<?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/37561?offset=120</link>
	<atom:link href="https://bioinformaticsonline.com/related/37561?offset=120" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/36952/getoptspl-file</guid>
	<pubDate>Fri, 15 Jun 2018 04:43:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/36952/getoptspl-file</link>
	<title><![CDATA[getopts.pl file]]></title>
	<description><![CDATA[
<p>SSPACE_longread complain for getopts.pl file. </p>

<p>To resolve this, download and have in SSPACED-Longreads folder. </p>

<p>Cheers :)</p>
]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/36952" length="942" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34418/spades-hybrid-genome-assembly</guid>
	<pubDate>Mon, 27 Nov 2017 08:05:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34418/spades-hybrid-genome-assembly</link>
	<title><![CDATA[SPAdes hybrid genome assembly]]></title>
	<description><![CDATA[<p>When you have both Illumina and Nanopore data, then SPAdes remains a good option for hybrid assembly - SPAdes was used to produce the&nbsp;<a href="https://gigascience.biomedcentral.com/articles/10.1186/s13742-015-0101-6">B fragilis assembly</a>&nbsp;by Mick Watson&rsquo;s group.</p><p>Again, running spades.py will show you the options:</p><div><pre><code>spades.py
</code></pre></div><p>This produces:</p><div><pre><code>SPAdes genome assembler v3.10.1

Usage: /usr/local/SPAdes-3.10.1-Linux/bin/spades.py [options] -o &lt;output_dir&gt;

Basic options:
-o      &lt;output_dir&gt;    directory to store all the resulting files (required)
--sc                    this flag is required for MDA (single-cell) data
--meta                  this flag is required for metagenomic sample data
--rna                   this flag is required for RNA-Seq data
--plasmid               runs plasmidSPAdes pipeline for plasmid detection
--iontorrent            this flag is required for IonTorrent data
--test                  runs SPAdes on toy dataset
-h/--help               prints this usage message
-v/--version            prints version

Input data:
--12    &lt;filename&gt;      file with interlaced forward and reverse paired-end reads
-1      &lt;filename&gt;      file with forward paired-end reads
-2      &lt;filename&gt;      file with reverse paired-end reads
-s      &lt;filename&gt;      file with unpaired reads
--pe&lt;#&gt;-12      &lt;filename&gt;      file with interlaced reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-1       &lt;filename&gt;      file with forward reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-2       &lt;filename&gt;      file with reverse reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-s       &lt;filename&gt;      file with unpaired reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--pe&lt;#&gt;-&lt;or&gt;    orientation of reads for paired-end library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--s&lt;#&gt;          &lt;filename&gt;      file with unpaired reads for single reads library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-12      &lt;filename&gt;      file with interlaced reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-1       &lt;filename&gt;      file with forward reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-2       &lt;filename&gt;      file with reverse reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-s       &lt;filename&gt;      file with unpaired reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--mp&lt;#&gt;-&lt;or&gt;    orientation of reads for mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--hqmp&lt;#&gt;-12    &lt;filename&gt;      file with interlaced reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-1     &lt;filename&gt;      file with forward reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-2     &lt;filename&gt;      file with reverse reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-s     &lt;filename&gt;      file with unpaired reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--hqmp&lt;#&gt;-&lt;or&gt;  orientation of reads for high-quality mate-pair library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9; &lt;or&gt; = fr, rf, ff)
--nxmate&lt;#&gt;-1   &lt;filename&gt;      file with forward reads for Lucigen NxMate library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--nxmate&lt;#&gt;-2   &lt;filename&gt;      file with reverse reads for Lucigen NxMate library number &lt;#&gt; (&lt;#&gt; = 1,2,..,9)
--sanger        &lt;filename&gt;      file with Sanger reads
--pacbio        &lt;filename&gt;      file with PacBio reads
--nanopore      &lt;filename&gt;      file with Nanopore reads
--tslr  &lt;filename&gt;      file with TSLR-contigs
--trusted-contigs       &lt;filename&gt;      file with trusted contigs
--untrusted-contigs     &lt;filename&gt;      file with untrusted contigs

Pipeline options:
--only-error-correction runs only read error correction (without assembling)
--only-assembler        runs only assembling (without read error correction)
--careful               tries to reduce number of mismatches and short indels
--continue              continue run from the last available check-point
--restart-from  &lt;cp&gt;    restart run with updated options and from the specified check-point ('ec', 'as', 'k&lt;int&gt;', 'mc')
--disable-gzip-output   forces error correction not to compress the corrected reads
--disable-rr            disables repeat resolution stage of assembling

Advanced options:
--dataset       &lt;filename&gt;      file with dataset description in YAML format
-t/--threads    &lt;int&gt;           number of threads
                                [default: 16]
-m/--memory     &lt;int&gt;           RAM limit for SPAdes in Gb (terminates if exceeded)
                                [default: 250]
--tmp-dir       &lt;dirname&gt;       directory for temporary files
                                [default: &lt;output_dir&gt;/tmp]
-k              &lt;int,int,...&gt;   comma-separated list of k-mer sizes (must be odd and
                                less than 128) [default: 'auto']
--cov-cutoff    &lt;float&gt;         coverage cutoff value (a positive float number, or 'auto', or 'off') [default: 'off']
--phred-offset  &lt;33 or 64&gt;      PHRED quality offset in the input reads (33 or 64)
                                [default: auto-detect]
</code></pre></div><p>As you can see this is also a &ldquo;pipeline&rdquo; of tools that can be switched on or off. SPAdes takes quite a long time, so for the purposes of this practical, something like this may suffice:</p><div><pre><code>spades.py -t 4 <span>\</span>
          -m 32 <span>\</span>
          -k 31,51,71 <span>\</span>
          --only-assembler <span>\</span>
          -1 miseq.1.fastq -2 miseq.2.fastq <span>\</span>
          --nanopore minion.fastq <span>\</span>
          -o hybrid_assembly
</code></pre></div><p>In turn, these parameters mean</p><ul>
<li>use 4 threads</li>
<li>max memory is 32Gb</li>
<li>use 3 kmer values to build the de bruijn graph(s) - 31, 51 and 71</li>
<li>only run the assembler, not the correction algorithm (for speed)</li>
<li>read 1 and read 2 of the MiSeq data</li>
<li>the nanopore data</li>
<li>put the output in folder &ldquo;hybrid_assembly&rdquo;</li>
</ul>]]></description>
	<dc:creator>Jit</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/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</guid>
	<pubDate>Tue, 15 May 2018 04:44:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</link>
	<title><![CDATA[LAMSA: fast split read alignment with long approximate matches]]></title>
	<description><![CDATA[LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs).

LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants.

We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs.

LAMSA is open source and free for non-commercial use.

LAMSA is mainly designed by Bo Liu &amp; Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.<p>Address of the bookmark: <a href="https://github.com/hitbc/LAMSA" rel="nofollow">https://github.com/hitbc/LAMSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</guid>
	<pubDate>Mon, 30 Jul 2018 12:01:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37457/nanofilt-filtering-and-trimming-of-long-read-sequencing-data</link>
	<title><![CDATA[nanofilt: Filtering and trimming of long read sequencing data]]></title>
	<description><![CDATA[<p>Filtering on quality and/or read length, and optional trimming after passing filters.<br>Reads from stdin, writes to stdout.</p>
<p>Intended to be used:</p>
<ul>
<li>directly after fastq extraction</li>
<li>prior to mapping</li>
<li>in a stream between extraction and mapping</li>
</ul>
<p>https://github.com/wdecoster/nanofilt</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanofilt" rel="nofollow">https://github.com/wdecoster/nanofilt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</guid>
	<pubDate>Tue, 14 Jan 2020 06:47:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40531/shasta-long-read-assembler</link>
	<title><![CDATA[Shasta long read assembler]]></title>
	<description><![CDATA[<p>The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by&nbsp;<a href="https://nanoporetech.com/">Oxford Nanopore</a>&nbsp;flow cells.</p>
<p>Computational methods used by the Shasta assembler include:</p>
<ul>
<li>Using a&nbsp;<a href="https://en.wikipedia.org/wiki/Run-length_encoding">run-length</a>&nbsp;representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.</li>
<li>Using in some phases of the computation a representation of the read sequence based on&nbsp;<em>markers</em>, a fixed subset of short k-mers (k &asymp; 10).</li>
</ul>
<p>More at&nbsp;<a href="https://chanzuckerberg.github.io/shasta/index.html">https://chanzuckerberg.github.io/shasta/index.html</a></p><p>Address of the bookmark: <a href="https://github.com/chanzuckerberg/shasta" rel="nofollow">https://github.com/chanzuckerberg/shasta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34394/tulip-the-uncorrected-long-read-itegration-pipeline</guid>
	<pubDate>Thu, 23 Nov 2017 09:30:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34394/tulip-the-uncorrected-long-read-itegration-pipeline</link>
	<title><![CDATA[TULIP - The Uncorrected Long read Itegration Pipeline]]></title>
	<description><![CDATA[<p>#Running TULIP (The Uncorrected Long-read Integration Process), version 0.4 late 2016 (European eel)</p>
<p>TULIP currently consists of to Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.&nbsp;<br>Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures. Tulipbulb adds long read sequencing data to these.</p>
<p>&nbsp;</p>
<p>https://github.com/Generade-nl/TULIP</p><p>Address of the bookmark: <a href="https://github.com/Generade-nl/TULIP" rel="nofollow">https://github.com/Generade-nl/TULIP</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore</guid>
	<pubDate>Wed, 25 Apr 2018 07:30:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore</link>
	<title><![CDATA[NGMLR: long-read mapper designed to align PacBio or Oxford Nanopore]]></title>
	<description><![CDATA[<p><span>CoNvex Gap-cost alignMents for Long Reads (ngmlr) is a long-read mapper designed to sensitively align PacBilo or Oxford Nanopore to (large) reference genomes. It was designed to quickly and correctly align the reads, including those spanning (complex) structural variations. Ngmlr uses an SV aware k-mer search to find approximate mapping locations for a read and then a banded Smith-Waterman alignment algorithm to compute the final alignment. Ngmlr uses a convex gap cost model that penalizes gap extensions for longer gaps less than for shorter ones to compute precise alignments. The gap model allows ngmlr to account for both the sequencing error and real genomic variations at the same time and makes it especially effective at more precisely identifying the position of breakpoints stemming from structural variations. The k-mer search helps to detect and split reads that cannot be aligned linearly, enabling ngmlr to reliably align reads to a wide range of different structural variations including nested SVs (e.g. inversions flanked by deletions).</span></p><p>Address of the bookmark: <a href="https://github.com/philres/ngmlr" rel="nofollow">https://github.com/philres/ngmlr</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/file/view/19732/marine-bioinformatician</guid>
	<pubDate>Wed, 24 Dec 2014 05:17:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/19732/marine-bioinformatician</link>
	<title><![CDATA[Marine bioinformatician ;)]]></title>
	<description><![CDATA[<p>A marine bioinformatician at work. Sorry&nbsp;jealous biotechnologist, this is how we work.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/19732" length="35550" type="image/gif" />
</item>

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