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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40505?offset=20</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</guid>
	<pubDate>Wed, 20 Dec 2017 18:35:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34718/dipspades-assembler-for-highly-polymorphic-diploid-genomes</link>
	<title><![CDATA[dipSPAdes: Assembler for Highly Polymorphic Diploid Genomes.]]></title>
	<description><![CDATA[<p><span>While the number of sequenced diploid genomes have been steadily increasing in the last few years, assembly of highly polymorphic (HP) diploid genomes remains challenging. As a result, there is a shortage of tools for assembling HP genomes from the next generation sequencing (NGS) data. The initial approaches to assembling HP genomes were proposed in the pre-NGS era and are not well suited for NGS projects. To address this limitation, we developed the first de Bruijn graph assembler, dipSPAdes, for HP genomes that significantly improves on the state-of-the-art assemblers for HP diploid genomes.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pubmed/25734602" rel="nofollow">https://www.ncbi.nlm.nih.gov/pubmed/25734602</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40385/598-indian-genomes-from-55-ethnic-groups-sequenced</guid>
	<pubDate>Fri, 13 Dec 2019 20:31:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40385/598-indian-genomes-from-55-ethnic-groups-sequenced</link>
	<title><![CDATA[598 Indian Genomes from 55 ethnic groups Sequenced]]></title>
	<description><![CDATA[<ul>
<li><strong>This study reports sequence from 1,267 individuals that includes 598 individuals representing 55 ethnic groups that span the major language groups across India.</strong></li>
</ul><ul>
<li><strong>Importantly, this study found many large population groups from India in which individuals were more related to each other by descent. These groups are similar to the Finnish population group where many disease gene discoveries were made. The Finnish-equivalent Indian groups are going to be a great resource for disease gene discovery and they will aid in target identification, drug development and disease management.</strong><strong style="font-size: 12.8px;">&nbsp;</strong></li>
</ul><ul>
<li><strong>This study has identified many genetic variants that are specific to Indian population groups that were previously not known. Some of these are common variants in the Indian groups, but when first identified by previous studies from India involving smaller sample size, they were thought to be disease causing (for example in diabetes) as they were not represented in the Eurocentric variant database.&nbsp;</strong></li>
</ul><p><strong><img src="https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41586-019-1793-z/MediaObjects/41586_2019_1793_Fig1_HTML.png" alt="image" style="border: 0px;"></strong></p><ul>
<li><strong>Several variants that pre-dispose individuals to higher cancer risk were identified in this study. Once this part of the work is expanded, the data from this can be used to screen individuals to understand the disease risk and provide appropriate monitoring and proactive treatment. Similarly, variants linked to increase in adverse effect in individuals for certain drugs were found. Understanding this will allow doctors to provide alternate safer drugs to such patients.</strong></li>
</ul><p><strong>More at&nbsp;<a href="https://www.nature.com/articles/s41586-019-1793-z">https://www.nature.com/articles/s41586-019-1793-z</a></strong></p><p><strong><a href="https://www.nature.com/nature/volumes/576/issues/7785">https://www.nature.com/nature/volumes/576/issues/7785</a></strong></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</guid>
	<pubDate>Sat, 18 Nov 2017 16:10:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34377/genomicus-genome-browser-that-enables-users-to-navigate-in-genomes-in-several-dimensions</link>
	<title><![CDATA[Genomicus: genome browser that enables users to navigate in genomes in several dimensions]]></title>
	<description><![CDATA[<p>Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.</p>
<p>Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.</p>
<p>All the data on extant species displayed in this browser are from&nbsp;<a href="http://www.ensembl.org/">Ensembl</a>.</p><p>Address of the bookmark: <a href="http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl" rel="nofollow">http://genomicus.biologie.ens.fr/genomicus-90.01/cgi-bin/search.pl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34877/recovery-of-complete-genomes-from-metagenomes</guid>
	<pubDate>Wed, 27 Dec 2017 00:04:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34877/recovery-of-complete-genomes-from-metagenomes</link>
	<title><![CDATA[Recovery of complete genomes from metagenomes]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p><strong>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes</strong></p>
<p><a href="http://personprofil.aau.dk/120257">Mads Albertsen</a>,&nbsp;<a href="http://ecogenomic.org/users/phil-hugenholtz">Philip Hugenholtz</a>,&nbsp;<a href="http://ecogenomic.org/users/adam-skarshewski">Adam Skarshewski</a>,&nbsp;<a href="http://www.ecogenomic.org/users/gene-tyson">Gene W. Tyson</a>,&nbsp;<a href="http://personprofil.aau.dk/103057">K&aring;re L. Nielsen</a>&nbsp;and&nbsp;<a href="http://personprofil.aau.dk/105842">Per .H. Nielsen</a></p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p><p>Address of the bookmark: <a href="http://madsalbertsen.github.io/multi-metagenome/" rel="nofollow">http://madsalbertsen.github.io/multi-metagenome/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36590/digest-in-silico-restriction-digest-of-complete-genomes</guid>
	<pubDate>Mon, 14 May 2018 04:02:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36590/digest-in-silico-restriction-digest-of-complete-genomes</link>
	<title><![CDATA[Digest: In silico restriction digest of complete genomes]]></title>
	<description><![CDATA[<p><span>This tool allows to retrieve number of cleavages yielded by commercially available endonucleases in up-to-date sequenced prokaryotic genomes. When the number of fragments is bellow 50, Pulse Field gel Electrophoresis (PFGE) is simulated.</span></p>
<p>A tool for restriction digest of&nbsp;<a href="http://insilico.ehu.eus/restriction/long_seq/">long</a>user's sequences is available.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://insilico.ehu.es/digest/" rel="nofollow">http://insilico.ehu.es/digest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</guid>
	<pubDate>Thu, 09 Aug 2018 17:41:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37520/mmgenome-tools-for-extracting-individual-genomes-from-metagneomes</link>
	<title><![CDATA[mmgenome: Tools for extracting individual genomes from metagneomes]]></title>
	<description><![CDATA[<p>The mmgenome toolbox enables reproducible extraction of individual genomes from metagenomes. It builds on the&nbsp;<a href="http://madsalbertsen.github.io/multi-metagenome/">multi-metagenome</a>&nbsp;concept, but wraps most of the process of extracting genomes in simple R functions. Thereby making the whole process of binning easy and at the same time reproducible through the Rmarkdown format.</p>
<p>The mmgenome R package also facilitates effortless integration with additional data sources and hence should not be seen as "yet another binning method", but rather a package to integrate different binning strategies.</p>
<p>All functions in the mmgenome R package has associated documentation, check it out in R by e.g.&nbsp;<code>?mmplot</code>.</p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/mmgenome" rel="nofollow">https://github.com/MadsAlbertsen/mmgenome</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</guid>
	<pubDate>Thu, 20 Dec 2018 12:03:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38505/allhic-phasing-and-scaffolding-polyploid-genomes-based-on-hi-c-data</link>
	<title><![CDATA[ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data]]></title>
	<description><![CDATA[<p><span>The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps:&nbsp;</span><em>prune</em><span>,&nbsp;</span><em>partition</em><span>,&nbsp;</span><em>rescue</em><span>,&nbsp;</span><em>optimize</em><span>&nbsp;and&nbsp;</span><em>build</em><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/tangerzhang/ALLHiC/wiki" rel="nofollow">https://github.com/tangerzhang/ALLHiC/wiki</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</guid>
	<pubDate>Thu, 19 Dec 2019 07:33:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes</link>
	<title><![CDATA[HaploTypo: a variant-calling pipeline for phased genomes]]></title>
	<description><![CDATA[<p>An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome.</p>
<div>Availability and Implementation</div>
<p>HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at&nbsp;<a href="https://github.com/gabaldonlab/haplotypo" target="">https://github.com/gabaldonlab/haplotypo</a>, and as a Docker image.</p><p>Address of the bookmark: <a href="https://github.com/gabaldonlab/haplotypo" rel="nofollow">https://github.com/gabaldonlab/haplotypo</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</guid>
	<pubDate>Fri, 01 May 2020 03:00:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</link>
	<title><![CDATA[RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes]]></title>
	<description><![CDATA[<p><span>RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/AppliedBioinformatics/RefKA" rel="nofollow">https://github.com/AppliedBioinformatics/RefKA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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