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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/27216?offset=0</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</guid>
	<pubDate>Fri, 17 Feb 2017 08:38:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31012/genomecomp</link>
	<title><![CDATA[GenomeComp]]></title>
	<description><![CDATA[<p>GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.<br><br>It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.<br><br>It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.</p><p>Address of the bookmark: <a href="http://www.mgc.ac.cn/GenomeComp/" rel="nofollow">http://www.mgc.ac.cn/GenomeComp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31014/sockeye</guid>
	<pubDate>Fri, 17 Feb 2017 08:51:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31014/sockeye</link>
	<title><![CDATA[sockeye]]></title>
	<description><![CDATA[<p>This sockeye&nbsp;software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.</p><p>Address of the bookmark: <a href="http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3" rel="nofollow">http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/32713/salzberg-lab</guid>
  <pubDate>Mon, 15 May 2017 05:14:01 -0500</pubDate>
  <link></link>
  <title><![CDATA[Salzberg lab]]></title>
  <description><![CDATA[
<p>We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.</p>

<p>https://salzberg-lab.org/</p>
]]></description>
</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/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</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/29018/crossmap</guid>
	<pubDate>Mon, 05 Sep 2016 04:07:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29018/crossmap</link>
	<title><![CDATA[CrossMap]]></title>
	<description><![CDATA[<ul>
<li>CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between&nbsp;<em>different assemblies</em>&nbsp;(such as Human&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2928/">hg18 (NCBI36)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/2758/">hg19 (GRCh37)</a>, Mouse&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/165668/">mm9 (MGSCv37)</a>&nbsp;&lt;&gt;&nbsp;<a href="http://www.ncbi.nlm.nih.gov/assembly/327618/">mm10 (GRCm38)</a>).</li>
<li>It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.</li>
<li>CrossMap is designed to liftover genome coordinates between assemblies. It&rsquo;s&nbsp;<em>not</em>&nbsp;a program for aligning sequences to reference genome.</li>
<li>We&nbsp;<em>do not</em>&nbsp;recommend using CrossMap to convert genome coordinates between species.</li>
</ul><p>Address of the bookmark: <a href="http://crossmap.sourceforge.net/" rel="nofollow">http://crossmap.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</guid>
	<pubDate>Tue, 16 Aug 2016 08:13:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28807/organellargenomedraw</link>
	<title><![CDATA[OrganellarGenomeDRAW]]></title>
	<description><![CDATA[<p><span>O</span><span>rganellar</span><span>G</span><span>enome</span><span>DRAW</span><span>&nbsp;is dedicated to convert genetic information stored in GenBank entries to graphical maps. The input text file has to be in GenBank flat file format, whereas the output format can be chosen among several formats. The application is especially optimized and adapted for the creation of high-quality, detailed circular maps of organellar genomes like the plastid genome (plastome) or the mitochondrial genome (chondriome). Nevertheless, you can upload any GenBank entry. The workflow is devided into three steps.&nbsp;</span></p>
<p><span>More at&nbsp;http://ogdraw.mpimp-golm.mpg.de/cgi-bin/ogdraw.pl</span></p><p>Address of the bookmark: <a href="http://ogdraw.mpimp-golm.mpg.de/index.shtml" rel="nofollow">http://ogdraw.mpimp-golm.mpg.de/index.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28844/teannot</guid>
	<pubDate>Thu, 18 Aug 2016 10:02:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28844/teannot</link>
	<title><![CDATA[TEannot]]></title>
	<description><![CDATA[<p>We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto" rel="nofollow">https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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