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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27076?offset=230</link>
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	<description><![CDATA[]]></description>
	
	<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/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/31018/j-circos</guid>
	<pubDate>Fri, 17 Feb 2017 09:06:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</link>
	<title><![CDATA[J-Circos]]></title>
	<description><![CDATA[<p>Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.</p><p>Address of the bookmark: <a href="http://www.australianprostatecentre.org/research/software/jcircos" rel="nofollow">http://www.australianprostatecentre.org/research/software/jcircos</a></p>]]></description>
	<dc:creator>Shruti Paniwala</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/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</guid>
	<pubDate>Mon, 06 Mar 2017 04:03:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</link>
	<title><![CDATA[MaxBin: software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm.]]></title>
	<description><![CDATA[<p><span>MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page.</span><br><br><span>Users can use MEGAN or similar software on MaxBin bins to find the taxonomy of each bin after the binning process is finished.</span></p>
<p>https://academic.oup.com/bioinformatics/article/32/4/605/1744462/MaxBin-2-0-an-automated-binning-algorithm-to<br><br><span>The most recent version of MaxBin is 2.2, which supports the analysis of coassemblies of multiple samples. It is available at this JBEI downloads sites as well as&nbsp;</span><a href="https://sourceforge.net/projects/maxbin/" target="_blank">MaxBin</a><span>&nbsp;and&nbsp;</span><a href="https://sourceforge.net/projects/maxbin2/" target="_blank">MaxBin 2.0</a><span>&nbsp;sourceforge sites.</span></p><p>Address of the bookmark: <a href="http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html" rel="nofollow">http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</guid>
	<pubDate>Mon, 10 Apr 2017 04:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32129/lordec-a-hybrid-error-correction-program-for-long-pacbio-reads</link>
	<title><![CDATA[LoRDEC: a hybrid error correction program for long, PacBio reads]]></title>
	<description><![CDATA[<p>LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.</p>
<p><br> Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.<br> After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.</p>
<p>Why is LoRDEC different?</p>
<ul>
<li>It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.</li>
<li>It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.</li>
</ul><p>Address of the bookmark: <a href="http://www.atgc-montpellier.fr/lordec/" rel="nofollow">http://www.atgc-montpellier.fr/lordec/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</guid>
	<pubDate>Tue, 07 Mar 2017 08:59:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</link>
	<title><![CDATA[GroopM: Metagenomic binning toolset]]></title>
	<description><![CDATA[<p>GroopM is a metagenomic binning toolset. It leverages spatio-temoral<br>dynamics (differential coverage) to accurately (and almost automatically)<br>extract population genomes from multi-sample metagenomic datasets.</p>
<p>GroopM is largely parameter-free. Use: groopm -h for more info.</p>
<p>For installation and usage instructions see : http://ecogenomics.github.io/GroopM/</p><p>Address of the bookmark: <a href="https://github.com/ecogenomics/GroopM" rel="nofollow">https://github.com/ecogenomics/GroopM</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>

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