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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38762?offset=80</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/933/world-of-omics</guid>
	<pubDate>Tue, 16 Jul 2013 17:11:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/933/world-of-omics</link>
	<title><![CDATA[World of Omics]]></title>
	<description><![CDATA[<p>How many variants of "omics" techniques presently in use ?</p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4100/should-you-get-sequenced-not-all-bad-genes-predict-disease</guid>
	<pubDate>Thu, 29 Aug 2013 15:10:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4100/should-you-get-sequenced-not-all-bad-genes-predict-disease</link>
	<title><![CDATA[Should you get sequenced? Not all bad genes predict disease]]></title>
	<description><![CDATA[<p><span>&ldquo;What we really don&rsquo;t know yet is whether the predictive aspects of the genome are going to turn out to be beneficial or potentially harmful&rdquo;</span></p>
<p><span><span>&ldquo;As we roll out genomic medicine we are fighting against this society-wide misconception that having the bad gene means you&rsquo;re going to get the disease. That&rsquo;s only true in a very few cases.&rdquo;</span></span></p>
<p><span><span><strong>Source</strong>:Today Health</span></span></p><p>Address of the bookmark: <a href="http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154" rel="nofollow">http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</guid>
	<pubDate>Wed, 21 Aug 2013 07:56:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</link>
	<title><![CDATA[Comparison of Short Read De Novo Alignment Algorithms]]></title>
	<description><![CDATA[<p>Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.</p>
<p>Title:&nbsp;<strong>Comparison of Short Read De Novo Alignment Algorithms&nbsp;</strong></p>
<p>Author<strong>: Nikhil Gopal</strong></p><p>Address of the bookmark: <a href="http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf" rel="nofollow">http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4208/latest-paper-on-comparison-of-mapping-tools</guid>
	<pubDate>Tue, 03 Sep 2013 18:00:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4208/latest-paper-on-comparison-of-mapping-tools</link>
	<title><![CDATA[Latest paper on comparison of mapping tools]]></title>
	<description><![CDATA[<p>A. Hatem, D. Bozdag, A. E. Toland, U. V. Catalyurek "Benchmarking short sequence mapping tools" BMC Bioinformatics, 14(1):184, 2013.</p>
<p>http://bmi.osu.edu/hpc/software/benchmark/</p>
<p><a href="http://bmi.osu.edu/hpc/software/pmap/pmap.html">http://bmi.osu.edu/hpc/software/pmap/pmap.html</a></p>
<p>Other similiar papers:</p>
<p><a href="http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022">http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022</a></p>
<p><a href="http://bioinformatics.oxfordjournals.org/content/28/24/3169">http://bioinformatics.oxfordjournals.org/content/28/24/3169</a></p>
<p>Some new Mapping tool links:<a href="http://bmi.osu.edu/hpc/software/benchmark/"></a></p>
<p><strong>GSNAP</strong></p>
<p><a href="http://research-pub.gene.com/gmap/"></a><a href="http://research-pub.gene.com/gmap/">http://research-pub.gene.com/gmap/</a></p>
<p><strong>RMAP</strong></p>
<p><a href="http://rulai.cshl.edu/rmap/"></a><a href="http://rulai.cshl.edu/rmap/">http://rulai.cshl.edu/rmap/</a></p>
<p><strong>mrsFAST</strong></p>
<p><a href="http://mrsfast.sourceforge.net/Home"></a><a href="http://mrsfast.sourceforge.net/Home">http://mrsfast.sourceforge.net/Home</a></p>
<p><a href="http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/">http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/</a></p>
<p><strong>BFAST</strong></p>
<p><a href="http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page">http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page</a></p>
<p><strong>SHRiMP (for&nbsp;AB SOLiD color-space reads)</strong></p>
<p><a href="http://compbio.cs.toronto.edu/shrimp/">http://compbio.cs.toronto.edu/shrimp/</a></p>
<p><strong>RazerA 3</strong></p>
<p><a href="http://www.seqan.de/projects/razers/">http://www.seqan.de/projects/razers/</a></p><p>Address of the bookmark: <a href="http://www.biomedcentral.com/1471-2105/14/184" rel="nofollow">http://www.biomedcentral.com/1471-2105/14/184</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/9400/largest-genome-sequenced</guid>
	<pubDate>Fri, 21 Mar 2014 13:57:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/9400/largest-genome-sequenced</link>
	<title><![CDATA[Largest Genome Sequenced]]></title>
	<description><![CDATA[<p>The enormous size of the <strong>loblolly pine genome</strong> having <strong>22 billion base pairs</strong> compared to only 3 billion in the human genome. In other words, it is&nbsp;<strong>seven times</strong> larger than a human&rsquo;s and also the largest and the most complete&nbsp;<strong>conifer<a href="http://en.wikipedia.org/wiki/Pinophyta" target="_blank"></a></strong>&nbsp;genome ever sequenced.</p>
<p><strong>Related Paper:</strong></p>
<p>http://genomebiology.com/2014/15/3/R59/abstract</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.news.ucdavis.edu/search/news_detail.lasso?id=10859" rel="nofollow">http://www.news.ucdavis.edu/search/news_detail.lasso?id=10859</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10243/new-rna-seq-tool</guid>
	<pubDate>Fri, 25 Apr 2014 10:59:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10243/new-rna-seq-tool</link>
	<title><![CDATA[New RNA Seq tool]]></title>
	<description><![CDATA[<p>"<span>By removing the time-consuming step of read mapping, the authors reported, Sailfish able to provide quantification estimates 20&ndash;30 times faster than current methods without loss of accuracy."</span></p>
<p><span>Tool link:</span></p>
<p><span>http://www.cs.cmu.edu/~ckingsf/software/sailfish/</span></p>
<p><span></span></p><p>Address of the bookmark: <a href="http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/" rel="nofollow">http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</guid>
	<pubDate>Thu, 22 May 2014 07:18:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/10966/genxpro-gmbh</link>
	<title><![CDATA[GenXPro GmbH]]></title>
	<description><![CDATA[<p><strong>GenXPro</strong>&nbsp;GMbH is service provider for entire spectrum of nucleotide-based information&nbsp;of any biological sample. By combining intelligent data reduction techniques and&nbsp;latest next generation sequencing technologies, our service portfolio provides most accurate and cost efficient solutions for&nbsp;transcriptomic-, genomic- or epigenomic research.</p><p><span><span><strong><span>GENXPRO GMBH</span>,&nbsp;</strong></span></span><span>ALTENH&Ouml;FERALLEE 3,&nbsp;</span><span>60438 FRANKFURT MAIN,&nbsp;</span><span>GERMANY</span></p><p><span><span><strong>Website</strong></span>:&nbsp;<a href="http://www.genxpro.info/products_and_services/"></a><a href="http://www.genxpro.info/products_and_services/">http://www.genxpro.info/products_and_services/</a></span></p><p><span><strong>PHONE</strong>: +49 (0)69- 95 73 97 10,&nbsp;FAX: +49 (0)69- 95 73 97 06</span></p><p><span>EMAIL: info@genxpro.de</span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</guid>
	<pubDate>Tue, 29 Jul 2014 09:11:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</link>
	<title><![CDATA[The Genome 10K Project]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/B57xDIGtCT0" frameborder="0" allowfullscreen></iframe>https://genome10k.soe.ucsc.edu

The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts.

The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.]]></description>
	
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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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