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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37643?offset=240</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</guid>
	<pubDate>Thu, 09 Mar 2023 02:48:02 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44229/common-steps-for-reads-mapping</link>
	<title><![CDATA[Common steps for reads mapping !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis. Here are some general steps to follow for mapping reads to a genome:</p><ol>
<li>
<p>Choose a read mapper: There are many read mappers available, such as BWA, Bowtie, and HISAT2. Choose a mapper that is appropriate for your type of data and research question.</p>
</li>
<li>
<p>Index the reference genome: Before mapping reads, the reference genome needs to be indexed. This involves creating an index of the genome sequence that allows the mapper to quickly find matches to the reads. Most mappers have their own indexing tools.</p>
</li>
<li>
<p>Prepare the read data: The reads should be in a format that is compatible with the mapper. Most mappers accept FASTQ or BAM files. Depending on the quality of the data, it may need to be filtered or trimmed before mapping.</p>
</li>
<li>
<p>Run the mapper: The mapper is run with the command-line interface or using a graphical user interface. The specific command depends on the mapper being used, but typically involves specifying the input data, reference genome, and output file format.</p>
</li>
<li>
<p>Evaluate the mapping results: After the mapping is complete, the results should be evaluated. This includes assessing the quality of the mapping, such as the mapping rate, the number of mapped reads, and the mapping quality score.</p>
</li>
<li>
<p>Post-processing: Depending on the analysis being performed, post-processing of the mapped reads may be necessary. This can include filtering reads based on quality, removing duplicate reads, and calling variants.</p>
</li>
</ol><p>Overall, mapping reads to a reference genome is a complex process that requires careful consideration of the type of data, the research question, and the specific mapper being used.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</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>
<item>
	<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>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23167/graphmap-a-highly-sensitive-and-accurate-mapper-for-long-error-prone-reads</guid>
	<pubDate>Mon, 06 Jul 2015 08:46:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23167/graphmap-a-highly-sensitive-and-accurate-mapper-for-long-error-prone-reads</link>
	<title><![CDATA[GraphMap - A highly sensitive and accurate mapper for long, error-prone reads]]></title>
	<description><![CDATA[<p>GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.<br>It is&nbsp;<strong>designed to handle Oxford Nanopore MinION 1d and 2d reads</strong>&nbsp;with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.</p>
<p>GraphMap was also designed for ease-of-use: the&nbsp;<strong>default parameters</strong>&nbsp;can handle a wide range of read lengths and error profiles, including:&nbsp;<em>Illumina</em>,&nbsp;<em>PacBio</em>&nbsp;and&nbsp;<em>Oxford Nanopore</em>.<br>This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.</p>
<p><a href="http://biorxiv.org/content/early/2015/06/10/020719">http://biorxiv.org/content/early/2015/06/10/020719</a></p><p>Address of the bookmark: <a href="https://github.com/isovic/graphmap" rel="nofollow">https://github.com/isovic/graphmap</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

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