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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44597?offset=60</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</guid>
	<pubDate>Tue, 09 Apr 2019 07:23:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</link>
	<title><![CDATA[CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants]]></title>
	<description><![CDATA[<p><span>Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.</span></p>
<p><a href="https://www.nature.com/articles/nm.3975">https://www.nature.com/articles/nm.3975</a></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/nm.3975" rel="nofollow">https://www.nature.com/articles/nm.3975</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</guid>
	<pubDate>Thu, 19 Dec 2019 07:33:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</link>
	<title><![CDATA[HaploTypo: a variant-calling pipeline for phased genomes]]></title>
	<description><![CDATA[<p>An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome.</p>
<div>Availability and Implementation</div>
<p>HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at&nbsp;<a href="https://github.com/gabaldonlab/haplotypo" target="">https://github.com/gabaldonlab/haplotypo</a>, and as a Docker image.</p><p>Address of the bookmark: <a href="https://github.com/gabaldonlab/haplotypo" rel="nofollow">https://github.com/gabaldonlab/haplotypo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</guid>
	<pubDate>Fri, 14 Feb 2020 14:23:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</link>
	<title><![CDATA[SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.]]></title>
	<description><![CDATA[<p>This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.</p>
<p>Here is an illustration of this pipeline:</p>
<p>&nbsp;<img src="https://github.com/BGI-Qingdao/SLR-superscaffolder/raw/master/image.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/BGI-Qingdao/SLR-superscaffolder" rel="nofollow">https://github.com/BGI-Qingdao/SLR-superscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline</guid>
	<pubDate>Sun, 20 Dec 2020 01:36:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42413/liftoff-an-accurate-gff3gtf-lift-over-pipeline</link>
	<title><![CDATA[Liftoff: An accurate GFF3/GTF lift over pipeline]]></title>
	<description><![CDATA[<p><span>Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated &ldquo;chain&rdquo; file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.</span></p><p>Address of the bookmark: <a href="https://github.com/agshumate/Liftoff" rel="nofollow">https://github.com/agshumate/Liftoff</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</guid>
	<pubDate>Mon, 06 Sep 2021 02:44:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43353/judi-just-do-it</link>
	<title><![CDATA[JUDI: Just Do It]]></title>
	<description><![CDATA[<p><em>judi</em><span>&nbsp;comes from the idea of bringing the power and efficiency of&nbsp;</span><em>doit</em><span>&nbsp;to execute any kind of task under many combinations of parameter settings.</span></p>
<p><span>https://github.com/ncbi/JUDI</span></p><p>Address of the bookmark: <a href="https://github.com/ncbi/JUDI" rel="nofollow">https://github.com/ncbi/JUDI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</guid>
	<pubDate>Wed, 06 Sep 2023 00:14:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data</link>
	<title><![CDATA[PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data]]></title>
	<description><![CDATA[<p dir="auto"><span>Phylo</span>genomic Analysis Pipeline for&nbsp;<span>Herb</span>arium Specimens</p>
<p dir="auto"><span>What is PhyloHerb</span>: PhyloHerb is a wrapper program to process&nbsp;<span>genome skimming</span>&nbsp;data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include&nbsp;<span>low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming</span>.</p>
<p dir="auto"><span>License</span>: GNU General Public License</p>
<p dir="auto"><span>Citation</span>:</p>
<ul dir="auto">
<li>Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1&ndash;9.&nbsp;<a href="https://doi.org/10.1002/aps3.11475">https://doi.org/10.1002/aps3.11475</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/lmcai/PhyloHerb/" rel="nofollow">https://github.com/lmcai/PhyloHerb/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22761/pit-bioinformatics-group</guid>
  <pubDate>Tue, 16 Jun 2015 14:34:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[PIT Bioinformatics Group]]></title>
  <description><![CDATA[
<p>PIT Bioinformatics Group solves problems in bioinformatics and  computational biology. Recent developed online tools:</p>

<p>- Budapest Reference Connectome: View a parametrizable connectome (brain graph).<br />- AmphoraNet: The webserver implementation of the AMPHORA2 workflow for phylogenetic analysis of metagenomic shotgun sequencing data.<br />- AmphoraVizu: Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet.<br />- SCARF: Free online association rule mining tool.</p>

<p>More at: http://pitgroup.org</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</guid>
	<pubDate>Wed, 08 May 2024 07:32:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44529/contigextender-a-new-approach-to-improving-de-novo-sequence-assembly-for-viral-metagenomics-data</link>
	<title><![CDATA[ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data]]></title>
	<description><![CDATA[<p dir="auto">ContigExtender, was developed to extend contigs, complementing de novo assembly. ContigExtender employs a novel recursive Overlap Layout Candidates (r-OLC) strategy that explores multiple extending paths to achieve longer and highly accurate contigs. ContigExtender is effective for extending contigs significantly in in silico synthesized and real metagenomics datasets.</p>
<p dir="auto">More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953547/</p>
<p dir="auto"><a href="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" target="_blank"><img src="https://camo.githubusercontent.com/72dc78177cd84dd0c667a2922a9fd984fb548b5ec94b11f9a547211a4adba3b1/68747470733a2f2f692e696d6775722e636f6d2f7734516944496a2e706e67" alt="extension process" title="extension process" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/dengzac/contig-extender" rel="nofollow">https://github.com/dengzac/contig-extender</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/6954/workshop-on-population-and-metagenomics-analysis-nerc</guid>
  <pubDate>Sun, 01 Dec 2013 14:25:45 -0600</pubDate>
  <link></link>
  <title><![CDATA[Workshop on population and metagenomics analysis @ NERC]]></title>
  <description><![CDATA[
<p>Workshop Overview</p>

<p>A ten-day workshop taking place between 25 February - 6 March 2014 providing detailed hands-on training for population and meta-genomics analysis for researchers with little or no background in mathematics or computing.</p>

<p>Venue: Dartington Hall, Totnes, Devon (nearest train station - Totnes)</p>

<p>Times: 25 February - 6th March 2014.</p>

<p>Arrival evening of Tuesday 25 February 2014. Departure morning of 6th March 2014. The course itself will take place 9am-12pm, 2pm-5pm and on some evenings 7pm-10pm everyday 26 February-5th March. Students are expected to attend the entire course.</p>

<p>Contact: research-events@exeter.ac.uk</p>

<p>Registration</p>

<p>The course itself is free of charged and is funded by a Professional Postgraduate Development Award from NERC.</p>

<p>A total of 30 funded places are available which cover the costs of accommodation and food, but not the cost of transportation to/from the venue.</p>

<p>An additional 10 places are available for participants from industry. The cost of accommodation and meals will need to be covered by the participants.</p>

<p>You should register your interest by 31 December 2013. Participants will be informed by 10th January 2014 as to whether they have been selected. Please note that preference will be given to researchers funded by NERC.</p>

<p>More at http://www.eventbrite.co.uk/e/nerc-workshop-on-population-and-metagenomics-analysis-tickets-8628888237</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</guid>
	<pubDate>Mon, 04 Dec 2017 07:18:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34515/metasim-a-sequencing-simulator-for-genomics-and-metagenomics</link>
	<title><![CDATA[MetaSim A Sequencing Simulator for Genomics and Metagenomics.]]></title>
	<description><![CDATA[<p><span>Our software can be used to&nbsp;</span><strong>generate collections of synthetic reads</strong><span>&nbsp;that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to&nbsp;</span><strong>design a metagenome</strong><span>&nbsp;by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a&nbsp;</span><strong>simulation of a number of different sequencing technologies</strong><span>. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree.&nbsp;</span></p><p>Address of the bookmark: <a href="http://ab.inf.uni-tuebingen.de/software/metasim/" rel="nofollow">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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