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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42148?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</guid>
	<pubDate>Wed, 29 Aug 2018 09:20:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</link>
	<title><![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]></title>
	<description><![CDATA[<p><em>indexcov</em><span>, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample.&nbsp;</span><em>Indexcov</em><span>&nbsp;is available at&nbsp;</span><a href="https://github.com/brentp/goleft" target="_blank">https://github.com/brentp/goleft</a><span>&nbsp;under the MIT license.</span></p><p>Address of the bookmark: <a href="https://github.com/brentp/goleft" rel="nofollow">https://github.com/brentp/goleft</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</guid>
	<pubDate>Thu, 15 Dec 2016 05:47:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</link>
	<title><![CDATA[MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation]]></title>
	<description><![CDATA[<p>MyPro is an improved genomics software pipeline for prokaryotic genomes. MyPro is user-friendly and requires minimal programming skills. High-quality prokaryotic genome assembly and annotation can be obtained with ease. It performed better than de novo assemblers and contig integration software. Produces more contiguous assemblies, higher N50 values and lower number of contigs.</p>
<p>More at https://sourceforge.net/projects/sb2nhri/files/MyPro/</p><p>Address of the bookmark: <a href="http://www.sciencedirect.com/science/article/pii/S0167701215001207" rel="nofollow">http://www.sciencedirect.com/science/article/pii/S0167701215001207</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</guid>
	<pubDate>Tue, 14 Jul 2020 06:42:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41969/shadowcaster-a-hybrid-approach-for-the-detection-of-horizontal-gene-transfer-events-in-prokaryotes</link>
	<title><![CDATA[ShadowCaster: a hybrid approach for the detection of horizontal gene transfer events in prokaryotes]]></title>
	<description><![CDATA[<p><span>ShadowCaster implements an evolutionary model to calculate Bayesian likelihoods for each &lsquo;alien genes&rsquo; with an unusual sequence composition according to the host genome background to detect HGT events in prokaryotes.</span></p>
<p><a href="https://www.mdpi.com/2073-4425/11/7/756/htm">https://www.mdpi.com/2073-4425/11/7/756/htm</a></p>
<p><a href="https://shadowcaster.readthedocs.io/en/latest/">https://shadowcaster.readthedocs.io/en/latest/</a></p>
<p><a href="https://github.com/dani2s/ShadowCaster_testData">https://github.com/dani2s/ShadowCaster_testData</a></p><p>Address of the bookmark: <a href="https://github.com/dani2s/ShadowCaster" rel="nofollow">https://github.com/dani2s/ShadowCaster</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</guid>
	<pubDate>Tue, 03 Jul 2018 04:09:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37221/asplice-a-scalable-and-memory-efficient-algorithm-for-de-novo-transcriptome-assembly</link>
	<title><![CDATA[ASplice: a scalable and memory-efficient algorithm for de novo transcriptome assembly]]></title>
	<description><![CDATA[With increased availability of de novo assembly algorithms, it is feasible to study entire transcriptomes of non-model organisms. While algorithms are available that are specifically designed for performing transcriptome assembly from high-throughput sequencing data, they are very memory-intensive, limiting their applications to small data sets with few libraries.

Texas A&amp;M University researchers develop a transcriptome assembly algorithm that recovers alternatively spliced isoforms and expression levels while utilizing as many RNA-Seq libraries as possible that contain hundreds of gigabases of data. New techniques are developed so that computations can be performed on a computing cluster with moderate amount of physical memory.

Availability – A software program that implements the algorithm is available at: http://faculty.cse.tamu.edu/shsze/asplice.

Sze SH, Pimsler ML, Tomberlin JK, Jones CD, Tarone AM. (2017) A scalable and memory-efficient algorithm for de novo transcriptome assembly of non-model organisms. BMC Genomics 18(Suppl 4):387.<p>Address of the bookmark: <a href="http://faculty.cse.tamu.edu/shsze/asplice/" rel="nofollow">http://faculty.cse.tamu.edu/shsze/asplice/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</guid>
	<pubDate>Sat, 08 Jun 2024 16:15:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly</link>
	<title><![CDATA[MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly]]></title>
	<description><![CDATA[<p><span>The MetaGraph framework</span><span>&nbsp;is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as&nbsp;</span><a href="https://metagraph.ethz.ch/#query">sequence search</a><span>&nbsp;or&nbsp;</span><a href="https://metagraph.ethz.ch/#assembly">differential assembly</a><span>.</span></p>
<p><span>Searcg link&nbsp;https://metagraph.ethz.ch/search&nbsp;</span></p>
<p><span>Pre-print&nbsp;https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4&nbsp;</span></p><p>Address of the bookmark: <a href="https://metagraph.ethz.ch/" rel="nofollow">https://metagraph.ethz.ch/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</guid>
	<pubDate>Sun, 15 Mar 2020 03:41:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41442/gsp4pdb-a-web-tool-to-visualize-search-and-explore-protein-ligand-structural-patterns</link>
	<title><![CDATA[GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns]]></title>
	<description><![CDATA[<p><span><span>GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.</span></span></p>
<p><span>GSP4PDB</span><span>&nbsp;is part of the services provided by the&nbsp;</span><a href="https://structuralbio.utalca.cl/" target="_blank">Bioinformatic Group</a><span>&nbsp;of the&nbsp;</span><a href="http://www.utalca.cl/" target="_blank">University of Talca</a></p>
<p><a href="http://gdblab.com/gsp4pdb/gsp4pdb2/">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>
<p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3352-x</p><p>Address of the bookmark: <a href="http://gdblab.com/gsp4pdb/gsp4pdb2/" rel="nofollow">http://gdblab.com/gsp4pdb/gsp4pdb2/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43904/jasmine-jointly-accurate-sv-merging-with-intersample-network-edges</guid>
	<pubDate>Sat, 02 Jul 2022 11:41:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43904/jasmine-jointly-accurate-sv-merging-with-intersample-network-edges</link>
	<title><![CDATA[JASMINE: Jointly Accurate Sv Merging with Intersample Network Edges]]></title>
	<description><![CDATA[<p><span>This tool is used to merge structural variants (SVs) across samples. Each sample has a number of SV calls, consisting of position information (chromosome, start, end, length), type and strand information, and a number of other values. Jasmine represents the set of all SVs across samples as a network, and uses a modified minimum spanning forest algorithm to determine the best way of merging the variants such that each merged variants represents a set of analogous variants occurring in different samples.</span></p><p>Address of the bookmark: <a href="https://github.com/mkirsche/Jasmine" rel="nofollow">https://github.com/mkirsche/Jasmine</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</guid>
	<pubDate>Sun, 22 Dec 2019 03:48:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads</link>
	<title><![CDATA[SViper: Swipe your Structural Variants called on long (ONT/PacBio) reads with short exact (Illumina) reads.]]></title>
	<description><![CDATA[<p>Call sviper</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants
</code></pre>
<p>This will output a&nbsp;<code>polished_variants.vcf</code>&nbsp;file, that contains all the refined variants.</p>
<p>Sometimes it is helpful to look at the polished sequence, e.g. with the IGV browser. In that case you want SViper to output the polished and aligned sequences in a bam file via the option&nbsp;<code>--output-polished-bam</code>:</p>
<pre><code>~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants --output-</code>polished-bam</pre><p>Address of the bookmark: <a href="https://github.com/smehringer/SViper" rel="nofollow">https://github.com/smehringer/SViper</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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