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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/32485?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30212/pear</guid>
	<pubDate>Mon, 19 Dec 2016 09:28:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30212/pear</link>
	<title><![CDATA[PEAR]]></title>
	<description><![CDATA[<p><strong>PEAR</strong>&nbsp;is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.</p>
<p>PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.</p><p>Address of the bookmark: <a href="http://sco.h-its.org/exelixis/web/software/pear/doc.html" rel="nofollow">http://sco.h-its.org/exelixis/web/software/pear/doc.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30976/brig</guid>
	<pubDate>Thu, 16 Feb 2017 13:14:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30976/brig</link>
	<title><![CDATA[BRIG]]></title>
	<description><![CDATA[<p>BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:<a href="http://sourceforge.net/projects/brig">http://sourceforge.net/projects/brig</a></p>
<p>If you have any questions or comments, post them on&nbsp;<a href="http://sourceforge.net/tracker/?group_id=328245">one of the trackers</a>&nbsp;on BRIG&rsquo;s SourceForge page:<a href="http://sourceforge.net/tracker/?group_id=328245">http://sourceforge.net/tracker/?group_id=328245</a>.</p>
<p>Features:</p>
<ul>
<li>Images show similarity between a central reference sequence and other sequences as concentric rings.</li>
<li>BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.</li>
<li>Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.</li>
<li>Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.</li>
<li>BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://brig.sourceforge.net/" rel="nofollow">http://brig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</guid>
	<pubDate>Fri, 03 Mar 2017 10:14:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</link>
	<title><![CDATA[Multi-metagenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes<br><br>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26309/ratt</guid>
	<pubDate>Sun, 07 Feb 2016 16:09:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26309/ratt</link>
	<title><![CDATA[RATT]]></title>
	<description><![CDATA[<p><strong>RATT</strong> is software to transfer annotation from a reference (annotated) genome to an unannotated query genome.</p>
<p>It was first developed to transfer annotations between different genome assembly versions. However, it can also transfer annotations between strains and even different species, like <em>Plasmodium chabaudi</em> onto <em> P. berghei</em>, between different Leishmania species or <em>Salmonella enterica</em> onto other Salmonella serotypes. <strong>RATT</strong> is able to transfer any entries present on a reference sequence, such as the systematic id or an annotator's notes; such information would be lost in a <em>de novo</em> annotation.</p>
<p>More at http://ratt.sourceforge.net/</p><p>Address of the bookmark: <a href="http://ratt.sourceforge.net/" rel="nofollow">http://ratt.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</guid>
	<pubDate>Fri, 20 May 2016 19:08:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</link>
	<title><![CDATA[Hagfish - assess an assembly through creative use of coverage plots]]></title>
	<description><![CDATA[<p>Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of&nbsp;<em style="font-size: 12.8px;">de novo</em>&nbsp;genome assembly or identification of structural variation in a genome re-sequencing experiment.</p>
<p>Hagfish requires a reference sequence and a&nbsp;<span>paired end</span>&nbsp;re-sequencing data set. Hagfish has more power the larger the insert size of the paired end library is.</p>
<p>Quick links:&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Install">Installation</a>,<a href="https://github.com/mfiers/hagfish/wiki/Operation">Operation</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/ReadMappers">Read mappers</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Scripts">Hagfish scripts</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Plots">Hagfish plots</a></p><p>Address of the bookmark: <a href="https://github.com/mfiers/hagfish" rel="nofollow">https://github.com/mfiers/hagfish</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</guid>
	<pubDate>Mon, 14 May 2018 04:26:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36592/lachesis-genome-assembly-with-hi-c-based-contact-probability-maps-lachesis</link>
	<title><![CDATA[LACHESIS: Genome Assembly with Hi-C-based Contact Probability Maps (LACHESIS)]]></title>
	<description><![CDATA[<p>LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale&nbsp;<em>de novo</em>&nbsp;genome assembly.</p>
<p>Further information about LACHESIS, including source code, documentation and a user's guide are available at:&nbsp;<a href="http://shendurelab.github.io/LACHESIS/">http://shendurelab.github.io/LACHESIS</a>.</p>
<p>Manuscript describing LACHESIS was published as: Burton JN#, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J#.&nbsp;<em>Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions.</em>&nbsp;Nature Biotechnology 2013 Dec;31(12):1119-25. doi:&nbsp;<a href="http://dx.doi.org/10.1038/nbt.2727">10.1038/nbt.272</a>. PubMed PMID:&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/24185095">24185095</a>.</p>
<p>&nbsp;</p>
<p>http://shendurelab.github.io/LACHESIS/</p><p>Address of the bookmark: <a href="http://shendurelab.github.io/LACHESIS/" rel="nofollow">http://shendurelab.github.io/LACHESIS/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29343/accnet</guid>
	<pubDate>Fri, 07 Oct 2016 05:22:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29343/accnet</link>
	<title><![CDATA[AccNET]]></title>
	<description><![CDATA[<p><span>AccNET is a Perl application that presents a new way to study the accessory genome of a given set of organisms. Using the proteomes of these organisms, AccNET create a bipartite network compatible with common network analysis platforms. AccNET collects phylogenetic and functional information in a network improving the analysis capability. Networks offer a new perspective of organism organization through elements acquired by horizontal gene transfers and not constricted by hierarchical structures.</span></p>
<p><span>More at&nbsp;https://www.youtube.com/watch?v=vdGuy1GAJrQ</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/accnet/" rel="nofollow">https://sourceforge.net/projects/accnet/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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