<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40251?offset=100</link>
	<atom:link href="https://bioinformaticsonline.com/related/40251?offset=100" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</guid>
	<pubDate>Fri, 09 Nov 2018 13:34:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</link>
	<title><![CDATA[AMStat: display statistics of large sequence files from next generation sequencing projects]]></title>
	<description><![CDATA[<p><span>SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to&nbsp;</span><a href="http://samstat.sourceforge.net/#about">SAM/BAM</a><span>&nbsp;files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.</span></p><p>Address of the bookmark: <a href="http://samstat.sourceforge.net/" rel="nofollow">http://samstat.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</guid>
	<pubDate>Thu, 10 Jan 2019 04:42:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/38649/ngs-platforms-launched-by-bgi%E2%80%99s-mgi-tech</link>
	<title><![CDATA[NGS Platforms launched by BGI’s MGI Tech]]></title>
	<description><![CDATA[<p>MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission&nbsp;is to&nbsp;develop and promote advanced life science tools for future healthcare.</p><p>MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to&nbsp;$5&nbsp;per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.</p><p>In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for&nbsp;$1 million.</p><p>The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.</p><p><span>Powered by DNBseq&trade;, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.</span></p><p><span><span>SOURCE MGI</span></span></p><p>https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/</p><p>http://en.mgitech.cn/</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40544/ngs-bits-short-read-sequencing-tools</guid>
	<pubDate>Thu, 16 Jan 2020 23:14:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40544/ngs-bits-short-read-sequencing-tools</link>
	<title><![CDATA[ngs-bits - Short-read sequencing tools]]></title>
	<description><![CDATA[<p>Binaries of&nbsp;<em>ngs-bits</em>&nbsp;are available via Bioconda. Alternatively,&nbsp;<em>ngs-bits</em>&nbsp;can be built from sources:</p>
<ul>
<li><span>Binaries</span>&nbsp;for&nbsp;<a href="https://github.com/imgag/ngs-bits/blob/master/doc/install_bioconda.md">Linux/macOS</a></li>
<li>From&nbsp;<span>sources</span>&nbsp;for&nbsp;<a href="https://github.com/imgag/ngs-bits/blob/master/doc/install_unix.md">Linux/macOS</a></li>
<li>From&nbsp;<span>sources</span>&nbsp;for&nbsp;<a href="https://github.com/imgag/ngs-bits/blob/master/doc/install_win.md">Windows</a></li>
</ul><p>Address of the bookmark: <a href="https://github.com/imgag/ngs-bits" rel="nofollow">https://github.com/imgag/ngs-bits</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</guid>
	<pubDate>Fri, 31 Jan 2020 05:50:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads</link>
	<title><![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>LEGE</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/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</guid>
	<pubDate>Sat, 04 Jan 2020 01:08:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</link>
	<title><![CDATA[RePS: Repeat-masked Phrap with scaffolding, a WGS sequence assembler]]></title>
	<description><![CDATA[<p>RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering</p>
<p><img src="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/bin/45793-17f1_F4TT.jpg" alt="image" style="border: 0px;"></p>
<p>More at</p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/</a></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz" rel="nofollow">ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</guid>
	<pubDate>Thu, 07 Jul 2016 12:05:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</link>
	<title><![CDATA[Fancy Oneliner for Bioinformatics !!]]></title>
	<description><![CDATA[<p><span>This webpage lists some of the one-liners that we frequently use in metagenomic analyses. You can click on the following links to browse through different topics. You can copy/paste the commands as they are in your terminal screen, provided you follow the same naming conventions and folder structures as we have. We are sharing these codes with the intention that if they are useful and help you in your analyses, then we will be appropriately credited as considerable effort has been put into devising them.</span></p><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>

</channel>
</rss>