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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38041?offset=140</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34925/rectangle-graph-for-repeat-resolution-in-genome-assembly</guid>
	<pubDate>Thu, 28 Dec 2017 09:43:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34925/rectangle-graph-for-repeat-resolution-in-genome-assembly</link>
	<title><![CDATA[Rectangle Graph for Repeat Resolution in Genome Assembly]]></title>
	<description><![CDATA[<p>Ultimate tool for resolving repeats in genome assemblies.</p>
<p>Though the specific implementation of the idea of the rectangle graph approach is already included into the&nbsp;<a href="http://bioinf.spbau.ru/spades">current SPAdes distribution</a>, we're also releasing the Rectangle Graph Module (RGM) as the separate code which can be run independently of SPAdes. Although RGM differs from the current implementation of the rectangle graph approach in SPAdes, in the future we plan to integrate RGM in SPAdes. RGM can be run with other genome assemblers if they use the graph format as SPAdes files.</p>
<p>For more details see: Nikolay Vyahhi, Son K. Pham, Pavel Pevzner.&nbsp;<a href="http://www.springerlink.com/content/e617788h25u36440/">From de Bruijn Graphs to Rectangle Graphs for Genome Assembly</a>,&nbsp;<em>Lecture Notes in Bioinformatics</em>&nbsp;7534 (2012), pp. 249-261.</p><p>Address of the bookmark: <a href="http://bioinf.spbau.ru/en/rectangles" rel="nofollow">http://bioinf.spbau.ru/en/rectangles</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</guid>
	<pubDate>Wed, 28 Feb 2018 03:45:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35762/genome-assembly-stats-plotting</link>
	<title><![CDATA[Genome assembly stats plotting]]></title>
	<description><![CDATA[<p>A&nbsp;<em>de novo</em>&nbsp;genome assembly can be summarised b</p>
<p>y a number of metrics, including:</p>
<ul>
<li>Overall assembly length</li>
<li>Number of scaffolds/contigs</li>
<li>Length of longest scaffold/contig</li>
<li>Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns</li>
<li>CEGMA completeness</li>
<li>Scaffold/contig length/count distribution</li>
</ul>
<p>assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.</p>
<p>Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.</p><p>Address of the bookmark: <a href="https://github.com/rjchallis/assembly-stats" rel="nofollow">https://github.com/rjchallis/assembly-stats</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/36405/earth-biogenome-project</guid>
	<pubDate>Wed, 25 Apr 2018 07:48:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/36405/earth-biogenome-project</link>
	<title><![CDATA[Earth BioGenome Project]]></title>
	<description><![CDATA[<p><span>The central goal of the Earth BioGenome Project is to understand the evolution and organization of life on our planet by sequencing and functionally annotating the genomes of 1.5 million known species of eukaryotes, a massive group that includes plants, animals, fungi and other organisms whose cells have a nucleus that houses their chromosomal DNA. To date, the genomes of less than 0.2 percent of eukaryotic species have been sequenced.&nbsp;</span></p><p><span>More at&nbsp;https://www.ucdavis.edu/news/earth-biogenome-project-aims-sequence-dna-all-complex-life</span></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</guid>
	<pubDate>Wed, 20 Jun 2018 10:15:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases. For examples of the various output types, see the CGView gallery.

http://wishart.biology.ualberta.ca/cgview/gallery.html

http://stothard.afns.ualberta.ca/downloads/CCT/index.html

https://www.gview.ca/wiki/GView/WebHome

https://server.gview.ca/

http://stothard.afns.ualberta.ca/cgview_server/

Paper https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbx081/4037458<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>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/37927/you-cant-hide-from-genome-hackers</guid>
	<pubDate>Sat, 13 Oct 2018 14:17:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/37927/you-cant-hide-from-genome-hackers</link>
	<title><![CDATA[You can't hide from Genome Hackers]]></title>
	<description><![CDATA[<p><span>Young computational biologist named Yaniv Erlich shocked the research world by showing it was possible to&nbsp;</span><a href="https://www.wired.com/2013/01/your-genome-could-reveal-your-identity/">unmask the identities</a><span>&nbsp;of people listed in anonymous genetic databases using&nbsp;</span><a href="http://science.sciencemag.org/content/339/6117/321" target="_blank">only an Internet connection</a></p><p>Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832</p><p>More at&nbsp;https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38215/pwhatshap-a-parallel-high-performance-version-of-whatshap</guid>
	<pubDate>Wed, 14 Nov 2018 08:20:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38215/pwhatshap-a-parallel-high-performance-version-of-whatshap</link>
	<title><![CDATA[pWhatsHap: a parallel, high-performance version of WhatsHap]]></title>
	<description><![CDATA[<div id="ASec4">
<p>Given the potential relevance of efficient haplotyping in several analysis pipelines, we have designed and engineered&nbsp;pWhatsHap, a parallel, high-performance version of&nbsp;WhatsHap.&nbsp;pWhatsHap&nbsp;is embedded in a toolkit developed in Python and supports genomics datasets in standard file formats. Building on&nbsp;WhatsHap,&nbsp;pWhatsHap&nbsp;exhibits the same complexity exploring a number of possible solutions which is exponential in the coverage of the dataset. The parallel implementation on multi-core architectures allows for a relevant reduction of the execution time for haplotyping, while the provided results enjoy the same high accuracy as that provided by&nbsp;WhatsHap, which increases with coverage.</p>
</div>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1170-y</p><p>Address of the bookmark: <a href="https://bitbucket.org/whatshap/whatshap" rel="nofollow">https://bitbucket.org/whatshap/whatshap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</guid>
	<pubDate>Thu, 20 Dec 2018 17:39:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38515/genome-annotation-using-maker-tutorial</link>
	<title><![CDATA[Genome Annotation using MAKER tutorial !]]></title>
	<description><![CDATA[<p><a href="http://www.yandell-lab.org/software/maker.html">MAKER</a><span>&nbsp;is a great tool for annotating a reference genome using empirical and&nbsp;</span><em>ab initio</em><span>gene predictions.&nbsp;</span><a href="http://gmod.org/wiki/Main_Page">GMOD</a><span>, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a&nbsp;</span><em>de novo</em><span>&nbsp;genome annotation for&nbsp;</span><em>Boa constrictor</em><span>&nbsp;in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.</span></p><p>Address of the bookmark: <a href="https://www.biostars.org/p/261203/" rel="nofollow">https://www.biostars.org/p/261203/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38801/genome-assembly-forensics-finding-the-elusive-mis-assembly</guid>
	<pubDate>Sat, 26 Jan 2019 18:02:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38801/genome-assembly-forensics-finding-the-elusive-mis-assembly</link>
	<title><![CDATA[Genome assembly forensics: finding the elusive mis-assembly]]></title>
	<description><![CDATA[<p><span>We present the first collection of tools aimed at automated genome assembly validation. This work formalizes several mechanisms for detecting mis-assemblies, and describes their implementation in our automated validation pipeline, called&nbsp;</span><em>amosvalidate</em><span>. We demonstrate the application of our pipeline in both bacterial and eukaryotic genome assemblies, and highlight several assembly errors in both draft and finished genomes. The software described is compatible with common assembly formats and is released, open-source, at&nbsp;</span><a href="http://amos.sourceforge.net/" target="_blank">http://amos.sourceforge.net</a><span>.</span></p>
<p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2397507/&nbsp;</p>
<p>http://amos.sourceforge.net/wiki/index.php/AMOS</p><p>Address of the bookmark: <a href="http://amos.sourceforge.net/wiki/index.php/AMOS" rel="nofollow">http://amos.sourceforge.net/wiki/index.php/AMOS</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39626/geval-genome-evaluation-browser</guid>
	<pubDate>Tue, 18 Jun 2019 05:39:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39626/geval-genome-evaluation-browser</link>
	<title><![CDATA[gEVAL: Genome Evaluation Browser]]></title>
	<description><![CDATA[<p>The&nbsp;<strong>gEVAL Browser</strong>&nbsp;allows the evaluation of genome assemblies through its tools and pre-computed analyses.</p>
<p>The strength of this browser is the ability to navigate an up to date assembly and identify problematic regions and assist in strategizing potential solutions for these issues.</p>
<p>This facilitates the improvement of overall assemblies to a &ldquo;gold&rdquo; standard for release as reference genomes</p><p>Address of the bookmark: <a href="https://geval.sanger.ac.uk/index.html" rel="nofollow">https://geval.sanger.ac.uk/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</guid>
	<pubDate>Mon, 20 Jan 2020 05:13:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40573/de-novo-genome-assembly-for-illumina-data</link>
	<title><![CDATA[De novo Genome Assembly for Illumina Data]]></title>
	<description><![CDATA[<p>Written and maintained by <a href="mailto:simon.gladman@unimelb.edu.au">Simon Gladman</a> - Melbourne Bioinformatics (formerly VLSCI)</p>
<p>Protocol Overview / Introduction</p>
<p>In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.</p>
<p>https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</p><p>Address of the bookmark: <a href="https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/" rel="nofollow">https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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