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2 changes: 1 addition & 1 deletion configure.ac
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# Process this file with autoconf to produce a configure script.

AC_PREREQ([2.69])
AC_INIT([igor], [1.2.0], [[email protected]], [igor], [https://github.com/qmarcou/IGoR])
AC_INIT([igor], [1.3.0], [[email protected]], [igor], [https://github.com/qmarcou/IGoR])

AM_INIT_AUTOMAKE([foreign -Wall -Werror])

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2 changes: 1 addition & 1 deletion docs/asciidoc/version.adoc
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Latest released version: 1.2.0
Latest released version: 1.3.0
160 changes: 114 additions & 46 deletions docs/index.html
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="generator" content="Asciidoctor 1.5.5">
<title>Quick summary</title>
<meta name="author" content="Quentin Marcou">
<title>IGoR (Inference and Generation Of Repertoires) Documentation</title>
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<body class="article toc2 toc-left">
<div id="header">
<h1>IGoR (<em>Inference and Generation Of Repertoires</em>) Documentation</h1>
<div class="details">
<span id="author" class="author">Quentin Marcou</span><br>
</div>
<div id="toc" class="toc2">
<div id="toctitle">Table of Contents</div>
<ul class="sectlevel1">
<li><a href="#quick-summary">Quick summary</a></li>
<li><a href="#version">Version</a></li>
<li><a href="#dependencies">Dependencies</a></li>
<li><a href="#install">Install</a>
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</div>
</div>
<div id="content">
<h1 id="_igor_inference_and_generation_of_repertoires" class="float">IGoR: Inference and Generation Of Repertoires</h1>
<div class="paragraph">
<p>This repository contains all sources and models useful to infer V(D)J
recombination related processes for TCR or BCR sequencing data using
<strong>IGoR</strong></p>
</div>
<div class="sect1">
<h2 id="quick-summary">Quick summary</h2>
<div id="preamble">
<div class="sectionbody">
<div class="paragraph">
<p>IGoR is a C++ software designed to infer V(D)J recombination related
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</ul>
</div>
<div class="paragraph">
<p>The following paper describes the methodology, performance tests and
<p>The following article describes the methodology, performance tests and
some new biological results obtained with IGoR:</p>
</div>
<div class="paragraph">
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<h2 id="version">Version</h2>
<div class="sectionbody">
<div class="paragraph">
<p>Latest released version: 1.2.0</p>
<p>Latest released version: 1.3.0</p>
</div>
</div>
</div>
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<p>bash</p>
</li>
<li>
<p>autotools suite, asciidoctor, doxygen and the latex suite if building from
<p>autotools suite, asciidoctor, pygments (optional), doxygen and the latex suite if building from
unpackaged sources</p>
</li>
</ul>
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<div class="sect2">
<h3 id="linux">Linux</h3>
<div class="paragraph">
<p>Widely tested on several Debian related distros. Install gcc/g if not
<p>Widely tested on several Debian related distros. Install gcc/g++ if not
already installed (note that another compiler could be used). With the
command line go to IGoR's root directory and simply type `./configure`.
command line go to IGoR&#8217;s root directory and simply type <code>./configure</code>.
This will make various check on your system and create makefiles
compatible with your system configuration. Many options can be appended
to ./configure such as `./configure CC=gcc CXX=g` to enforce the use
of gcc as compiler. Once over, type <code>make</code> to compile the sources (this
to ./configure such as <code>./configure CC=gcc CXX=g\+\+ ` to enforce the use
of gcc as compiler. Once over, type `make</code> to compile the sources (this
will take a few minutes). <strong>IGoR&#8217;s executable will appear in the igor_src
folder</strong></p>
</div>
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</div>
<div class="listingblock">
<div class="content">
<pre>sudo port selfupdate #Update macports database
sudo port install gcc6 #install gcc version 6</pre>
<pre class="pygments highlight"><code data-lang="shell">sudo port selfupdate <span class="tok-c1">#Update macports database</span>
sudo port install gcc6 <span class="tok-c1">#install gcc version 6</span></code></pre>
</div>
</div>
<div class="paragraph">
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</div>
<div class="listingblock">
<div class="content">
<pre>port select --list gcc #Will list the versions of gcc available on your system
sudo port select --set gcc mp-gcc6 #set the one you wish to have as default call upon using the gcc command</pre>
<pre class="pygments highlight"><code data-lang="shell">port <span class="tok-k">select</span> --list gcc <span class="tok-c1">#Will list the versions of gcc available on your system</span>
sudo port <span class="tok-k">select</span> --set gcc mp-gcc6 <span class="tok-c1">#set the one you wish to have as default call upon using the gcc command</span></code></pre>
</div>
</div>
<div class="paragraph">
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</div>
<div class="listingblock">
<div class="content">
<pre>brew install gcc</pre>
<pre class="pygments highlight"><code data-lang="shell">brew install gcc</code></pre>
</div>
</div>
<div class="paragraph">
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</tr>
<tr>
<td class="tableblock halign-left valign-top"><p class="tableblock"><code>-set_CDR3_anchors --<strong>gene</strong></code></p></td>
<td class="tableblock halign-left valign-top"><p class="tableblock">Load a CSV file containing the indices/offset of
<td class="tableblock halign-left valign-top"><p class="tableblock">Load a semicolon separated file containing the indices/offset of
the CDR3 anchors for the <em>gene</em>(--V or --J). The index should correspond
to the first letter of the cysteine (for V) or tryptophan/phenylalanin
(for J) for the nucleotide sequence of the gene. Indices are 0 based.</p></td>
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</div>
<div class="paragraph">
<p>Python utility functions are provided to analyze these outputs in the
pygor.counters submodule.</p>
<code>pygor.counters</code> submodule.</p>
</div>
<div class="sect3">
<h4 id="best-scenarios">Best scenarios</h4>
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</div>
<div class="listingblock">
<div class="content">
<pre>igor -run_demo</pre>
<pre class="pygments highlight"><code data-lang="shell">igor -run_demo</code></pre>
</div>
</div>
<div class="paragraph">
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</div>
<div class="listingblock">
<div class="content">
<pre>WDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory
<pre class="pygments highlight"><code data-lang="shell"><span class="tok-nv">WDPATH</span><span class="tok-o">=</span>/path/to/your/working/directory <span class="tok-c1">#Let&#39;s define a shorthand for the working directory</span>

#We first read the sequences contained in a text file inside the demo folder
#This will create the align folder in the working directory and the mydemo_indexed_seqs.csv file.
igor -set_wd $WDPATH -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt
<span class="tok-c1">#We first read the sequences contained in a text file inside the demo folder</span>
<span class="tok-c1">#This will create the align folder in the working directory and the mydemo_indexed_seqs.csv file.</span>
igor -set_wd <span class="tok-nv">$WDPATH</span> -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt

#Now let's align the sequences against the provided human beta chain genomic templates with default parameters
#This will create foo_V_alignments.csv, foo_D_alignments.csv and foo_J_alignments.csv files inside the align folder.
igor -set_wd $WDPATH -batch foo -species human -chain beta -align --all
<span class="tok-c1">#Now let&#39;s align the sequences against the provided human beta chain genomic templates with default parameters</span>
<span class="tok-c1">#This will create foo_V_alignments.csv, foo_D_alignments.csv and foo_J_alignments.csv files inside the align folder.</span>
igor -set_wd <span class="tok-nv">$WDPATH</span> -batch foo -species human -chain beta -align --all

#Now use the provided beta chain model to get the 10 best scenarios per sequence
#This will create the foo_output and foo_evaluate and the corresponding files inside
igor -set_wd $WDPATH -batch foo -species human -chain beta -evaluate -output --scenarios 10
<span class="tok-c1">#Now use the provided beta chain model to get the 10 best scenarios per sequence</span>
<span class="tok-c1">#This will create the foo_output and foo_evaluate and the corresponding files inside</span>
igor -set_wd <span class="tok-nv">$WDPATH</span> -batch foo -species human -chain beta -evaluate -output --scenarios <span class="tok-m">10</span>

#Now generate 100 synthetic sequences from the provided human beta chain model
#This will create the directory bar_generate with the corresponding files containing the generated sequences and their realizations
igor -set_wd $WDPATH -batch bar -species human -chain beta -generate 100</pre>
<span class="tok-c1">#Now generate 100 synthetic sequences from the provided human beta chain model</span>
<span class="tok-c1">#This will create the directory bar_generate with the corresponding files containing the generated sequences and their realizations</span>
igor -set_wd <span class="tok-nv">$WDPATH</span> -batch bar -species human -chain beta -generate <span class="tok-m">100</span></code></pre>
</div>
</div>
<div class="paragraph">
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</div>
<div class="listingblock">
<div class="content">
<pre>WDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory
MYCOMMANDS=./igor -set_wd $WDPATH
<pre class="pygments highlight"><code data-lang="shell"><span class="tok-nv">WDPATH</span><span class="tok-o">=</span>/path/to/your/working/directory <span class="tok-c1">#Let&#39;s define a shorthand for the working directory</span>
<span class="tok-nv">MYCOMMANDS</span><span class="tok-o">=</span>./igor -set_wd <span class="tok-nv">$WDPATH</span>

$MYCOMMANDS -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt #Read seqs
MYCOMMANDS=$MYCOMMANDS -species human -chain beta #Add chain and species commands
$MYCOMMANDS -batch foo -align --all #Align
$MYCOMMANDS -batch foo -evaluate -output --scenarios 10 #Evaluate
$MYCOMMANDS -batch bar -generate 100 #Generate</pre>
<span class="tok-nv">$MYCOMMANDS</span> -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt <span class="tok-c1">#Read seqs</span>
<span class="tok-nv">MYCOMMANDS</span><span class="tok-o">=</span><span class="tok-nv">$MYCOMMANDS</span> -species human -chain beta <span class="tok-c1">#Add chain and species commands</span>
<span class="tok-nv">$MYCOMMANDS</span> -batch foo -align --all <span class="tok-c1">#Align</span>
<span class="tok-nv">$MYCOMMANDS</span> -batch foo -evaluate -output --scenarios <span class="tok-m">10</span> <span class="tok-c1">#Evaluate</span>
<span class="tok-nv">$MYCOMMANDS</span> -batch bar -generate <span class="tok-m">100</span> <span class="tok-c1">#Generate</span></code></pre>
</div>
</div>
</div>
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</div>
<div id="footer">
<div id="footer-text">
Last updated 2018-08-03 20:23:35 EDT
Last updated 2018-08-04 15:26:06 EDT
</div>
</div>
</body>
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2 changes: 1 addition & 1 deletion pygor/setup.py
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requirements = [line.rstrip("\n") for line in f.readlines()]

setup(name="pygor",
version="1.2.0",
version="1.3.0",
description="Module for parsing IGoR output (alignments, models etc).",
url="https://github.com/qmarcou/IGoR",
author="Quentin Marcou",
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