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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44489?offset=80</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>
</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>
<item>
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</guid>
	<pubDate>Fri, 24 Feb 2017 04:50:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31087/bedtools</link>
	<title><![CDATA[bedtools]]></title>
	<description><![CDATA[<p>Collectively, the&nbsp;<strong>bedtools</strong>&nbsp;utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable&nbsp;<em>genome arithmetic</em>: that is, set theory on the genome. For example,&nbsp;<strong>bedtools</strong>&nbsp;allows one to<em>intersect</em>,&nbsp;<em>merge</em>,&nbsp;<em>count</em>,&nbsp;<em>complement</em>, and&nbsp;<em>shuffle</em>&nbsp;genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g.,&nbsp;<em>intersect</em>&nbsp;two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.</p>
<p><strong>bedtools</strong>&nbsp;is developed in the&nbsp;<a href="http://quinlanlab.org/">Quinlan laboratory</a>&nbsp;at the&nbsp;<a href="http://www.utah.edu/">University of Utah</a>&nbsp;and benefits from fantastic contributions made by scientists worldwide.</p><p>Address of the bookmark: <a href="http://bedtools.readthedocs.io/en/latest/index.html" rel="nofollow">http://bedtools.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes</guid>
	<pubDate>Tue, 28 Feb 2017 09:01:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes</link>
	<title><![CDATA[splitbam: splits a BAM by chromosomes]]></title>
	<description><![CDATA[<p><strong>splitbam</strong>&nbsp;splits a BAM by chromosomes.</p>
<p>Using the reference sequence dictionary (<code>*.dict</code>), it also creates some empty BAM files if no sam record was found for a chromosome. A pair of 'mock' SAM-Records can also be added to those empty BAMs to avoid some tools (like samtools) to crash.</p>
<h1>Usage</h1>
<p><code>java -jar splitbam.jar -p OUT/__CHROM__/__CHROM__.bam -R ref.fasta (bam|sam|stdin)</code></p>
<h1>Options</h1>
<ul>
<li>-h help; This screen.</li>
<li>-R (indexed reference file) REQUIRED.</li>
<li>-u (unmapped chromosome name): default:Unmapped</li>
<li>-e | --empty : generate EMPTY bams for chromosome having no read mapped</li>
<li>-m | --mock : if option '-e', add a mock pair of sam records to the empty bam</li>
<li>-p (output file/bam pattern) REQUIRED. MUST contain&nbsp;<strong><code>__CHROM__</code></strong>&nbsp;and end with .bam</li>
<li>-s assume input is sorted.</li>
<li>-x | --index create index.</li>
<li>-t | --tmp (dir) tmp file directory</li>
<li>-G (file) chrom-group file (see below)</li>
</ul><p>Address of the bookmark: <a href="https://code.google.com/archive/p/jvarkit/wikis/SplitBam.wiki" rel="nofollow">https://code.google.com/archive/p/jvarkit/wikis/SplitBam.wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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