: contains segmentID, reco... |
ad7570b2e57f49cdaf8012d1618f28c30d763865a0a0a995082c82212b747ece | Perl | 14,910 | 533 | #!/usr/bin/perl
use strict;
use File::Basename;
my $dirname = dirname(__FILE__);
my $pav_matrix = $ARGV[0];
my $prot_dir = $ARGV[1];
my $cog_outfile = $ARGV[2];
my $kegg = $ARGV[3];
my $cog_stats2 = $ARGV[4];
my $cog_clusters = $ARGV[5];
my $function_clusters = $ARGV[6];
my $strain_info_file = $ARGV[7];
my %cogs_ca... |
50511e67225e425cbac10c02641421670f9f356b059048078081a123263d76f0 | Perl | 15,105 | 471 | # Perl Routines to Manipulate CGI input
# cgi-lib@pobox.com
# $Id: cgi-lib.pl,v 2.18 1999/02/23 08:16:43 brenner Exp $
#
# Copyright (c) 1993-1999 Steven E. Brenner
# Unpublished work.
# Permission granted to use and modify this library so long as the
# copyright above is maintained, modifications are documented, and... |
d0b3dc98ca2885fcfb4e3b3932928f365150eb9e65e1af2f7403a7009cb3a7e4 | Perl | 16,844 | 404 | #!/usr/bin/env perl
use Getopt::Long;
use Data::Dumper;
###############################################################################
#
# Convert a Babel-formatted dictionary to work with Kaldi, and optionally
# add non-speech "words" that appear in the transcription. e.g. <laughter>
#
# Convert dictionary from entr... |
712e25a6bc88c5e9dcf7d2f9fe495891cdc085c7377265eeaeca32bfea603b2a | Perl | 16,886 | 524 | #!/usr/bin/perl
# DO NOT USE THIS SCRIPT DIRECTLY! Copy it to your own directory and
# modify appropriately. You MUST modify at least the path settings,
# training file list and BASE_ID/initial model names!
# Run this script at your desktop machine, which acts as the host
# for the Condor batch system.
use lib '/sha... |
1cde38d738b3b93d3325b9ea33639e6c3533090a3377b4134090f90bb6329af6 | Perl | 16,900 | 404 | #!/usr/bin/env perl
use Getopt::Long;
use Data::Dumper;
###############################################################################
#
# Convert a Babel-formatted dictionary to work with Kaldi, and optionally
# add non-speech "words" that appear in the transcription. e.g. <laughter>
#
# Convert dictionary from entr... |
54637dffe55927897c8ffd1a8df92627d89ad0f244b159ac3c679a8e98891ac2 | Perl | 16,919 | 479 | #!/usr/bin/perl
# Generates HMM networks for model training.
# Options:
# -n Generate numerator networks (ML training)
# -d Generate denumerator networks (discriminative training)
# -o Use original PHN transcriptions without vocabulary (only -n)
# -e Skip generating hmmnets if t... |
a67c1fa6f53615a8851685f8a092a59db6519880e0e774629877bff44ca64817 | Perl | 16,926 | 405 | #!/usr/bin/env perl
use Getopt::Long;
use Data::Dumper;
###############################################################################
#
# Convert a Babel-formatted dictionary to work with Kaldi, and optionally
# add non-speech "words" that appear in the transcription. e.g. <laughter>
#
# Convert dictionary from entr... |
99682e6d1cec8db865c6fa06add103c2f5a0565d1d3ee8275d087c786d072109 | Perl | 17,390 | 417 | #!/usr/bin/env perl
use Getopt::Long;
use Data::Dumper;
###############################################################################
#
# Convert a Babel-formatted dictionary to work with Kaldi, and optionally
# add non-speech "words" that appear in the transcription. e.g. <laughter>
#
# Convert dictionary from entr... |
09ac7524948ee52b4fb374a587dbf96b1f9881baa28ccca1e1c117fde90334fc | Perl | 17,443 | 456 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<calc_fastq-stats.pl> - basic statistics for bases and reads in a FASTQ file
=head1 SYNOPSIS
C<perl calc_fastq-stats.pl -i reads.fastq>
B<or>
C<gzip -dc reads.fastq.gz | perl calc_fastq-stats.pl -i ->
=head1 DESCRIPTION
Calculates some simple statistic... |
95fd296bb50c7aaaa906d05cb7323350730ecc8827a56ddabbdee5b71d0d95b2 | Perl | 17,917 | 522 | #!/usr/bin/perl
# This is an example script showing how to use opt_ebw_d to control EBW training.
# It shares many parts with train_ebw.pl
# Prerequisites:
# - Trained ML model, which is used to initialize the discriminative training
# - Denominator lattices (hmmnets) generated with generate_den_hmmnets.pl,
# ... |
6508ea333d70840833be0c6ee6c39cfa7630472b417347e45e750dbade07c26e | Perl | 18,000 | 545 | #!/usr/bin/env perl
#
#
# export2sam.pl converts GERALD export files to SAM format.
#
#
#
########## License:
#
# The MIT License
#
# Copyright (c) 2008-2010 Genome Research Ltd.
# Modifications Copyright (c) 2010 Illumina, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this ... |
a5ac19ad2c0343c98192c41bf373350472e9a83ba2e506fc64e249dc2c3e3645 | Perl | 18,776 | 381 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<genomes_feature_table.pl> - create a feature table for genomes in EMBL and GENBANK format
=head1 SYNOPSIS
C<perl genomes_feature_table.pl path/to/genome_dir E<gt> feature_table.tsv>
=head1 DESCRIPTION
A genome feature table lists basic stats/info (e.g. ... |
b16b17581bc898418d907bd2cbacba2c8d0fdaf05d1049bd3d22ec670d640110 | Perl | 20,746 | 636 | #!/usr/bin/perl
use locale;
use strict;
use ClusterManager;
## Model name ##
my $BASE_ID = $ENV{'TRAIN_NAME'};
defined($BASE_ID) || die("TRAIN_NAME environment variable needs to be set.");
## Path settings ##
my $BINDIR = $ENV{'TRAIN_BINDIR'};
defined($BINDIR) || die("TRAIN_BINDIR environment variable needs... |
387e3083b4a298ebca03645e5438560ba49b075d24cbbf8db1871461ae529a68 | Perl | 21,047 | 499 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
ecoli_mlst.pl 25-10-2011
=head1 SYNOPSIS
C<perl ecoli_mlst.pl -a fas -g fasta>
=head1 DESCRIPTION
The script searches for multilocus sequence type (MLST) alleles in
I<E. coli> genomes according to Mark Achtman's schem... |
f9e87ba728b70f896e2db4aa12ca103b2ecf4e1a0125e0ba6f164c8ee0ebb43b | Perl | 21,058 | 408 | #!/usr/bin/perl
use warnings;
use strict;
use File::Find; # module to traverse directory trees
my $usage = << "USAGE";
#######################################################################
# $0 genbank|refseq [y] #
# #
... |
92160283a8de5fad17bba382110dec5c0eda0820f87244178fe445e5c0b85520 | Perl | 21,558 | 478 | #!/usr/bin/env perl
use Getopt::Long;
########################################################################
#
# Script to prepare the Babel acoustic training data for Kaldi.
#
# - Place transcripts in a file named "text"
# Each line contains: utteranceID word1 word2 ...
#
# - Place the utterance-to-speaker ... |
5e7e1b6445fe9ef7b97f2d671f38aa84b21154f3fda851c0a4d435dfc8286c7f | Perl | 21,591 | 519 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
blast_rod_finder.pl 07-11-2011
=head1 SYNOPSIS
C<perl blast_rod_finder.pl -q query.embl -r blastn.out -m 2000>
=head1 DESCRIPTION
This script is intended to identify region of differences (RODs)
between a nucleotide q... |
c56e9a71674b36993c094e14c71c13766113810e0b97919ab35d80fe4e559124 | Perl | 21,842 | 484 | #!/usr/bin/env perl
use Getopt::Long;
########################################################################
#
# Script to prepare the Babel acoustic training data for Kaldi.
#
# - Place transcripts in a file named "text"
# Each line contains: utteranceID word1 word2 ...
#
# - Place the utterance-to-speaker ... |
8ecb190d73b1776dab9ef064392c6293a8e389d1205e47c4fe0510b456d38f4c | Perl | 21,860 | 484 | #!/usr/bin/env perl
use Getopt::Long;
########################################################################
#
# Script to prepare the Babel acoustic training data for Kaldi.
#
# - Place transcripts in a file named "text"
# Each line contains: utteranceID word1 word2 ...
#
# - Place the utterance-to-speaker ... |
48fdbb77ea3a4a070f1d62babf270ebed9590d46a5fc8eef84edeccd6bde26de | Perl | 22,443 | 495 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<po2anno.pl> - create an annotation comparison matrix from Proteinortho5 output
=head1 SYNOPSIS
C<perl po2anno.pl -i matrix.proteinortho -d genome_fasta_dir/ -l -a E<gt> annotation_comparison.tsv>
=head1 DESCRIPTION
Supplement an ortholog/paralog output ... |
7242fb7e2818fa4dfc8b5b93067894800193167fa991a99111e01429db46f46a | Perl | 26,436 | 644 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<cds_extractor.pl> - extract protein or DNA sequences from CDS features
=head1 SYNOPSIS
C<perl cds_extractor.pl -i seq_file.[embl|gbk] -p>
=head1 DESCRIPTION
Extracts protein or DNA sequences of CDS features from a
(multi)-RichSeq file (e.g. EMBL or GENB... |
cf7b4530957555b6216419e932820416016ab9c2c94d3265a44aa5b8e2e0947e | Perl | 29,134 | 691 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<sam_insert-size.pl> - insert size and read length statistics for paired-end reads
=head1 SYNOPSIS
C<perl sam_insert-size.pl -i file.sam>
B<or>
C<samtools view -h file.bam | perl sam_insert-size.pl -i ->
=head1 DESCRIPTION
Calculate insert size and rea... |
9065597e708b8455d99750a0017a3095326ca955056db004063fe82f428c9f5f | Perl | 31,910 | 730 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<tbl2tab.pl> - convert tbl to tab-separated format and back
=head1 SYNOPSIS
C<perl tbl2tab.pl -m tbl2tab -i feature_table.tbl -s -l locus_prefix>
B<or>
C<perl tbl2tab.pl -m tab2tbl -i feature_table.tab -g -l locus_prefix
-p "gnl|dbname|">
=head1 DESCRIP... |
2dfd6395da73c968c541521be76ff332f037b24bd7df048e96a0d7c0f4236d68 | Perl | 37,470 | 763 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<prot_finder.pl> - search for query protein homologs in annotated
bacterial genomes with BLASTP
=head1 SYNOPSIS
C<perl prot_finder.pl -r report.blastp -s subject.faa E<gt> blast_hits.tsv>
=head1 DESCRIPTION
This script is intended to search for homologou... |
76210a1adb75e9a793a8e616354bb92ccaed9a4233fa42eb10b25acf95edb54e | Perl | 38,447 | 712 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<binary_group_stats.pl> - categorize binary matrix rows according to
column groups
=head1 SYNOPSIS
C<perl binary_group_stats.pl -i binary_matrix.tsv -g group_file.tsv
-p E<gt> overall_stats.tsv>
=head1 DESCRIPTION
Categorize rows of a delimited TEXT inpu... |
cb016ad93b5b9012575ec5dba8ccde91d304e00b12019cc6342bef9f0f9365a6 | Perl | 52,699 | 963 | #!/usr/bin/perl
#######
# POD #
#######
=pod
=head1 NAME
C<po2group_stats.pl> - categorize orthologs from Proteinortho5
output according to genome groups
=head1 SYNOPSIS
C<perl po2group_stats.pl -i matrix.proteinortho -d genome_fasta_dir/
-g group_file.tsv -p E<gt> overall_stats.tsv>
=head1 DESCRIPTION
Categori... |
f3ddb2199c1ef3eff59bcce7c118b9f5072ba4f1ed28072891671ec57e3baa0f | Perl | 80,012 | 2,359 | #!/opt/anaconda1anaconda2anaconda3/bin/perl
eval 'exec /opt/anaconda1anaconda2anaconda3/bin/perl -S $0 ${1+"$@"}'
if 0; # not running under some shell
=pod
=head1 NAME
bp_genbank2gff3.pl -- Genbank-E<gt>gbrowse-friendly GFF3
=head1 SYNOPSIS
bp_genbank2gff3.pl [options] filename(s)
# process a direct... |
232054f5eefc2442e072cdc7cb10befc4e4ce6682404ced00207f149cd9b7172 | Perl | 147,479 | 3,240 | #!/usr/bin/env perl
#
# Copyright (C) 2013-2020 Genome Research Ltd.
#
# Author: Petr Danecek <pd3@sanger.ac.uk>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, i... |
5ce9cd9830dc012a2a96d849c8d68a4a8c390387b69d94a1b0dd2a6b9c8b0123 | Python | 6 | 1 | #init
|
ff41b8fd376c931b1c6c04daea556c6ae6a93471ff8d38b79a2cc6978f7a4441 | Python | 9 | 2 | dt= 0.2
|
45a4cdb301c6eaca449d4094762d784d3bfa365bcf599aa7e228601f603c15fb | Python | 13 | 1 | #coding:utf-8 |
7aa4c6e9a431d3c6957252116e93d191e7550d5053ab6344376d7908c917f2c9 | Python | 14 | 1 | #!/bin/python
|
884d736c535b5fc25e8de5683100a4ccd2c21059bdd024ace8b77f969da8036a | Python | 15 | 1 | RANDOM_SEED = 5 |
20df0c8d7926d2f1572ace008b001ac06e61708215b2867d02130a3cf921418e | Python | 18 | 1 | from .th import *
|
db3b5bf9c517b12537029c71317235a59e436c58ab792b0227e52e161853fb21 | Python | 18 | 1 | from hcbr import * |
0169a96ef4866d48fbb0b1ec28fd131e1f8724fa31bc7eeaa7f11135c561fe81 | Python | 19 | 1 | __version__ = '1.0' |
30625bf9724a6341c61128a4068d6bfa996c4b8d95eaa87050a57e03acf46c48 | Python | 20 | 1 | from models import * |
3381254070a8f96c6d5572b7f5b177422153dc81973ed675921a9ec478930447 | Python | 20 | 1 | """Example code."""
|
58482ab0e84301bb1e1d42d9480d60efbbe07d4bd0880767f29f67917e82e9a4 | Python | 20 | 1 | from config import * |
f9c1cee683873ee042965e0da1ed5f2158db30884afddd6068925c3e56d296de | Python | 20 | 1 | __version__ = '0.2'
|
9bdca6f8225a245de69c63643aa36f02a60d90bb8ac5f1248c29066de15e22c4 | Python | 21 | 1 | __version__ = '2.2.0' |
c961103064572723ea10c30be1aedf29914fc09ae804998eb69e377970d602f9 | Python | 21 | 1 | from .carla import *
|
034d25a6750a83eab7cbf6fe70dde3285f6eae41931a36f6633fe019cf5608bb | Python | 22 | 1 | from .config import *
|
68111b0efc782cc83c0354c9251e9d107bbcad03835629f9dbc84b4bf103bee0 | Python | 22 | 1 | __version__ = '0.1.4'
|
717a269e37ebcfc8e4cb6b3e0c5b1e9d65fc31cbc07038d5ea36ab7d2f66af16 | Python | 22 | 1 | __author__ = 'duarte'
|
84c159b9388b9c89f0c4c6cfbdee2e438f4121ac0bb306b2a74f1c80eae0f973 | Python | 22 | 1 | from .models import *
|
8a2f401af5971bfe2a1cdd05119b38e6eac9e54acf43d23cdd88d752314cbed2 | Python | 22 | 1 | __version__ = "1.1.8"
|
b4b1ef271c9552b935434134b268f56063b5e6b1dedb1646abde6ff8e45a877b | Python | 22 | 1 | from .sphere import *
|
b67256c0ccd5285120227e6599b56c8db4dffb4f2d13d4480473f17dde215768 | Python | 22 | 1 | from .masker import *
|
e34f8f5193d121a909536c985907304d8bd2240ea27b0aa21bc5f2961c6e0109 | Python | 22 | 1 | __version__ = "0.4.8"
|
e65522ae78341b3872d2b537c201d94e8f66fb716bde7796758adfe2b75aa705 | Python | 23 | 1 | from .agco import agco
|
34351d66f69f7505631e7a32941a073f0f18b9c2b89298b0fe23e87b8aaa1da1 | Python | 24 | 1 | import scripts.ACEtools
|
634b9d8738ee09680e459b968b40c69fe5ca3166f741952b368e1e2ec36ce9a7 | Python | 24 | 1 | from .image_gui import * |
6766c0a7938636ec145b479f11fa779ab7a42a6d87cdb618542b6b0df1437cd4 | Python | 24 | 1 | from util.util import *
|
93d4f05b79c383940db8f854111b92306662b9c900f04dff58bf55bdc5476d40 | Python | 24 | 1 | from src.model import *
|
cf5a46e4864e3824d38d73a297cb21b610eebaf2faaacaa0717ab0b15e036042 | Python | 24 | 1 | from .seg_oprs import *
|
e097908b83de6ef0f00474b1e85c663e90035dda8f7a2d571418e809187c13c4 | Python | 25 | 1 | from . import Dataset_2a
|
78c5e68cdaf3079de12a9e4bf4d864edae53c817be58051b2d4fb5cc14216fce | Python | 26 | 1 | from . import new_visuals
|
b2ca11b1917333c70fe698cead3d303ecc22788b2ac4a51306ca9c2752feef19 | Python | 26 | 1 | from .core import LogEntry |
c3ab8237be62ae30a6474f46b6ea7ff20ba6e51d9230e1e0220a1fb7bd7ef413 | Python | 27 | 2 |
from .eeg import plot_eeg
|
d776124b5197cf2452a27d6283eab8387bebf25176b25cdd5d72c0562500ffbc | Python | 28 | 1 | from .base_trainer import *
|
6fb744c123c828634c01676deefd65123175108d345653708e16409dc1242a45 | Python | 31 | 1 | from .core import FlyV1Dataset
|
3cc722f4bda0d4782ba996997913aa777cb4baca2145220568e7e6a20750a038 | Python | 32 | 1 | from .crossfolds import generate |
8b160c88b885c21e1fe93f7b26c0eb9bd9b9bd213fd0502f8a0543371c670db5 | Python | 32 | 1 | from .predictor import Predictor |
ec64bfeed10d8d4aeec28ce8140a48db0db8120442b984a8ee68c2ad79493a8a | Python | 32 | 1 | from .core import MouseV1Dataset |
06ce0e48cc58baa51d7f09c536609af0b1cca1d23c26f8f83812136609f1ab03 | Python | 33 | 1 | from .predictor import Predictor
|
285a97ec67849a0f822247cc11e60ef9c8c1bd245cfabebd9138d5aa3a7a9288 | Python | 33 | 1 | from .sampling import sample_rdpg |
69dc96e324a39c30975eec8f8ab462ca34a2631c6310a33d7218f09910da5f7f | Python | 33 | 1 | """Unittests for the package."""
|
e48c8a3cc1b5aa3b8dfeac5f71cab8f76cccdfcffefd8a8420d7fd92d09afed1 | Python | 33 | 1 | from envs.fdtd_env import FdtdEnv |
2b15aeab35815486e0d5d06aa2492b3d1fca2fec1253c723894d2c21effe7ee2 | Python | 35 | 1 | hiddenimports = ['torchvision._C']
|
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