<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42987?offset=240</link>
	<atom:link href="https://bioinformaticsonline.com/related/42987?offset=240" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</guid>
	<pubDate>Wed, 22 Aug 2018 22:10:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</link>
	<title><![CDATA[ComparativeGenomics Exercise2]]></title>
	<description><![CDATA[<p>COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP&nbsp; @&nbsp;cbs.dtu.dk</p><p>Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37581" length="139956" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</guid>
	<pubDate>Sun, 04 Nov 2018 16:44:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</link>
	<title><![CDATA[Referee: Genome assembly quality scores]]></title>
	<description><![CDATA[<p>Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.</p>
<p>We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.</p>
<h3>Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.</h3>
<p>https://github.com/gwct/referee</p><p>Address of the bookmark: <a href="https://gwct.github.io/referee/#" rel="nofollow">https://gwct.github.io/referee/#</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</guid>
	<pubDate>Wed, 12 Dec 2018 08:31:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38441/genome-sequence-based-sub-species-delineation</link>
	<title><![CDATA[Genome sequence-based (sub-)species delineation.]]></title>
	<description><![CDATA[<p>The GGDC web service reports digital DDH for a universal and accurate delineation of prokaryotic (sub-)species without inheriting the pitfalls of classic DDH, and also calculates differences in genomic G+C content.</p>
<p>http://ggdc.dsmz.de/ggdc_background.php#</p>
<p><small>Genome-to-Genome Distance Calculator 2.1</small></p>
<p>http://ggdc.dsmz.de/ggdc.php</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://ggdc.dsmz.de/" rel="nofollow">http://ggdc.dsmz.de/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</guid>
	<pubDate>Tue, 22 Jan 2019 05:52:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</link>
	<title><![CDATA[Roary: the Pan Genome Pipeline]]></title>
	<description><![CDATA[<p><span>Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.</span></p><p>Address of the bookmark: <a href="https://sanger-pathogens.github.io/Roary/" rel="nofollow">https://sanger-pathogens.github.io/Roary/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39269/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Wed, 17 Apr 2019 19:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39269/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Breaking-Chimeric-Contigs">Chimeric contig correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</guid>
	<pubDate>Fri, 17 Jan 2020 02:11:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40549/mgse-mapping-based-genome-size-estimation</link>
	<title><![CDATA[MGSE: Mapping-based Genome Size Estimation]]></title>
	<description><![CDATA[<p>MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.</p><p>Address of the bookmark: <a href="https://github.com/bpucker/MGSE" rel="nofollow">https://github.com/bpucker/MGSE</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</guid>
	<pubDate>Tue, 03 Mar 2020 01:39:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41330/u-plot-genome-u-plot-sample-implementation</link>
	<title><![CDATA[U-Plot: Genome U-Plot sample implementation]]></title>
	<description><![CDATA[<p>The Genome U-Plot is a JavaScript tool to visualize Chromosomal abnormalities in the Human Genome using a U-shape layout.</p>
<p><img src="https://raw.githubusercontent.com/gaitat/GenomeUPlot/master/public/data/LNCAP.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/gaitat/GenomeUPlot" rel="nofollow">https://github.com/gaitat/GenomeUPlot</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</guid>
	<pubDate>Sun, 20 Dec 2020 01:39:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42415/sneakysnake-a-fast-and-accurate-universal-genome-pre-alignment-filter-for-cpus-gpus-and-fpgas</link>
	<title><![CDATA[SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs]]></title>
	<description><![CDATA[<p><span>The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads. Described by Alser et al. (preliminary version at&nbsp;</span><a href="https://arxiv.org/abs/1910.09020">https://arxiv.org/abs/1910.09020</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/CMU-SAFARI/SneakySnake" rel="nofollow">https://github.com/CMU-SAFARI/SneakySnake</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43060/simons-genome-diversity-project</guid>
	<pubDate>Sat, 08 May 2021 21:55:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43060/simons-genome-diversity-project</link>
	<title><![CDATA[Simons Genome Diversity Project]]></title>
	<description><![CDATA[<p><em>Complete genome sequences from more than one hundred diverse human populations</em></p>
<p>All genomes in the dataset were sequenced to at least 30x coverage using Illumina technology. The sequencing reads were mapped and genotyped using a customized procedure that was optimized for population genetic analysis. The researchers eliminated bias of alleles toward matching the human genome reference sequence, and determined genotypes on a single-sample basis to avoid preferential calling of genotypes from populations that had more individuals represented.</p><p>Address of the bookmark: <a href="https://www.simonsfoundation.org/simons-genome-diversity-project/" rel="nofollow">https://www.simonsfoundation.org/simons-genome-diversity-project/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</guid>
	<pubDate>Wed, 15 Sep 2021 22:17:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43376/hisat2-index-files-download</link>
	<title><![CDATA[HISAT2 Index Files Download !]]></title>
	<description><![CDATA[<p>Resource for downloading all the HISAT2 related files&nbsp;</p>
<p>Please cite:</p>
<blockquote>
<p>Kim, D., Paggi, J.M., Park, C.&nbsp;<em>et al.</em>&nbsp;Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.&nbsp;<em>Nat Biotechnol</em>&nbsp;<strong>37</strong>, 907&ndash;915 (2019).&nbsp;<a href="https://doi.org/10.1038/s41587-019-0201-4" target="_blank">https://doi.org/10.1038/s41587-019-0201-4</a></p>
</blockquote><p>Address of the bookmark: <a href="http://daehwankimlab.github.io/hisat2/download/#h-sapiens" rel="nofollow">http://daehwankimlab.github.io/hisat2/download/#h-sapiens</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

</channel>
</rss>