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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/1956?offset=0</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/1906</guid>
	<pubDate>Sun, 11 Aug 2013 11:13:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/1906</link>
	<title><![CDATA[Compressive Genomics]]></title>
	<description><![CDATA[<p>The key to finding a solution is to notice that most&nbsp;<a href="http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html">genomic</a>sequences differ by very little. It may well be that the number of complete genome sequences being stored is increasing rapidly, but the actual amount of new data is very small. In other words, a single DNA sequence isn't particularly compressible but a set of sequences shares so much in common that the redundancy can be used to store them in a much smaller storage space. (Source:e-article from&nbsp;Alex Armstrong)</p><p><a href="http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html">http://www.i-programmer.info/news/181-algorithms/4537-a-new-dna-sequence-search-compressive-genomics.html</a></p><p><a href="http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data">http://en.wikipedia.org/wiki/Compression_of_Genomic_Re-Sequencing_Data</a></p><p><a href="http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html">http://www.nature.com/nbt/journal/v30/n7/full/nbt.2241.html</a></p><p><a href="http://bioinformatics.oxfordjournals.org/content/29/13/i283.full">http://bioinformatics.oxfordjournals.org/content/29/13/i283.full</a></p><p><a href="http://groups.csail.mit.edu/cb/cast/">http://groups.csail.mit.edu/cb/cast/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</guid>
	<pubDate>Tue, 16 Jul 2013 14:30:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/926/list-of-popular-bioinformatics-softwaretools</link>
	<title><![CDATA[List of popular bioinformatics software/tools]]></title>
	<description><![CDATA[<p><a href="http://samtools.sourceforge.net/swlist.shtml">I</a>n current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.</p><p>Address of the bookmark: <a href="http://samtools.sourceforge.net/swlist.shtml" rel="nofollow">http://samtools.sourceforge.net/swlist.shtml</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40251/mosdepth-fast-bamcram-depth-calculation-for-wgs-exome-or-targeted-sequencing</guid>
	<pubDate>Wed, 13 Nov 2019 22:20:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40251/mosdepth-fast-bamcram-depth-calculation-for-wgs-exome-or-targeted-sequencing</link>
	<title><![CDATA[mosdepth: fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing]]></title>
	<description><![CDATA[<p>mosdepth can output:</p>
<p>per-base depth about 2x as fast samtools depth--about 25 minutes of CPU time for a 30X genome.<br>mean per-window depth given a window size--as would be used for CNV calling.<br>the mean per-region given a BED file of regions.<br>a distribution of proportion of bases covered at or above a given threshold for each chromosome and genome-wide.<br>quantized output that merges adjacent bases as long as they fall in the same coverage bins e.g. (10-20)<br>threshold output to indicate how many bases in each region are covered at the given thresholds.<br>A summary of mean depths per chromosome and within specified regions per chromosome.</p><p>Address of the bookmark: <a href="https://github.com/brentp/mosdepth" rel="nofollow">https://github.com/brentp/mosdepth</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</guid>
	<pubDate>Thu, 31 May 2018 09:35:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36833/bfc-a-standalone-high-performance-tool-for-correcting-sequencing-errors-from-illumina-sequencing-data</link>
	<title><![CDATA[BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data]]></title>
	<description><![CDATA[BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes.

The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC.

https://github.com/lh3/bfc<p>Address of the bookmark: <a href="https://github.com/lh3/bfc" rel="nofollow">https://github.com/lh3/bfc</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35351/sam-to-bam-conversion</guid>
	<pubDate>Fri, 26 Jan 2018 02:36:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35351/sam-to-bam-conversion</link>
	<title><![CDATA[sam to bam conversion !!]]></title>
	<description><![CDATA[<p>To do sam to bam conversion, follow the following commands :-&nbsp;</p><div><div>Code:</div><pre dir="ltr">$ samtools view -b -S file.sam &gt; file.bam</pre></div><p>Then you will need to use&nbsp;<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools sort file.bam file-sorted</pre></div><p>followed by<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools index  file-sorted.bam</pre></div><p>in order to get an indexed file.<br /><br />If you just type&nbsp;<br /><br /></p><div><div>Code:</div><pre dir="ltr">$ samtools</pre></div><p>or samtools followed by the name of one of the samtools commands, you will get a few lines of help giving the correct syntax for that command,</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</guid>
	<pubDate>Thu, 07 Jul 2016 12:05:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</link>
	<title><![CDATA[Fancy Oneliner for Bioinformatics !!]]></title>
	<description><![CDATA[<p><span>This webpage lists some of the one-liners that we frequently use in metagenomic analyses. You can click on the following links to browse through different topics. You can copy/paste the commands as they are in your terminal screen, provided you follow the same naming conventions and folder structures as we have. We are sharing these codes with the intention that if they are useful and help you in your analyses, then we will be appropriately credited as considerable effort has been put into devising them.</span></p><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</guid>
	<pubDate>Fri, 24 Feb 2017 04:50:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</link>
	<title><![CDATA[bedtools]]></title>
	<description><![CDATA[<p>Collectively, the&nbsp;<strong>bedtools</strong>&nbsp;utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable&nbsp;<em>genome arithmetic</em>: that is, set theory on the genome. For example,&nbsp;<strong>bedtools</strong>&nbsp;allows one to<em>intersect</em>,&nbsp;<em>merge</em>,&nbsp;<em>count</em>,&nbsp;<em>complement</em>, and&nbsp;<em>shuffle</em>&nbsp;genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g.,&nbsp;<em>intersect</em>&nbsp;two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.</p>
<p><strong>bedtools</strong>&nbsp;is developed in the&nbsp;<a href="http://quinlanlab.org/">Quinlan laboratory</a>&nbsp;at the&nbsp;<a href="http://www.utah.edu/">University of Utah</a>&nbsp;and benefits from fantastic contributions made by scientists worldwide.</p><p>Address of the bookmark: <a href="http://bedtools.readthedocs.io/en/latest/index.html" rel="nofollow">http://bedtools.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43870/quip-aggressive-compression-of-fastq-sam-and-bam-files</guid>
	<pubDate>Tue, 24 May 2022 06:31:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43870/quip-aggressive-compression-of-fastq-sam-and-bam-files</link>
	<title><![CDATA[Quip: Aggressive compression of FASTQ, SAM and BAM files.]]></title>
	<description><![CDATA[<p>This will help us to reduce the amount of drive space we take up and decrease data transfer times</p>
<p dir="auto">Quip compresses next-generation sequencing data with extreme prejudice. It supports input and output in the&nbsp;<a href="http://en.wikipedia.org/wiki/Fastq">FASTQ</a>&nbsp;and&nbsp;<a href="http://samtools.sourceforge.net/">SAM/BAM</a>&nbsp;formats, compressing large datasets to as little as 15% of their original size.</p><p>Address of the bookmark: <a href="https://github.com/dcjones/quip" rel="nofollow">https://github.com/dcjones/quip</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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