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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43722?offset=130</link>
	<atom:link href="https://bioinformaticsonline.com/related/43722?offset=130" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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<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/news/view/32719/download-assemblies-from-ncbi</guid>
	<pubDate>Mon, 15 May 2017 06:02:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/32719/download-assemblies-from-ncbi</link>
	<title><![CDATA[Download assemblies from NCBI]]></title>
	<description><![CDATA[<p>A new &ldquo;Download assemblies&rdquo; button is now available in the&nbsp;<a href="https://www.ncbi.nlm.nih.gov/assembly" target="_blank">Assembly</a>&nbsp;database. This makes it easy to download data for multiple genomes without having to write scripts.</p><p>For example, you can run a search in Assembly and use check boxes (see left side of screenshot below) to refine the set of genome assemblies of interest. Then, just open the &ldquo;Download assemblies&rdquo; menu, choose the source database (<a href="https://www.ncbi.nlm.nih.gov/genbank/" target="_blank">GenBank</a>&nbsp;or&nbsp;<a href="https://www.ncbi.nlm.nih.gov/refseq/" target="_blank">RefSeq</a>), choose the file type, and start the download. An archive file will be saved to your computer that can be expanded into a folder containing your selected genome data files.</p><p><img src="https://ncbiinsights.files.wordpress.com/2017/05/download_button.jpg?w=584" alt="image" width="584" height="444" style="border: 0px; border: 0px;"></p><p>&nbsp;</p><p>More at&nbsp;https://ncbiinsights.ncbi.nlm.nih.gov/2017/05/08/genome-data-download-made-easy/</p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</guid>
	<pubDate>Mon, 29 May 2017 05:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33221/genome-annotation-transfer-utility-gatu</link>
	<title><![CDATA[Genome Annotation Transfer Utility (GATU)]]></title>
	<description><![CDATA[<p>Genome Annotation Transfer Utility (GATU) was designed to facilitate quick, efficient annotation of similar genomes using genomes that have already been annotated. For example, whenever a new strain of SARS coronavirus is sequenced, it is possible, using GATU, to automatically annotate the new strain using a previously-annotated strain of SARS CoV. This saves researchers from tedious manual annotation of these sequences.</p>
<p>The program utilizes tBLASTn and BLASTn algorithms to map genes from the reference genome (the annotated strain) to the new sequence (the unannotated strain). The goal is to annotate the majority of the new genome&rsquo;s genes in a single step. ORFs present in the target genome and absent from the reference genome are also identified; these ORFs can be further analyzed using BLAST, VGO and BBB. Afterwards, they can either be accepted for/rejected from annotation. GATU can handle multiple-exon genes as well as mature peptides. Although it was designed for use with viral genomes, GATU can also be used to help annotate larger genomes (ie. bacterial genomes).</p>
<p>The output is saved in GenBank, XML, or EMBL file format.</p><p>Address of the bookmark: <a href="https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/" rel="nofollow">https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome</guid>
	<pubDate>Wed, 29 Nov 2017 05:08:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome</link>
	<title><![CDATA[Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome]]></title>
	<description><![CDATA[<p><span>Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available that we used for sequencing the S. cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr (</span><a href="https://github.com/jgurtowski/nanocorr">https://github.com/jgurtowski/nanocorr</a><span>) specifically for Oxford Nanopore reads, as existing packages were incapable of assembling the long read lengths (5-50kbp) at such high error rate (between ~5 and 40% error). With this new method we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: the contig N50 length is more than ten-times greater than an Illumina-only assembly (678kb versus 59.9kbp), and has greater than 99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.</span></p><p>Address of the bookmark: <a href="http://schatzlab.cshl.edu/data/nanocorr/" rel="nofollow">http://schatzlab.cshl.edu/data/nanocorr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</guid>
	<pubDate>Wed, 19 Sep 2018 07:47:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37746/funannotate-eukaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[funannotate: Eukaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p><span>Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.</span></p><p>Address of the bookmark: <a href="https://github.com/nextgenusfs/funannotate" rel="nofollow">https://github.com/nextgenusfs/funannotate</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</guid>
	<pubDate>Tue, 17 Apr 2018 04:33:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</link>
	<title><![CDATA[SciLifeLab tutorial for bioinformatics analysis !]]></title>
	<description><![CDATA[<p>SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.</p>
<h2 id="courses">Courses</h2>
<p><a href="http://uppnex.se/twiki/bin/view/Courses/">Old courses (2012-2014)</a></p>
<h3 id="metagenomics-workshop">Metagenomics Workshop</h3>
<p><a href="https://scilifelab.github.io/courses/Metagenomics/1511/">2015 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1711/">2017 November - Uppsala</a></p>
<h3 id="introduction-to-bioinformatics-using-ngs-data">Introduction to Bioinformatics Using NGS Data</h3>
<p><a href="https://scilifelab.github.io/courses/ngsintro/1502/">2015 February - Uppsala</a>&nbsp;<br><a href="https://scilifelab.github.io/courses/ngsintro/1505/">2015 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1509/">2015 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1511/">2015 November - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1601/">2016 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1604/">2016 April - Link&ouml;ping</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1609/">2016 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1611/">2016 November - Ume&aring;</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1701/">2017 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1705/">2017 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1709/">2017 September - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1802/">2018 February - Uppsala</a></p>
<h3 id="introduction-to-genome-annotation">Introduction to Genome Annotation</h3>
<p><a href="https://scilifelab.github.io/courses/annotation/2015/">2015 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2016/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2017/">2017 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2018/">2018 May - Uppsala</a></p>
<h3 id="de-novo-genome-assembly">De Novo Genome Assembly</h3>
<p><a href="https://scilifelab.github.io/courses/assembly/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/assembly/2017-11-15/">2017 November - Uppsala</a></p>
<h3 id="rna-seq-course">RNA-seq course</h3>
<p><a href="https://scilifelab.github.io/courses/rnaseq/1510/">2015 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1604/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1610/">2016 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1703/">2017 March - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/labs">RNAseq tutorials</a></p>
<h3 id="r-programming-foundations-for-life-scientists">R Programming Foundations for Life Scientists</h3>
<p><a href="https://scilifelab.github.io/courses/r_programming/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/r_programming/1703/">2017 Mars - Uppsala</a></p>
<h3 id="single-cell-rna-sequencing-analysis">Single cell RNA sequencing analysis</h3>
<p><a href="https://scilifelab.github.io/courses/scrnaseq/1710/">2017 October - Uppsala</a></p><p>Address of the bookmark: <a href="https://scilifelab.github.io/courses/" rel="nofollow">https://scilifelab.github.io/courses/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</guid>
	<pubDate>Fri, 08 Jun 2018 09:31:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36880/jvarkit-java-utilities-for-bioinformatics</link>
	<title><![CDATA[Jvarkit : Java utilities for Bioinformatics]]></title>
	<description><![CDATA[Collection of Java tool kits for bioinformatics works:

Jvarkit : Java utilities for Bioinformatics<p>Address of the bookmark: <a href="http://lindenb.github.io/jvarkit/" rel="nofollow">http://lindenb.github.io/jvarkit/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/37905/phased-human-genome-assembly</guid>
	<pubDate>Mon, 08 Oct 2018 09:10:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/37905/phased-human-genome-assembly</link>
	<title><![CDATA[Phased Human Genome Assembly !]]></title>
	<description><![CDATA[<p>The new publicly available assembly (PacBio&nbsp;<a href="https://www.globenewswire.com/Tracker?data=IM2cKfZgtHafORdb9VSstujBjyW-aIzFILCtXNAkcY_yqVmxdjvG01R_FZQC7zLxs-alqquXwsW6MG98G9-g-ym8Nue2pmUZMtkIg3FIat2mYbJ-z2Ra367GlinbO13x" target="_blank" title=""><span style="text-decoration: underline;">HG00733</span></a>) has the fewest gaps of any human genome assembly, with more than half of the genome contained in gapless sequence at least 27 Mb long. The primary contig assembly is 2.89 Gb long and consists of 865 contigs that were assembled with PacBio data generated with the company&rsquo;s Sequel<span>&reg;</span>&nbsp;System. Using the&nbsp;<a href="https://www.globenewswire.com/Tracker?data=jOa6mE1Y5r8VbU1CaCgx1A0HsoVzJ7waxOiDKgvmKL6cwJq_eH4nWrGj2vLkNpxHl1-5CH4htDB4113PXT8WU60hvHQ-KKpvAwQwveEGvz3N4d0q7QHSa_X97LW8_9xEiYqfsc4d24ca-IpVYZsf7Ue-XL7fSIIZw_EHK-F96t1aaQNRcD-z1PP5qvlZbVwX" target="_blank" title=""><span style="text-decoration: underline;">FALCON-Unzip assembler</span></a>, maternal and paternal haplotypes were resolved over more than 80% of the genome. Maternal and paternal haplotype blocks were then further phased using Hi-C technology and the&nbsp;<a href="https://www.globenewswire.com/Tracker?data=jOa6mE1Y5r8VbU1CaCgx1IrQmRcKvNQm83FLTqQE6OGzutM-fEggnm4Z-nsniK0D_YmDKS_UKWE0NHtHbgvbL973Y2-9NhrWhYKizXQ4lpiTvlqPf1UZdjqVs7BDjISgDnovv8foYw8es8jQzAg5Xfq1CH36NOnWQgA_X04XSvyEEEj0q801Im6cV5M5K4eL15vb_ZgUayccOvDY_fc6lxxPAAAyA4h16-zUN44Y81KdujciCrJrv5xynMIXEjRsaIKCf6eCX_Q1j_uZlN5TD0MVr6HulTYG8lGgyL0x-eQ=" target="_blank" title=""><span style="text-decoration: underline;">FALCON-Phase method</span></a>developed in collaboration with Phase Genomics. The genome was then&nbsp;<em>de novo</em>&nbsp;scaffolded using Phase Genomics&rsquo;&nbsp;<a href="https://www.globenewswire.com/Tracker?data=4wcqEWHJpCHRJARQkC0oVkYT9htT14iVebujxcW1nMpAjmigHGQ46ObCGetRfyaZm1ADIHaV1-30B9izTAhjJ-efhFlxorUxs08kdV-9AAzQyuHJ9S7wxnRRnyegsTZd" target="_blank" title=""><span style="text-decoration: underline;">Proximo Hi-C platform</span></a>, resulting in the first chromosome-scale diploid assembly of a single individual accomplished with only two technologies. More specific details about the assembly are included on the PacBio blog.</p><p>The data are available using NCBI accession IDs: BioProject: (<a href="https://www.globenewswire.com/Tracker?data=YZtCuhY2wu5H0yIso9jtUufPXbwyHh1QOZ1jBggGpK5NtXaU_JGC9X39F3uHZ96uVmu6hW5OB2Qq805hUEW2OhSNCm630yFiEF6_nsAwYB0=" target="_blank" title=""><span style="text-decoration: underline;">PRJNA483067</span></a>), assembly: [<a href="https://www.globenewswire.com/Tracker?data=CEXZ7E56JOsRgfH4Wq3r5LVbv4QH_UIekV9idYBys9l8K7pFft824jmYWNzJqK7lQ9fMbaAtbURpm8gM7zqUbpPUrydFwrkJGGtG-NBHctjyjddiFY-p06xZPm2mHXE2" target="_blank" title=""><span style="text-decoration: underline;">RBJD00000000</span></a>] and sequence data (<a href="https://www.globenewswire.com/Tracker?data=pELP2RpqTqTRaPF9yN1N7GZYlQmTxpY0aW-B8xaNw6iyD-Lylw7X3UzMDK3YS4AIYgLtD13em2XsbzOwKhXuNbI4Ks6-LSyXl1_yVdFoB0U=" target="_blank" title=""><span style="text-decoration: underline;">SRP155659</span></a>).</p><p><span>Additional Resources</span></p><ul>
<li><a href="http://globenewswire.com/Tracker?data=zXpdadphSgIAIEWeq46yRPm5-TU0H7wTkL48ue4I9GsaHd5mJyMb9PgXgAsElREkLOCOdWdJ8uW9DHB-LyQ7xhzbd97Qis6CuAlqD0ubGgY%3D" target="_blank" title=""><span style="text-decoration: underline;">Interactive map</span></a>&nbsp;showcasing global initiatives underway to generate reference-quality human genome assemblies for diverse populations</li>
<li><a href="http://globenewswire.com/Tracker?data=EQ8NIaaa8k1Nw1MPRJYIHYrqgsDy92kU8W0siJdGQhq5IJ0dcb890PFFm-C1SrAlFf0xkxUVRxZefFK5ebhoIzmS-6OjR1G9sTxOkCOwRHCAZWmHL-e7uGSuZYcw1VsDp8AeDWO0RwcepMMB6hAoR6BBCJDiJVVZtdFlWBn2uxs%3D" target="_blank" title=""><span style="text-decoration: underline;">BioReport Podcast</span></a>&nbsp;on the value of ethnic-specific reference genomes</li>
<li><em>Nature Reviews Genetics</em>&nbsp;paper from NHGRI:&nbsp;<a href="http://globenewswire.com/Tracker?data=dffu-wPD_JX1_KVeCA6VFy-kP1tlAUbn7d85saXD59dnnJfT2BE3N_Rbm6kT4BvifA_XEs49ioa75cy4HyFi90RA_LRa2QFF6Y4mr-dcoMucljZw0K4JNDZuwWkWPE51cVC2Lqq3E3C1aZ8un6Bq3i-OO_NiVH0hh23hUw4wC84%3D" target="_blank" title=""><span style="text-decoration: underline;">Prioritizing&nbsp;diversity&nbsp;in human genomics research</span></a></li>
<li>Article in&nbsp;<em>The Journal of Precision Medicine</em>: &ldquo;<a href="http://globenewswire.com/Tracker?data=yokLqO2TCBLCdj6uZl-GYbqcGMWBerBYjSPrLMumNrWF2p5XlXq9yl5p-1b5xx3Ckfn5ZjQWkdhxLttbiNae5gccUCP-9RWPUqvTu9MuU9zgJ1c8e14lAladCuEOiVZ2oVRiqssPtLu9hgQWw4ad5EUxZemevsHE4BHC6IiFmMZ6DS6ApwZu-IonFgCFBIcjWOpitQthDASosfaqkMi9LsKgLU9F0WGVJDDOzHXpddhjfCUdEEJ7xC1p8uh9TSiCZgZV6XPlUJSe8n0C_9TtOw%3D%3D" target="_blank" title=""><span style="text-decoration: underline;">Minority Report &ndash; Ethnic Diversity and the Real Promise for Precision Medicine</span></a>&rdquo;</li>
<li>Article&nbsp;in&nbsp;<em>Bio-IT World</em>: &ldquo;<a href="http://globenewswire.com/Tracker?data=rLp1pKetctTPitNEnRjOVDZ3Cvw3FUdL6_ybXncvhjR4ksOrX3y6HUK8WtLlKHT7XZzq_woUjZ-uw20YNvsP0GZAmy5lVqETt27oBLi02wFtTH_6ubELIHtBu8vfVyKnqKp-YhosFG5K7y0RUtzmNjOAlCYPAeVXabn2a2AiSePxUXA_tSy_g79hjYm63x9dPN9oFQGYedOsyHD_ls8DKw%3D%3D" target="_blank" title=""><span style="text-decoration: underline;">Genomic Data Standards Are a Necessity</span></a>&rdquo;</li>
<li>NHGRI Project Award:&nbsp;<a href="http://globenewswire.com/Tracker?data=FbqTEeRffJ88lFryYX6MiOefXvIXFdZDAyW4nrFoYNHaJyMEYIcb7I4BIcEQmxzsKOjrlf9F8irfRJeJLOqG8KFsl-kvkhakUkg3BfYdKGnpLzKYyWbUFR0aKMeEXirHBi7oDLEUSDO45qxANwxyee-pqZXfzAIwF1Wcuaf7EIzNqRqmBUJ3TyNyI05lwAo9gDKmApMnJo5VxPj5P_6rY8lisuv1PNSAh_kJPOuhVBk%3D" target="_blank" title=""><span style="text-decoration: underline;">High Quality Human and Non-Human Primate Genome Assemblies</span></a></li>
</ul><p>More details are available on the PacBio website:</p><ul>
<li>Blog post:&nbsp;<a href="http://globenewswire.com/Tracker?data=ycj-ujgsKzVyljNa11buVmIS5tk9B733VsFZEw77nBXo-IkBvcoG16dN9vuTiY3nm2G5dJZS5Iva3w_znrEtJVDuU8cVlFpozY2ibinKwrMGxkXZVSqW8_uD8fbySRjM5Q_cjuPU22ARFSSLCc9vHJx9WHnb9Rza-qPbuWgewa0rWWStq2fQY5mLpeaQf5fcDJnyQkvDAMI3fauXdzyThg%3D%3D" target="_blank" title=""><span style="text-decoration: underline;">Data Release: Highest-Quality, Most Contiguous Individual Human Genome Assembly to Date</span></a></li>
<li>Blog post:&nbsp;<a href="http://globenewswire.com/Tracker?data=GlZZ9nyp5mDSjJPPfhVD1-dZ_W2l8s0eAUox3TQs949zyGjzO7dx9xodyvyqerdqPC-G3ZhdPEs9xNhJwflrwgHPYQL3kTofprKHBBq3O4gn9E75YUBweJw9b6tTE89sMLUQzF-vRNNDjero3mibm_uG-fSHoYBTm2ZlyEmwzZ5E9tXVd5_RjG0Xnej2E0scA0SncEItAF6Q7vdOydTV_Yr9yYT2TmKY5jtyAt6ZrNGn3McqfV9mMRkR-8dYJLqrQln9JiEkWTwUae6Blj56HyjyXKl6Dfa_CyNuy4r-EWU%3D" target="_blank" title=""><span style="text-decoration: underline;">For Reference-Grade Human Genome Assemblies, SMRT Sequencing Yields Optimal Results</span></a></li>
<li>Webinar: &nbsp;<a href="http://globenewswire.com/Tracker?data=xlnfDwMNLGZZvtexJYsUgMe-DV8HNrYx2QqjwIjfj40dToVtqrBi-gvhknHZmIe8GV_3WU3_9LIlP6GzG3ZoajnDIpwECzdMV5Vyy8Ast4Y2AiHJckf7rBhZVEU4_mV4JB0k3I9XjN2jHK8Cp5uBxyIWWqPdI6qBBdCYYhYLXUTkKpaZEV98oCfC5ET2Q7OSwUM7NieKa75yzMHwaPEYwg%3D%3D" target="_blank" title=""><span style="text-decoration: underline;">Assembling High-Quality Human Reference Genomes for Global Populations</span></a></li>
<li>FALCON-Phase&nbsp;<a href="http://globenewswire.com/Tracker?data=4Z9LDdRq3w2zYFQXEFGmz6u-Vrbfh96syfzrQMKhegLRo2PUvk7s3Xz_y1o--NuTLoCQMrHsqOEBUHIL1IPeOmhyf6Eqwdp8dv8xYo9gSVI%3D" target="_blank" title=""><span style="text-decoration: underline;">press release</span></a>&nbsp;and article&nbsp;<a href="http://globenewswire.com/Tracker?data=4Z9LDdRq3w2zYFQXEFGmz9Ts_IJqHWWrKd33x_ldJEU9mSKXpcVTTi9ioY0kVqrbrXHeCKDf4TdPnAoPJaGBK3YeZtYp-nXZacgyPESZ1XboSUZEJ9rIhDyW7bTLL5HN" target="_blank" title=""><span style="text-decoration: underline;">preprint</span></a></li>
<li>PacBio research focus webpage about&nbsp;<a href="http://globenewswire.com/Tracker?data=E-zzUkw4N01KR4muPun47qg4HX8ToDvLS4sX953hLM2wRyQZ2upkLR4WidyXTFDRLWQORpqxnkbD-CNzsOJyIfH8mJPbrLwRf04J4yjuNdem-Fulc8QIT3OCi4wx5LpqgC2ymLE0rYX5UOpbFPBgvA%3D%3D" target="_blank" title=""><span style="text-decoration: underline;">Human Population Genetics</span></a></li>
</ul><p>&nbsp;Ref:&nbsp;https://stockguru.com/2018/10/08/pacific-biosciences-releases-highest-quality-most-contiguous-individual-human-genome-assembly-to-date/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</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>

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