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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44628?offset=480</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39383/geck-trio-based-comparative-benchmarking-of-variant-calls</guid>
	<pubDate>Sun, 19 May 2019 20:54:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39383/geck-trio-based-comparative-benchmarking-of-variant-calls</link>
	<title><![CDATA[geck: trio-based comparative benchmarking of variant calls]]></title>
	<description><![CDATA[<p><span>Determine the accuracy of our model by comparing the precision and recall of GATK Unified Genotyper and Haplotype Caller on the high-confidence SNPs of the NIST Ashkenazim trio and the two independent Platinum Genome trios. We show that our method is able to estimate&nbsp;</span><em>differential</em><span>&nbsp;precision and recall between the two pipelines with&nbsp;</span><span>10<span>&minus;3</span></span><span>uncertainty.</span></p><p>Address of the bookmark: <a href="https://github.com/sbg/geck" rel="nofollow">https://github.com/sbg/geck</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/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</guid>
	<pubDate>Sun, 31 Mar 2024 02:43:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44501/minda-a-tool-for-evaluating-structural-variant-sv-callers</link>
	<title><![CDATA[Minda: a tool for evaluating structural variant (SV) callers]]></title>
	<description><![CDATA[<p dir="auto">Minda is a tool for evaluating structural variant (SV) callers that</p>
<ul dir="auto">
<li>standardizes VCF records for compatibility with both germline and somatic SV callers,</li>
<li>benchmarks against a single VCF input file, or</li>
<li>benchmarks against an ensemble call set created from multiple VCF input files.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/KolmogorovLab/minda" rel="nofollow">https://github.com/KolmogorovLab/minda</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/5933/virus-3d-animation</guid>
	<pubDate>Sat, 26 Oct 2013 09:01:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/5933/virus-3d-animation</link>
	<title><![CDATA[Virus 3D Animation]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/67ays2ZYr48" frameborder="0" allowfullscreen></iframe>piranha.dl facebook site: http://www.facebook.com/home.php?#!/pages/piranhadl-3D/131721586891915]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43643/corona-virus-literature</guid>
	<pubDate>Sun, 12 Dec 2021 23:30:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43643/corona-virus-literature</link>
	<title><![CDATA[Corona Virus Literature !]]></title>
	<description><![CDATA[<p><span><span>LitCovid</span>&nbsp;is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus.</span><span>&nbsp;It is the most comprehensive resource on the subject, providing a central access to&nbsp;</span><span>201482</span><span>&nbsp;(and&nbsp;</span><span>growing</span><span>) relevant articles in PubMed. The articles are updated daily and are further categorized by different research topics (e.g.&nbsp;</span><span>Long Covid</span><span>) and geographic locations for improved access. You can learn more at&nbsp;</span><a href="https://www.nature.com/articles/d41586-020-00694-1" target="_blank">Chen et al. Nature</a><span>&nbsp;(2020) or our&nbsp;</span><span>FAQ</span><span>, and download our data&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/research/coronavirus/#data-download">here</a><span>.</span></p>
<p>https://www.ncbi.nlm.nih.gov/research/coronavirus/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/research/coronavirus/" rel="nofollow">https://www.ncbi.nlm.nih.gov/research/coronavirus/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</guid>
	<pubDate>Wed, 24 Apr 2024 06:19:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</link>
	<title><![CDATA[Virus Bioinformatics Tools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools play a crucial role in studying viruses, enabling researchers to analyze their genetic makeup, structure, function, and evolution. Here are some commonly used bioinformatics tools for virus research</span></p>
<p>https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</p><p>Address of the bookmark: <a href="https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947" rel="nofollow">https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41886/coronavirus-sars-cov-2</guid>
	<pubDate>Wed, 17 Jun 2020 11:18:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41886/coronavirus-sars-cov-2</link>
	<title><![CDATA[Coronavirus SARS-CoV-2]]></title>
	<description><![CDATA[<p><span>Used Nanographics Vj, our real-time molecular visualization and animation software, to create this video showing the structure of the virus. In the video, you can see the latest theory on how the RNA is organized inside of the virus particle.</span></p>
<p><span><span>On this page, you can download&nbsp;</span><a href="https://nanographics.at/projects/sars-cov-2/sars-cov-2-renders.zip">high resolution images</a><span>&nbsp;of our renderings. We made them with transparent background, so that you can use it in your work. As the research progresses, we will keep updating the model as well as the images on this page, so stay tuned!</span></span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://nanographics.at/projects/sars-cov-2/" rel="nofollow">https://nanographics.at/projects/sars-cov-2/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</guid>
	<pubDate>Wed, 23 Jul 2014 07:29:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12963/cosmos-our-workflow-management-system-for-ngs-data</link>
	<title><![CDATA[COSMOS, our workflow management system for NGS data]]></title>
	<description><![CDATA[<p><strong>COSMOS</strong>, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via <a href="http://bioinformatics.oxfordjournals.org/content/early/2014/06/29/bioinformatics.btu385.abstract">Advance Access</a> in <em>Bioinformatics</em> (<a href="http://scholar.harvard.edu/lancaster/publications/cosmos-python-library-massively-parallel-workflows">Gafni et al. 2014</a>).&nbsp; It is also available for download for non-commercial academic and research purposes at:</p>
<p><strong>&nbsp;<a href="http://cosmos.hms.harvard.edu/">http://cosmos.hms.harvard.edu/</a></strong>.</p><p>Address of the bookmark: <a href="https://cosmos.hms.harvard.edu/" rel="nofollow">https://cosmos.hms.harvard.edu/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</guid>
	<pubDate>Wed, 21 Feb 2024 12:37:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44474/claw-chloroplast-long-read-assembly-workflow</link>
	<title><![CDATA[CLAW: Chloroplast Long-read Assembly Workflow]]></title>
	<description><![CDATA[<p dir="auto">CLAW (Chloroplast Long-read Assembly Workflow) is an mostly-automated Snakemake-based workflow for the assembly of chloroplast genomes. CLAW uses chloroplast long-reads, which are baited out of larger read libraries (e.g., an Oxford Nanopore Technologies MinION read library derived from photosynthetic tissue), for assembly with Flye and/or Unicycler. CLAW was designed with the novice bioinformatician in mind - it is easy to install and easy to use, requiring only minimal user input.</p><p>Address of the bookmark: <a href="https://github.com/aaronphillips7493/CLAW" rel="nofollow">https://github.com/aaronphillips7493/CLAW</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</guid>
	<pubDate>Sat, 09 Oct 2021 07:59:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43447/rna-seq-workflow-gene-level-exploratory-analysis-and-differential-expression</link>
	<title><![CDATA[RNA-seq workflow: gene-level exploratory analysis and differential expression]]></title>
	<description><![CDATA[<p><span>Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were quantified to the reference transcripts, and prepare gene-level count datasets for downstream analysis. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.</span></p><p>Address of the bookmark: <a href="http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html" rel="nofollow">http://master.bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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