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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31018?offset=80</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30203/e-rga-enhanced-reference-guided-assembly-of-complex-genomes</guid>
	<pubDate>Mon, 19 Dec 2016 05:56:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30203/e-rga-enhanced-reference-guided-assembly-of-complex-genomes</link>
	<title><![CDATA[e-RGA: enhanced Reference Guided Assembly of Complex Genomes]]></title>
	<description><![CDATA[<p><span>Next Generation Sequencing has totally changed genomics: we are able to produce huge amounts of data at an incredibly low cost compared to Sanger sequencing. Despite this, some old problems have become even more difficult, de novo assembly being on top of this list. Despite efforts to design tools able to assemble, de novo, an organism sequenced with short reads, the results are still far from those achievable with long reads. In this paper, we propose a novel method that aims to improve de novo assembly in the presence of a closely related reference. The idea is to combine de novo and reference-guided assembly in order to obtain enhanced results.</span></p><p>Address of the bookmark: <a href="http://journal.embnet.org/index.php/embnetjournal/article/view/208" rel="nofollow">http://journal.embnet.org/index.php/embnetjournal/article/view/208</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30214/megamerge-a-tool-to-merge-assembled-contigs-long-reads-from-metagenomic-sequencing-runs</guid>
	<pubDate>Mon, 19 Dec 2016 09:42:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30214/megamerge-a-tool-to-merge-assembled-contigs-long-reads-from-metagenomic-sequencing-runs</link>
	<title><![CDATA[MeGAMerge: A tool to merge assembled contigs, long reads from metagenomic sequencing runs]]></title>
	<description><![CDATA[<p>MeGAMerge</p>
<p>MeGAMerge (A tool to merge assembled contigs, long reads from metagenomic sequencing runs)</p>
<p>Description</p>
<p>MeGAMerge is a perl based wrapper/tool that can accept any number of sequence (FASTA) files containing assembled contigs of any length in Multi-FASTA format to produce an improved contig set based on OLC based assembly. All overlap parameters (Minimum Overlap Length, Identity, etc) are user-declarable at runtime. It is written to run on Linux.</p>
<p>Requirements:</p>
<p>You will need to have the following tools installed and in $PATH, or added to $binpath in the tool:</p>
<p>Newbler (specifically runAssembly)<br>Minimus2 (part of AMOS, also requires MUMmer)</p><p>Address of the bookmark: <a href="https://github.com/LANL-Bioinformatics/MeGAMerge" rel="nofollow">https://github.com/LANL-Bioinformatics/MeGAMerge</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</guid>
	<pubDate>Tue, 26 Apr 2016 03:50:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</link>
	<title><![CDATA[mrFAST:  Micro Read Fast Alignment Search Tool]]></title>
	<description><![CDATA[<p><span>mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find&nbsp;</span><strong><span style="text-decoration: underline;">'all'</span></strong><span>&nbsp; mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.</span></p>
<p><span>More at&nbsp;http://mrfast.sourceforge.net/manual.html</span></p><p>Address of the bookmark: <a href="http://mrfast.sourceforge.net/manual.html" rel="nofollow">http://mrfast.sourceforge.net/manual.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</guid>
	<pubDate>Fri, 20 Jan 2017 06:05:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30557/speedseq</link>
	<title><![CDATA[SpeedSeq]]></title>
	<description><![CDATA[<p>A flexible framework for rapid genome analysis and interpretation</p>
<p>C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.</p>
<p><a href="http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html">http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html</a></p><p>Address of the bookmark: <a href="https://github.com/hall-lab/speedseq" rel="nofollow">https://github.com/hall-lab/speedseq</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31714/krona</guid>
	<pubDate>Wed, 22 Mar 2017 04:47:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31714/krona</link>
	<title><![CDATA[Krona]]></title>
	<description><![CDATA[<p>Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an <a href="https://github.com/marbl/Krona/wiki/ExcelTemplate">Excel template</a> or <a href="https://github.com/marbl/Krona/wiki/KronaTools">KronaTools</a>, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see <a href="https://github.com/marbl/Krona/wiki/Browser%20support">Browser support</a>).</p>
<p><a href="http://marbl.github.io/Krona/img/screen_mgrast.png"><img src="https://camo.githubusercontent.com/27b71b1f1832523723c3d14dec764e7ad098438c/687474703a2f2f6d6172626c2e6769746875622e696f2f4b726f6e612f696d672f7468756d625f6d67726173742e706e67" width="210" height="167" alt="image" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marbl/Krona/wiki" rel="nofollow">https://github.com/marbl/Krona/wiki</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32481/sspace</guid>
	<pubDate>Fri, 05 May 2017 05:42:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32481/sspace</link>
	<title><![CDATA[SSPACE]]></title>
	<description><![CDATA[<p>SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" rel="nofollow">https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</guid>
	<pubDate>Fri, 30 May 2014 13:24:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11249/how-to-sequence-the-human-genome-mark-j-kiel</link>
	<title><![CDATA[How to sequence the human genome - Mark J. Kiel]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/MvuYATh7Y74" frameborder="0" allowfullscreen></iframe>View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel

Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence.

Lesson by Mark J. Kiel, animation by Marc Christoforidis.]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/12870/nuclear-dynamics-lab</guid>
  <pubDate>Thu, 17 Jul 2014 15:03:27 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nuclear Dynamics Lab]]></title>
  <description><![CDATA[
<p>Lab focus is to elucidate fundamental principles, new mechanisms, machineries and emergent properties that are involved in maintaining the genome and gene expression programmes for improvements in lifelong health and well-being for all.</p>

<p>More at http://www.babraham.ac.uk/our-research/nuclear-dynamics/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19090/deeptools</guid>
	<pubDate>Sat, 08 Nov 2014 15:02:08 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19090/deeptools</link>
	<title><![CDATA[deepTools]]></title>
	<description><![CDATA[<p>deepTools addresses the challenge of handling the large amounts of data that are now routinely generated from DNA sequencing centers. To do so, deepTools contains useful modules to process the mapped reads data to create coverage files in standard bedGraph and bigWig file formats. By doing so, deepTools allows the creation of normalized coverage files or the comparison between two files (for example, treatment and control). Finally, using such normalized and standardized files, multiple visualizations can be created to identify enrichments with functional annotations of the genome.<br /><br />Publicaton: http://nar.oxfordjournals.org/content/early/2014/05/05/nar.gku365.full<br /><br />Source Code and Wiki: https://github.com/fidelram/deepTools/wiki<br /><br />Galaxy Tool Shed repository: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools<br /><br />and example Galaxy workflows: http://toolshed.g2.bx.psu.edu/view/bgruening/deeptools_workflows</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>

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