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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40705?offset=30</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</guid>
	<pubDate>Sat, 26 Jun 2021 15:22:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics</link>
	<title><![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]></title>
	<description><![CDATA[<p><span>This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.</span></p>
<p><span>https://academic.oup.com/bib/article/22/3/bbaa123/5868070</span></p><p>Address of the bookmark: <a href="https://github.com/hzi-bifo/Quasimodo" rel="nofollow">https://github.com/hzi-bifo/Quasimodo</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling</guid>
	<pubDate>Thu, 25 Jul 2019 12:55:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39720/snakemake-workflow-dna-seq-gatk-variant-calling</link>
	<title><![CDATA[Snakemake workflow: dna-seq-gatk-variant-calling]]></title>
	<description><![CDATA[<p><span>This Snakemake pipeline implements the&nbsp;</span><a href="https://software.broadinstitute.org/gatk/best-practices/workflow?id=11145">GATK best-practices workflow</a><span>&nbsp;for calling small genomic variants.</span></p><p>Address of the bookmark: <a href="https://github.com/snakemake-workflows/dna-seq-gatk-variant-calling" rel="nofollow">https://github.com/snakemake-workflows/dna-seq-gatk-variant-calling</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14191/scalpel</guid>
	<pubDate>Wed, 20 Aug 2014 02:07:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14191/scalpel</link>
	<title><![CDATA[Scalpel]]></title>
	<description><![CDATA[<p>A team from Cold Spring Harbor Laboratory has released an algorithm, called Scalpel, for finding insertions and deletions in next generation sequencing data sets. Scalpel, which is open source and <a href="http://scalpel.sourceforge.net/" title="available for download">available for download</a> on SourceForge,&nbsp;<span>outperformed the popular tools GATK HaplotypeCaller and SOAPindel in test runs on both simulated and real whole human exomes.</span></p><p>Like other indel callers, Scalpel works by performing <em>de novo</em>&nbsp;assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.</p><p>The Cold Spring Harbor team's validation of Scalpel, <a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3069.html" title="published over the weekend in Nature Methods">published over the weekend in <em>Nature Methods</em></a>, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.</p><p>Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/45253/brava-browser</guid>
	<pubDate>Sun, 23 Aug 2026 10:32:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/45253/brava-browser</link>
	<title><![CDATA[BRaVa Browser]]></title>
	<description><![CDATA[<p>BRaVa Browser is an interactive web tool for exploring rare genetic variant associations. It allows users to search and visualize rare variant association results across genes and traits, making it easier to investigate potential relationships between genetic variation and disease or other phenotypes.</p>
<p>More at&nbsp;https://nikbaya.github.io/brava_browser/#/</p><p>Address of the bookmark: <a href="https://nikbaya.github.io/brava_browser/#/" rel="nofollow">https://nikbaya.github.io/brava_browser/#/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</guid>
	<pubDate>Mon, 06 Aug 2018 17:24:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</link>
	<title><![CDATA[NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data]]></title>
	<description><![CDATA[<p>NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purpose. The output of NextSV is in ANNOVAR-compatible bed format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer.</p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/Nextomics/NextSV" rel="nofollow">https://github.com/Nextomics/NextSV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/33479/novelseq-novel-sequence-insertion-detection</guid>
	<pubDate>Fri, 09 Jun 2017 04:31:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33479/novelseq-novel-sequence-insertion-detection</link>
	<title><![CDATA[NovelSeq: Novel Sequence Insertion Detection]]></title>
	<description><![CDATA[<p><span>The NovelSeq framework is designed to detect novel sequence insertions using high throughput paired-end whole genome sequencing data.</span></p>
<p>http://novelseq.sourceforge.net/Home</p>
<p>Paper at&nbsp;https://www.ncbi.nlm.nih.gov/pubmed/20385726</p><p>Address of the bookmark: <a href="http://novelseq.sourceforge.net/Home" rel="nofollow">http://novelseq.sourceforge.net/Home</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</guid>
	<pubDate>Fri, 08 Dec 2017 07:16:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</link>
	<title><![CDATA[Harvest: a suite of core-genome alignment and visualization tools]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="https://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="https://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="https://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
<li></li>
</ul><p>Address of the bookmark: <a href="https://harvest.readthedocs.io/en/latest/" rel="nofollow">https://harvest.readthedocs.io/en/latest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes</guid>
	<pubDate>Sat, 12 May 2018 07:26:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36583/eugi-a-novel-resource-for-studying-genomic-islands-to-facilitate-horizontal-gene-transfer-detection-in-eukaryotes</link>
	<title><![CDATA[EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes]]></title>
	<description><![CDATA[<p><span>SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.</span></p>
<p>https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8</p><p>Address of the bookmark: <a href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8" rel="nofollow">https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</guid>
	<pubDate>Wed, 08 May 2024 07:02:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44527/alvis-a-tool-for-contig-and-read-alignment-visualisation-and-chimera-detection</link>
	<title><![CDATA[Alvis: a tool for contig and read ALignment VISualisation and chimera detection]]></title>
	<description><![CDATA[<p><span>Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in a variety of alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies.</span></p>
<p>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04056-0</p><p>Address of the bookmark: <a href="https://github.com/SR-Martin/alvis" rel="nofollow">https://github.com/SR-Martin/alvis</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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