<?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/43614?offset=290</link>
	<atom:link href="https://bioinformaticsonline.com/related/43614?offset=290" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27967/linux-command-line-exercises-for-ngs-data-processing</guid>
	<pubDate>Wed, 22 Jun 2016 07:59:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27967/linux-command-line-exercises-for-ngs-data-processing</link>
	<title><![CDATA[Linux command line exercises for NGS data processing]]></title>
	<description><![CDATA[<p>The purpose of this tutorial is to introduce students to the frequently used tools for NGS analysis as well as giving experience in writing one-liners. Copy the required files to your current directory, change directory (<code>cd</code>) to the <code>linuxTutorial</code> folder, and do all the processing inside:</p>
<pre><span>[uzi@quince-srv2 ~/]$</span> cp -r /home/opt/MScBioinformatics/linuxTutorial .
<span>[uzi@quince-srv2 ~/]$</span> cd linuxTutorial
<span>[uzi@quince-srv2 ~/linuxTutorial]$</span>
</pre>
<p>I have deliberately chosen <code>Awk</code> in the exercises as it is a language in itself and is used more often to manipulate NGS data as compared to the other command line tools such as <code>grep</code>, <code>sed</code>, <code>perl</code> etc. Furthermore, having a command on <code>awk</code> will make it easier to understand advanced tutorials such as <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/Illumina_workflow.html">Illumina Amplicons Processing Workflow</a>. <br><br> In <code>Linux</code>, we use a shell that is a program that takes your commands from the keyboard and gives them to the operating system. Most Linux systems utilize Bourne Again SHell (<code>bash</code>), but there are several additional shell programs on a typical Linux system such as <code>ksh</code>, <code>tcsh</code>, and <code>zsh</code>. To see which shell you are using, type</p>
<pre><span>[uzi@quince-srv2 ~/linuxTutorial]$</span> echo $SHELL

<span>/bin/bash
</span></pre><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/linux.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/linux.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</guid>
	<pubDate>Tue, 06 Sep 2016 03:58:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29103/genome-strip</link>
	<title><![CDATA[Genome STRiP]]></title>
	<description><![CDATA[<p><strong>Genome STRiP</strong><span>&nbsp;(Genome STRucture In Populations) is a suite of tools for discovering and genotyping structural variations using sequencing data. The methods are designed to detect shared variation using data from multiple individuals.</span><br><br><span>Genome STRiP looks both across and within a set of sequenced genomes to detect variation. The methods are adaptive and support heterogeneous data sets, including variations in sequencing depth, read lengths and mixtures of paired and single-end reads. A minimum of 20 to 30 genomes are required to get acceptable results, but the method gains power across genomes and processing more genomes provide better results.</span><br><br><span>To run discovery or genotyping on a single sequenced genome or a small set of genomes, you need to call your data against a background population, such as a set of genomes from the 1000 Genomes Project.&nbsp; The background population does not need to be matched to the target individuals.</span></p><p>Address of the bookmark: <a href="http://software.broadinstitute.org/software/genomestrip/" rel="nofollow">http://software.broadinstitute.org/software/genomestrip/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</guid>
	<pubDate>Thu, 18 Aug 2016 09:57:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</link>
	<title><![CDATA[RepeatModeler]]></title>
	<description><![CDATA[<p><span>RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.</span></p><p>Address of the bookmark: <a href="http://www.repeatmasker.org/RepeatModeler.html" rel="nofollow">http://www.repeatmasker.org/RepeatModeler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28884/tgnet</guid>
	<pubDate>Wed, 24 Aug 2016 05:36:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28884/tgnet</link>
	<title><![CDATA[TGNet]]></title>
	<description><![CDATA[<p><span>Recent technological progress has greatly facilitated&nbsp;</span><em>de novo</em><span>&nbsp;genome sequencing. However,&nbsp;</span><em>de novo</em><span>&nbsp;assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis.&nbsp;</span></p>
<p>Visualization and quality assessment of de novo genome assemblies</p>
<p>Citation</p>
<p>This software is fully described in the paper:<br>Riba-Grognuz, Keller, Falquet, Xenarios &amp; Wurm (2011) Visualization and quality assessment of de novo genome assemblies.</p>
<p>In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.</p>
<p>Software requirements</p>
<p>BLAT (tested with Standalone BLAT v. 32&times;1). Source Binaries .<br>Cytoscape (tested with versions 2.7.0, 2.8.2)<br>a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)</p><p>Address of the bookmark: <a href="https://github.com/ksanao/TGNet" rel="nofollow">https://github.com/ksanao/TGNet</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28915/useful-bioinformatics-tools</guid>
	<pubDate>Mon, 29 Aug 2016 04:08:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28915/useful-bioinformatics-tools</link>
	<title><![CDATA[Useful Bioinformatics Tools]]></title>
	<description><![CDATA[<p>Collections of few handy tools for bioinformatician</p>
<p>http://molbiol-tools.ca/Convert.htm</p><p>Address of the bookmark: <a href="http://molbiol-tools.ca/Convert.htm" rel="nofollow">http://molbiol-tools.ca/Convert.htm</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29004/r-chie</guid>
	<pubDate>Thu, 01 Sep 2016 11:47:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29004/r-chie</link>
	<title><![CDATA[R-chie]]></title>
	<description><![CDATA[<p><strong>R-chie</strong><span>&nbsp;allows you to make arc diagrams of RNA secondary structures, allowing for easy comparison and overlap of two structures, rank and display basepairs in colour and to also visualize corresponding multiple sequence alignments and co-variation information.</span><br><strong>R4RNA</strong><span>&nbsp;is the R package powering R-chie, available for&nbsp;</span><a href="http://www.e-rna.org/r-chie/download.cgi">download</a><span>&nbsp;and local use for more customized figures and scripting.</span></p>
<p>http://www.e-rna.org/r-chie/plot.cgi?eg=single</p><p>Address of the bookmark: <a href="http://www.e-rna.org/r-chie/plot.cgi?eg=single" rel="nofollow">http://www.e-rna.org/r-chie/plot.cgi?eg=single</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29110/structural-variants-ppt</guid>
	<pubDate>Wed, 07 Sep 2016 03:16:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29110/structural-variants-ppt</link>
	<title><![CDATA[Structural variants PPT]]></title>
	<description><![CDATA[<p>1000 Genomes data tutorial at ASHG</p><p>Structural variants presentation by</p><p>Jan Korbel</p><p>European Molecular Biology Laboratory (EMBL) Heidelberg Genome Biology Research Unit</p><p>Reference:&nbsp;</p><p>https://www.genome.gov/pages/research/der/1000genomesprojecttutorials/structuralvariants-jankorbel.pdf</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29110" length="1090837" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29210/cgview-circular-genome-viewer</guid>
	<pubDate>Mon, 19 Sep 2016 07:52:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29210/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[<p>GView is a Java package used to display and navigate bacterial genomes. GView is useful for producing high-quality genome maps for use in publications and websites, or as a visualization tool in a sequence annotation pipeline. Users can interact with the genome using a powerful pan-and-zoom interface, or GView can write static images of a genome to a file. GView can draw a genome using either circular or linear layouts. For examples of some of the images GView can produce, see the <a href="https://www.gview.ca/bin/view/GView/ImageGallery">Image Gallery</a>. GView is a re-write of <a href="http://wishart.biology.ualberta.ca/cgview/" target="_top">CGView</a>, a circular genome viewer written by Paul Stothard. The goal of GView is to provide greater user interaction, and more flexibility in how the genome map is rendered. To aid with easily configuring the display of a genome, a style editor has been included to provide an intuitive, user-friendly graphical user interface for customizing genome maps. Styling attributes such as colours or fonts for the various map elements can be adjusted in real time. Customized styles can be saved for later use or for application to other genome maps using GView's <a href="https://www.gview.ca/bin/view/GViewDocumentation/GViewGSS">custom file format</a>.</p><p>Address of the bookmark: <a href="http://wishart.biology.ualberta.ca/cgview/" rel="nofollow">http://wishart.biology.ualberta.ca/cgview/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</guid>
	<pubDate>Fri, 30 Sep 2016 10:22:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</link>
	<title><![CDATA[Murasaki]]></title>
	<description><![CDATA[<p>Murasaki is an anchor alignment program that is</p>
<ul style="margin-left: 16px;">
<li>exteremely fast (17 CPU hours for whole Human x Mouse genome (with 40 nodes: 35 wall minutes), or 8 mammals in 21 CPU hours (42 wall minutes))</li>
<li>scalable (Arbitrarily parallelizable across multiple nodes using MPI)</li>
<li>memory efficient. (Even a single node with 16GB of ram can handle over 1Gbp of sequence)</li>
<li>unlimited by pattern length or selection</li>
<li>repeat tolerant</li>
</ul>
<p><img src="http://murasaki.dna.bio.keio.ac.jp/9mammals-small.png" width="500" height="375" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki" rel="nofollow">http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>

</channel>
</rss>