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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34748?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37512/purecn-copy-number-calling-and-snv-classification-using-targeted-short-read-sequencing</guid>
	<pubDate>Thu, 09 Aug 2018 04:09:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37512/purecn-copy-number-calling-and-snv-classification-using-targeted-short-read-sequencing</link>
	<title><![CDATA[PureCN: copy number calling and SNV classification using targeted short read sequencing]]></title>
	<description><![CDATA[<p>This package estimates tumor purity, copy number, and loss of heterozygosity (LOH), and classifies single nucleotide variants (SNVs) by somatic status and clonality. PureCN is designed for targeted short read sequencing data, integrates well with standard somatic variant detection and copy number pipelines, and has support for tumor samples without matching normal samples.</p>
<p>Author: Markus Riester [aut, cre], Angad P. Singh [aut]</p>
<p>Maintainer: Markus Riester &lt;markus.riester at novartis.com&gt;</p>
<div id="bioc_citation_outer">
<p>Citation (from within R, enter&nbsp;<code>citation("PureCN")</code>):</p>
<div id="bioc_citation">
<p>Riester M, Singh A, Brannon A, Yu K, Campbell C, Chiang D, Morrissey M (2016). &ldquo;PureCN: Copy number calling and SNV classification using targeted short read sequencing.&rdquo;&nbsp;<em>Source Code for Biology and Medicine</em>,&nbsp;<strong>11</strong>, 13. doi:&nbsp;<a href="http://doi.org/10.1186/s13029-016-0060-z">10.1186/s13029-016-0060-z</a>.</p>
</div>
</div><p>Address of the bookmark: <a href="http://bioconductor.org/packages/release/bioc/html/PureCN.html" rel="nofollow">http://bioconductor.org/packages/release/bioc/html/PureCN.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41222/best-practices-for-variant-calling-with-the-gatk</guid>
	<pubDate>Sat, 22 Feb 2020 03:07:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41222/best-practices-for-variant-calling-with-the-gatk</link>
	<title><![CDATA[Best Practices for Variant Calling with the GATK]]></title>
	<description><![CDATA[<p>The presentations below were filmed during the March 2015 GATK Workshop, part of the BroadE Workshop series. At the time of this workshop, the current version of Broad&rsquo;s Genome Analysis Toolkit (GATK) was version 3.3.</p>
<div>
<div>
<div>
<div>
<div>
<div>
<div>
<div>
<div>
<ul>
<li><a href="https://software.broadinstitute.org/gatk/">Genome Analysis Toolkit</a></li>
</ul>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<table>
<tbody style="vertical-align: top;">
<tr>
<td>03/19/15</td>
<td>Introduction to High-Throughput Sequencing data formats and methods</td>
<td>Joel Thibault</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeY3g1M1ZjVjFrZ2s/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6696">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Introduction to the GATK</td>
<td>Geraldine Van der Auwera</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeVEJ1Z1pXUF9Ib3M/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6707">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Mapping, processing, and duplicate marking with Picard tools</td>
<td>Matt Sooknah</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeaGVrbE1GVV9SQkE/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6706">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Mapping and processing RNAseq</td>
<td>Ami Levy-Moonshine</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeLUkwUm5vTGl4bG8/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6705">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Indel realignment</td>
<td>Mark Fleharty</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeLTFzNndsNDBuVms/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6704">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Base quality score recalibration</td>
<td>David Roazen</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeZk1rMXpTYmZzTXc/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6703">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Introduction to variant discovery: calling cohorts</td>
<td>Louis Bergelson</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeQUFYUFRmM1hhRUE/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6702">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Variant calling and joint genotyping</td>
<td>Sheila Chandran</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeYzVTUGs0bjM3M1E/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6701">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Variant quality score recalibration</td>
<td>Bertrand Haas</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeSEpwRkNVQm4wdkE/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6700">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Introduction to working with variants</td>
<td>Yossi Farjoun</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWec0NqUTN2WTRuWWs/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6699">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Genotype refinement</td>
<td>Laura Gauthier</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeMzFldVF5SUp4dWM/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6698">Video</a></td>
</tr>
<tr>
<td>03/19/15</td>
<td>Annotation and variant evaluation</td>
<td>David Benjamin</td>
<td><a href="https://docs.google.com/file/d/0B2dK2q40HDWeWi1YMm42bWdpRE0/preview" target="_blank">PDF</a></td>
<td><a href="https://www.broadinstitute.org/node/6697">Video</a></td>
</tr>
</tbody>
</table><p>Address of the bookmark: <a href="https://www.broadinstitute.org/partnerships/education/broade/best-practices-variant-calling-gatk-1" rel="nofollow">https://www.broadinstitute.org/partnerships/education/broade/best-practices-variant-calling-gatk-1</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
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	<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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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</guid>
	<pubDate>Tue, 28 Jan 2020 03:44:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data</link>
	<title><![CDATA[vt: a variant tool set that discovers short variants from Next Generation Sequencing data.]]></title>
	<description><![CDATA[<p><span>vt is a variant tool set that discovers short variants from Next Generation Sequencing data.</span></p>
<p><span><a href="https://genome.sph.umich.edu/wiki/Vt">https://genome.sph.umich.edu/wiki/Vt</a></span></p>
<p><a href="https://github.com/atks/vt">https://github.com/atks/vt</a></p><p>Address of the bookmark: <a href="https://genome.sph.umich.edu/wiki/Vt" rel="nofollow">https://genome.sph.umich.edu/wiki/Vt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</guid>
	<pubDate>Thu, 28 May 2020 21:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</link>
	<title><![CDATA[Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data]]></title>
	<description><![CDATA[<p>Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.</p>
<p>Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.</p><p>Address of the bookmark: <a href="https://github.com/dnanexus/parliament2" rel="nofollow">https://github.com/dnanexus/parliament2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37536/snippy-rapid-haploid-variant-calling-and-core-snp-phylogeny</guid>
	<pubDate>Sat, 11 Aug 2018 11:06:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37536/snippy-rapid-haploid-variant-calling-and-core-snp-phylogeny</link>
	<title><![CDATA[Snippy: Rapid haploid variant calling and core SNP phylogeny]]></title>
	<description><![CDATA[<p><span>Snippy finds SNPs between a haploid reference genome and your NGS sequence reads. It will find both substitutions (snps) and insertions/deletions (indels). It will use as many CPUs as you can give it on a single computer (tested to 64 cores). It is designed with speed in mind, and produces a consistent set of output files in a single folder. It can then take a set of Snippy results using the same reference and generate a core SNP alignment (and ultimately a phylogenomic tree).</span></p>
<pre><code>snippy --cpus 16 --outdir mysnps --ref Listeria.gbk --R1 FDA_R1.fastq.gz --R2 FDA_R2.fastq.gz</code></pre><p>Address of the bookmark: <a href="https://github.com/tseemann/snippy" rel="nofollow">https://github.com/tseemann/snippy</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44622/variant-calling-resequencing-based-genome-inference</guid>
	<pubDate>Wed, 31 Jul 2024 02:02:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44622/variant-calling-resequencing-based-genome-inference</link>
	<title><![CDATA[Variant Calling Resequencing-Based Genome Inference]]></title>
	<description><![CDATA[<p>Variant Calling - Resequencing-Based Genome Inference</p>
<p>Erik Garrison<br>University of Tennessee Health Science Center<br>Workshop on Genomics - Česk&yacute; Krumlov<br>January 12, 2024</p>
<p>https://evomics.org/wp-content/uploads/2024/01/Variant-calling-Workshop-on-Genomics-2024-Cesky-Krumlov.pdf</p><p>Address of the bookmark: <a href="https://evomics.org/wp-content/uploads/2024/01/Variant-calling-Workshop-on-Genomics-2024-Cesky-Krumlov.pdf" rel="nofollow">https://evomics.org/wp-content/uploads/2024/01/Variant-calling-Workshop-on-Genomics-2024-Cesky-Krumlov.pdf</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</guid>
	<pubDate>Tue, 28 Jan 2020 03:27:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</link>
	<title><![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]></title>
	<description><![CDATA[<p>FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.</p>
<p><a href="http://bioinfo.ut.ee/FastGT/">http://bioinfo.ut.ee/FastGT/</a></p>
<p><strong><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></strong></p><p>Address of the bookmark: <a href="http://bioinfo.ut.ee/FastGT/" rel="nofollow">http://bioinfo.ut.ee/FastGT/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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