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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35144?</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37396/converting-a-vcf-into-a-fasta-given-some-reference</guid>
	<pubDate>Fri, 20 Jul 2018 10:03:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37396/converting-a-vcf-into-a-fasta-given-some-reference</link>
	<title><![CDATA[Converting a VCF into a FASTA given some reference !]]></title>
	<description><![CDATA[<p>Samtools/BCFtools (Heng Li) provides a Perl script&nbsp;<a href="https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl"><code>vcfutils.pl</code></a>&nbsp;which does this, the function&nbsp;<code>vcf2fq</code>&nbsp;(lines 469-528)</p><p>This script has been modified by others to convert InDels as well, e.g.&nbsp;<a href="https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl">this</a>&nbsp;by David Eccles</p><pre><code><span>./</span><span>vcf2fq</span><span>.</span><span>pl </span><span>-</span><span>f </span><span>&lt;</span><span>input</span><span>.</span><span>fasta</span><span>&gt;</span><span> </span><span>&lt;</span><span>all</span><span>-</span><span>site</span><span>.</span><span>vcf</span><span>&gt;</span><span> </span><span>&gt;</span><span> </span><span>&lt;</span><span>output</span><span>.</span><span>fastq</span><span>&gt;</span></code></pre><p>https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl</p><p>https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43957/gfastats-the-swiss-army-knife-for-genome-assembly</guid>
	<pubDate>Thu, 08 Sep 2022 06:03:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43957/gfastats-the-swiss-army-knife-for-genome-assembly</link>
	<title><![CDATA[gfastats: The swiss army knife for genome assembly.]]></title>
	<description><![CDATA[<p><span>gfastats</span><span>&nbsp;is a single fast and exhaustive tool for&nbsp;</span><span>summary statistics</span><span>&nbsp;and simultaneous *fa* (fasta, fastq, gfa [.gz]) genome assembly file&nbsp;</span><span>manipulation</span><span>.&nbsp;</span><span>gfastats</span><span>&nbsp;also allows seamless fasta&lt;&gt;fastq&lt;&gt;gfa[.gz] conversion. It has been tested in genomes even &gt;100Gbp.</span></p><p>Address of the bookmark: <a href="https://github.com/vgl-hub/gfastats" rel="nofollow">https://github.com/vgl-hub/gfastats</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37493/fastq-stats-in-emoji</guid>
	<pubDate>Mon, 06 Aug 2018 10:20:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37493/fastq-stats-in-emoji</link>
	<title><![CDATA[Fastq stats in Emoji :)]]></title>
	<description><![CDATA[<p>Read one or more FASTQ files,&nbsp;<a href="https://fastqe.com/">fastqe</a>&nbsp;will compute quality stats for each file and print those stats as emoji... for some reason.</p>
<p>Given a fastq file in Illumina 1.8+/Sanger format, calculate the mean (rounded) score for each position and print a corresponding emoji!</p>
<p><a href="https://github.com/lonsbio/fastqe/blob/master/docs/img/fastqe_binned.png" target="_blank"><img src="https://github.com/lonsbio/fastqe/raw/master/docs/img/fastqe_binned.png" alt="Example" style="border: 0px;"></a></p>
<p><a href="https://fastqe.com/">https://fastqe.com/</a></p><p>Address of the bookmark: <a href="https://github.com/lonsbio/fastqe" rel="nofollow">https://github.com/lonsbio/fastqe</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</guid>
	<pubDate>Sat, 27 Feb 2021 01:42:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42921/run-bash-script-in-perl-program</link>
	<title><![CDATA[Run bash script in Perl program !]]></title>
	<description><![CDATA[<p>BioPerl is a compilation of Perl modules that can be used to build bioinformatics-related Perl scripts. It is used, for example, in the development of source codes, standalone software/tools, and algorithms in bioinformatics programmes. Different modules are easy to instal and include, making it easier to perform different functions. Despite the fact that Python is commonly favoured over Perl, some bioinformatics software, such as the standalone version of 'alienomics', is written in Perl. Often it's a major problem for beginners to execute certain Unix/shell commands in Perl script, so it's hard to determine which feature is unique to a situation.</p><div style="background-color: white;">Perl provides various features and operators for the execution of external commands (described as follows), which are unique in their own way.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;">They vary slightly from one another, making it difficult for Perl beginners to choose between them.</div><div style="background-color: white;">&nbsp;</div><div style="background-color: white;"><strong>1. IPC::Open2</strong></div><p>More at https://bioinformaticsonline.com/snippets/view/42919/perl-ipcopen2-module</p><p><strong>2. exec&rdquo;&rdquo;</strong></p><p><em>&nbsp;syntax:&nbsp;</em><code>exec "command";</code></p><div style="background-color: #edfbff;">It's a Perl function (perlfunc) that executes a command but never returns, similar to a function's return statement.</div><div style="background-color: white;">While running the command, it keeps processing the script and does not wait until it finishes first, returns false when the command is not found, but never returns true.</div><p><strong>3. Backticks &ldquo; or qx//</strong></p><p><em>syntax:&nbsp;</em><code>`command`;</code></p><p><em>syntax:&nbsp;</em><code>qx/command/;</code></p><div style="background-color: white;">It's a Perl operator (perlop) that executes a command and then resumes the Perl script once the command has ended, but the return value is the command's STDOUT.</div><p><strong>4. IPC::Open3</strong></p><p><em>syntax:&nbsp;</em><code>$output =&nbsp;open3(\*CHLD_IN, \*CHLD_OUT, \*CHLD_ERR,&nbsp;'command arg1 arg2', 'optarg',...);</code></p><p style="text-align: justify;"><code></code>It is very similar to <code>IPC::Open2</code> with the capability to capture all three file handles of the process, i.e., STDIN, STDOUT, and STDERR. It can also be used with or without the shell. You can read about it more in the documentation: <a href="https://perldoc.perl.org/IPC/Open3.html" target="_blank">IPC::Open3</a>.</p><p><code>$output = open3(my $o ut,&nbsp;my $in, 'command arg1 arg2');</code></p><p>OR without using the shell</p><p><code>$output = open3(my $out,&nbsp;my $in, 'command', 'arg1', 'arg2');</code></p><p><strong>5.a2p</strong></p><p><em>syntax:&nbsp;</em><code>a2p [options] [awkscript]</code></p><p>There is a Perl utility known as <code>a2p</code> which translates <code>awk</code> command to Perl. It takes awk script as input and generates a comparable Perl script as the output. Suppose, you want to execute the following <code>awk</code> statement</p><p><code>awk '{$1 = ""; $2 = ""; print}' f1.txt</code></p><p>This statement gives error sometimes even after escaping the variables (\$1, \$2) but by using <code>a2p</code> it can be easily converted to Perl script:</p><p>For further information, you can read it&rsquo;s documentation: <code><a href="https://perldoc.perl.org/a2p.html" target="_blank">a2p</a></code></p><p>More help at https://bioinformaticsonline.com/snippets/view/42920/perl-script-to-run-awk-inside-perl</p><p><strong>6. system()</strong></p><p><em>syntax:&nbsp;</em><code>system( "command" );</code></p><p>It is also a Perl function (<a href="https://perldoc.perl.org/functions/system.html" target="_blank">perlfunc</a>) that executes a command and waits for it to get finished first and then resume the Perl script. The return value is the exit status of the command. It can be called in two ways:</p><p><code>system( "command arg1 arg2" );</code></p><p>OR</p><p><code>system( "command", "arg1", "arg2" );</code></p><p>HELP</p><p>Here are some useful Perl cheat sheets that can be used as a quick reference guide.--&nbsp;<a href="https://www.pcwdld.com/perl-cheat-sheet" target="_blank">https://www.pcwdld.com/perl-cheat-sheet</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34600/converting-blast-output-into-csv</guid>
	<pubDate>Mon, 11 Dec 2017 04:17:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34600/converting-blast-output-into-csv</link>
	<title><![CDATA[Converting BLAST output into CSV]]></title>
	<description><![CDATA[<p>Suppose we wanted to do something with all this BLAST output. Generally, that&rsquo;s the case - you want to retrieve all matches, or do a reciprocal BLAST, or something.</p><p>As with most programs that run on UNIX, the text output is in some specific format. If the program is popular enough, there will be one or more parsers written for that format &ndash; these are just utilities written to help you retrieve whatever information you are interested in from the output.</p><p>Let&rsquo;s conclude this tutorial by converting the BLAST output in out.txt into a spreadsheet format, using a Python script.&nbsp;</p><p>First, we need to get the script. We&rsquo;ll do that using the &lsquo;git&rsquo; program:</p><div><div><pre>git clone <a href="https://github.com/ngs-docs/ngs-scripts.git">https://github.com/ngs-docs/ngs-scripts.git</a> /root/ngs-scripts
</pre></div></div><p>We&rsquo;ll discuss &lsquo;git&rsquo; more later; for now, just think of it as a way to get ahold of a particular set of files. In this case, we&rsquo;ve placed the files in /root/ngs-scripts/, and you&rsquo;re looking to run the script blast/blast-to-csv.py using Python:</p><div><div><pre>python /root/ngs-scripts/blast/blast-to-csv.py out.txt
</pre></div></div><p>This outputs a spread-sheet like list of names and e-values. To save this to a file, do:</p><div><div><pre>python /root/ngs-scripts/blast/blast-to-csv.py out.txt &gt; ~out.csv
</pre></div></div><p>If you have Excel installed, try double clicking on it.</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43663/vcf2maf-convert</guid>
	<pubDate>Fri, 17 Dec 2021 03:20:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43663/vcf2maf-convert</link>
	<title><![CDATA[vcf2maf convert !]]></title>
	<description><![CDATA[<p>To convert a <a href="http://samtools.github.io/hts-specs/">VCF</a> into a <a href="https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format">MAF</a>, each variant must be mapped to only one of all possible gene transcripts/isoforms that it might affect. But even within a single isoform, a <code>Missense_Mutation</code> close enough to a <code>Splice_Site</code>, can be labeled as either in MAF format, but not as both. <strong>This selection of a single effect per variant, is often subjective. And that's what this project attempts to standardize.</strong> The <code>vcf2maf</code> and <code>maf2maf</code> scripts leave most of that responsibility to <a href="http://useast.ensembl.org/info/docs/tools/vep/index.html">Ensembl's VEP</a>, but allows you to override their "canonical" isoforms, or use a custom ExAC VCF for annotation. Though the most useful feature is the <strong>extensive support in parsing a wide range of crappy MAF-like or VCF-like formats</strong> we've seen out in the wild.</p><p>Address of the bookmark: <a href="https://github.com/mskcc/vcf2maf" rel="nofollow">https://github.com/mskcc/vcf2maf</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2727/download-mutliple-fasta-file-from-ncbi-in-one-go</guid>
	<pubDate>Wed, 21 Aug 2013 08:13:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2727/download-mutliple-fasta-file-from-ncbi-in-one-go</link>
	<title><![CDATA[Download mutliple fasta file from NCBI in one GO!!]]></title>
	<description><![CDATA[<p>if you have less time, then use three ways mentioned in bookmark link to extract/download all fasta sequences in single click given that you already have a list of GIs or accession IDs .</p>
<p>Alternatively, use one liner perl script:</p>
<p>perl -ne 'if(/^&gt;(\S+)/){$c=$i{$1}}$c?print:chomp;$i{$_}=1 if @ARGV' GIs.txt &gt;sequence.fasta</p>
<p>where GIs.txt contains&nbsp;a list of GIs or accession IDs.</p>
<p>(from :<a href="http://edwards.sdsu.edu/labsite/index.php/robert?start=5">http://edwards.sdsu.edu/labsite/index.php/robert?start=5</a>)</p><p>Address of the bookmark: <a href="http://edwards.sdsu.edu/labsite/index.php/robert/380-ncbi-sequence-or-fasta-batch-download-using-entrez" rel="nofollow">http://edwards.sdsu.edu/labsite/index.php/robert/380-ncbi-sequence-or-fasta-batch-download-using-entrez</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26968/scalce</guid>
	<pubDate>Fri, 15 Apr 2016 05:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26968/scalce</link>
	<title><![CDATA[SCALCE]]></title>
	<description><![CDATA[<p><span>SCALCE (</span><code>/skeɪlz/</code><span>, a.k.a. boosting&nbsp;</span><span style="text-decoration: underline;">S</span><span>equence&nbsp;</span><span style="text-decoration: underline;">C</span><span>ompression&nbsp;</span><span style="text-decoration: underline;">A</span><span>lgorithms using&nbsp;</span><span style="text-decoration: underline;">L</span><span>ocally&nbsp;</span><span style="text-decoration: underline;">C</span><span>onsistent</span><span style="text-decoration: underline;">E</span><span>ncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths.&nbsp;</span></p>
<p><span>More at&nbsp;http://sfu-compbio.github.io/scalce/</span></p><p>Address of the bookmark: <a href="http://sfu-compbio.github.io/scalce/" rel="nofollow">http://sfu-compbio.github.io/scalce/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</guid>
	<pubDate>Tue, 10 May 2016 08:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</link>
	<title><![CDATA[segemehl]]></title>
	<description><![CDATA[<p><span>segemehl is a software to map short sequencer reads to reference genomes. Unlike other methods, segemehl is able to detect not only mismatches but also insertions and deletions. Furthermore, segemehl is not limited to a specific read length and is able to map&nbsp;primer- or polyadenylation contaminated reads correctly.&nbsp; segemehl implements a matching strategy based on enhanced suffix arrays (ESA).&nbsp;</span></p>
<p><span>More at&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/</span></p>
<p><span>Manual&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/segemehl_manual_0_1_7.pdf</span></p><p>Address of the bookmark: <a href="http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html" rel="nofollow">http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</guid>
	<pubDate>Fri, 13 May 2016 04:54:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</link>
	<title><![CDATA[cutadapt]]></title>
	<description><![CDATA[<p>Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.</p>
<p>Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3&rsquo; sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don&rsquo;t want them to be in your reads.</p>
<p>Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.</p>
<p>Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.</p>
<p>If you use cutadapt, please cite <a href="http://dx.doi.org/10.14806/ej.17.1.200">DOI:10.14806/ej.17.1.200</a> .</p><p>Address of the bookmark: <a href="https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart" rel="nofollow">https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
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