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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34475?offset=140</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</guid>
	<pubDate>Fri, 01 May 2020 03:00:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</link>
	<title><![CDATA[RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes]]></title>
	<description><![CDATA[<p><span>RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/AppliedBioinformatics/RefKA" rel="nofollow">https://github.com/AppliedBioinformatics/RefKA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<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>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</guid>
	<pubDate>Tue, 29 Jul 2014 09:11:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/13267/the-genome-10k-project</link>
	<title><![CDATA[The Genome 10K Project]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/B57xDIGtCT0" frameborder="0" allowfullscreen></iframe>https://genome10k.soe.ucsc.edu

The Genome 10K project aims to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts.

The growing Genome 10K Community of Scientists (G10KCOS), made up of leading scientists representing major zoos, museums, research centers, and universities around the world, is dedicated to coordinating efforts in tissue specimen collection that will lay the groundwork for a large-scale sequencing and analysis project.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</guid>
	<pubDate>Tue, 26 Apr 2016 11:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</link>
	<title><![CDATA[CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.]]></title>
	<description><![CDATA[<p>Canu is a fork of the&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler">Celera Assembler</a>&nbsp;designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.</p>
<p>Canu is a hierachical assembly pipeline which runs in four steps:</p>
<ul>
<li>Detect overlaps in high-noise sequences using&nbsp;<a href="https://github.com/marbl/MHAP" title="MHAP">MHAP</a></li>
<li>Generate corrected sequence consensus</li>
<li>Trim corrected sequences</li>
<li>Assemble trimmed corrected sequences</li>
</ul>
<p>Read the&nbsp;<a href="http://canu.readthedocs.org/" title="docs">documentation</a></p>
<p>New release https://github.com/marbl/canu/releases</p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28999/redundans</guid>
	<pubDate>Thu, 01 Sep 2016 08:28:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28999/redundans</link>
	<title><![CDATA[Redundans]]></title>
	<description><![CDATA[<p>Redundans pipeline assists&nbsp;<span>an assembly of heterozygous genomes</span>.<br>Program takes as input&nbsp;<span>assembled contigs</span>,&nbsp;<span>paired-end and/or mate pairs sequencing libraries</span>&nbsp;and returns&nbsp;<span>scaffolded homozygous genome assembly</span>, that should be&nbsp;<span>less fragmented</span>&nbsp;and with total&nbsp;<span>size smaller</span>&nbsp;than the input contigs. In addition, Redundans will automatically&nbsp;<span>close the gaps</span>&nbsp;resulting from genome assembly or scaffolding&nbsp;<a href="https://github.com/Gabaldonlab/redundans/blob/master/test#redundans-pipeline">more details</a>.</p>
<p>The pipeline consists of three steps/modules:</p>
<ul>
<li><span>redundancy reduction</span>: detection and selectively removal of redundant contigs from an initial&nbsp;<em>de novo</em>&nbsp;assembly</li>
<li><span>scaffolding</span>: joining of genome fragments using paired-end and/or mate-pairs reads</li>
<li><span>gap closing</span></li>
</ul>
<p>Redundans is:</p>
<ul>
<li><span>fast</span>&nbsp;&amp;&nbsp;<span>lightweight</span>, multi-core support and memory-optimised, so it can be run even on the laptop for small-to-medium size genomes</li>
<li><span>flexible</span>&nbsp;toward many sequencing technologies (Illumina, 454 or Sanger) and library types (paired-end, mate pairs, fosmids)</li>
<li><span>modular</span>: every step can be ommited or replaced by another tools</li>
</ul><p>Address of the bookmark: <a href="https://github.com/Gabaldonlab/redundans" rel="nofollow">https://github.com/Gabaldonlab/redundans</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30090/standardized-velvet-assembly-report</guid>
	<pubDate>Fri, 09 Dec 2016 03:59:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30090/standardized-velvet-assembly-report</link>
	<title><![CDATA[Standardized velvet assembly report]]></title>
	<description><![CDATA[<p>Requirements:</p>
<ul>
<li>velvet (velveth velvetg should be in your PATH)</li>
<li>R (with Sweave)</li>
<li>pdflatex (usually part of TeTeX)</li>
<li>ggplot2 (from R prompt type install.packages("ggplot2","proto","xtable"))</li>
<li>Perl</li>
</ul>
<p>Optional:</p>
<ul>
<li>BLAT or BLAST (to generate alignments against a reference genome). If using BLAT, add faToTwoBit,gfClient,gfServer to your PATH. If using BLAST, add blastall and formatdb.</li>
</ul>
<p>Edit permute.sh to your liking, paying particular attention to the kmer, cvCut, expCov, and other flags</p>
<p>To Run:</p>
<ol>
<li><code>perl fastaAllSize mysequences.fa &gt; mysequences.stat or gunzip -c mysequences.fa.gz | fastaAllSize &gt; mysequences.stat</code>&nbsp;Substitute fastqAllSize for fastq files.</li>
<li><code>./permute.sh mysequences</code>&nbsp;(leave out the .fa)</li>
</ol>
<p>https://github.com/leipzig/standardized-velvet-assembly-report</p><p>Address of the bookmark: <a href="https://github.com/leipzig/standardized-velvet-assembly-report" rel="nofollow">https://github.com/leipzig/standardized-velvet-assembly-report</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30130/scaffmatch</guid>
	<pubDate>Tue, 13 Dec 2016 10:23:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30130/scaffmatch</link>
	<title><![CDATA[ScaffMatch]]></title>
	<description><![CDATA[<p>caffMatch is a novel scaffolding tool based on Maximum-Weight Matching able to produce high-quality scaffolds from NGS data (reads and contigs). The tool is written in Python 2.7. It also includes a bash script wrapper that calls aligner in case one needs to first map reads to contigs (instead of providing .sam files).</p>
<p>The arguments accepted by ScaffMatch are:</p>
<p>&nbsp; -w) Working directory -- this is the directory where ScaffMatch files are stored. These are .sam files produced after mapping reads to contigs and the resulting scaffolds file `scaffolds.fa` fasta file;</p>
<p>&nbsp; -c) Contig fasta file;</p>
<p>&nbsp; -m) Command line argument with no options. It is used when .sam files are used instead of reads .fastq files. Do not use this option if you provide reads files;</p>
<p>&nbsp; -1) (Comma separated list of) either .fastq or .sam file(s) corresponding to the first read of the read pair;</p>
<p>&nbsp; -2) (Comma separated list of) either .fastq or .sam file(s) corresponding to the second read of the read pair;</p>
<p>&nbsp; -i) (Comma separated list of) insert size(s) of the library(-ies);</p>
<p>&nbsp; -s) (Comma separated list of) library(-ies) standard deviation(s) of insert size(s);</p>
<p>&nbsp; -t) Bundle threshold. Pairs of contigs supported by number of read pairs less than the value of this argument are discarded. Optional argument, by default it is equal to 5;</p>
<p>&nbsp; -g) Matching heuristics: use `max_weight` for Maximum Weight Matching heuristics with the Insertion step, use `backbone` for Maximum Weight Matching heuristics without the Insertion step, use `greedy` for Greedy Matching heuristics;</p>
<p>&nbsp; -l) Log file - where to store the logs. Optional argument. By default, stdout is used.</p><p>Address of the bookmark: <a href="http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch" rel="nofollow">http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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/30249/genome-assembly-tutorial</guid>
	<pubDate>Tue, 20 Dec 2016 07:56:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30249/genome-assembly-tutorial</link>
	<title><![CDATA[Genome Assembly Tutorial]]></title>
	<description><![CDATA[<p><span>If genomes were completely random sequences in a statistical sense, 'overlap-consensus-layout' method would have been enough to assemble large genomes from Sanger reads. In contrast, real genomes often have long repetitive regions, and they are hard to assemble using overlap-consensus-layout approach. De Bruijn graph-based assembly approach was originally proposed to handle the assembly of repetitive regions better.</span></p>
<p><span>More at&nbsp;http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1</span></p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1" rel="nofollow">http://www.homolog.us/Tutorials/index.php?p=1.4&amp;s=1</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30701/harvest</guid>
	<pubDate>Tue, 31 Jan 2017 10:57:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30701/harvest</link>
	<title><![CDATA[Harvest]]></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="http://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="http://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="http://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="http://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
</ul>
<p><strong>Citation</strong></p>
<blockquote>
<div>Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15 (11), 1-15 [<a href="http://www.biomedcentral.com/content/pdf/s13059-014-0524-x.pdf">PDF</a>]</div>
</blockquote><p>Address of the bookmark: <a href="http://harvest.readthedocs.io/en/latest/index.html" rel="nofollow">http://harvest.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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