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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2759?offset=90</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</guid>
	<pubDate>Tue, 10 May 2016 07:46:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</link>
	<title><![CDATA[BUSCO: Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs]]></title>
	<description><![CDATA[<ul>
<li><span>High-throughput genomics has revolutionized biological research, however, while the number of sequenced genomes grows by the day, quality assessment of the resulting assembled sequences remains complicated and mostly limited to technical measures like N50.&nbsp;</span></li>
<li></li>
<li><span>BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from&nbsp;</span><a href="http://orthodb.org/">OrthoDB</a><span>.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments are implemented in open-source software, with comprehensive lineage-specific sets of Benchmarking Universal Single-Copy Orthologs for arthropods, vertebrates, metazoans, fungi, eukaryotes, and bacteria.&nbsp;</span></li>
<li></li>
<li><span>These conserved orthologs are ideal candidates for large-scale phylogenomics studies, and the annotated BUSCO gene models built during genome assessments provide a comprehensive gene predictor training set for use as part of genome annotation pipelines.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments offer intuitive metrics, based on evolutionarily informed expectations of gene content from hundreds of species, to gauge completeness of rapidly accumulating genomic data and satisfy an Iberian's quest for quality - "Busco calidad/qualidade".</span></li>
</ul><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</guid>
	<pubDate>Tue, 26 Apr 2016 11:38:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27090/canu-assembling-large-genomes-with-single-molecule-sequencing-and-locality-sensitive-hashing</link>
	<title><![CDATA[CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.]]></title>
	<description><![CDATA[<p>Canu is a fork of the&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php?title=Main_Page" title="Celera Assembler">Celera Assembler</a>&nbsp;designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.</p>
<p>Canu is a hierachical assembly pipeline which runs in four steps:</p>
<ul>
<li>Detect overlaps in high-noise sequences using&nbsp;<a href="https://github.com/marbl/MHAP" title="MHAP">MHAP</a></li>
<li>Generate corrected sequence consensus</li>
<li>Trim corrected sequences</li>
<li>Assemble trimmed corrected sequences</li>
</ul>
<p>Read the&nbsp;<a href="http://canu.readthedocs.org/" title="docs">documentation</a></p>
<p>New release https://github.com/marbl/canu/releases</p><p>Address of the bookmark: <a href="https://github.com/marbl/canu" rel="nofollow">https://github.com/marbl/canu</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes</guid>
	<pubDate>Wed, 27 Apr 2016 11:07:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes</link>
	<title><![CDATA[RASTtk : algorithm for building custom annotation pipelines and annotating batches of genomes]]></title>
	<description><![CDATA[<p>The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.</p>
<p>More at http://www.nature.com/articles/srep08365</p><p>Address of the bookmark: <a href="http://rast.nmpdr.org/" rel="nofollow">http://rast.nmpdr.org/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</guid>
	<pubDate>Tue, 03 May 2016 05:31:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</link>
	<title><![CDATA[Painless package development for R]]></title>
	<description><![CDATA[<p>Devtools makes package development a breeze: it works with R&rsquo;s existing conventions for code structure, adding efficient tools to support the cycle of package development. With devtools, developing a package becomes so easy that it will be your default layout whenever you&rsquo;re writing a significant amount of code.</p>
<p>Before you get started be sure to check out:</p>
<ul>
<li><a href="https://groups.google.com/forum/#%21forum/rdevtools" title="Google devtools Group">devtools Google Group &ndash;&nbsp;https://groups.google.com/forum/#!forum/rdevtools</a></li>
<li><a href="http://adv-r.had.co.nz/" title="Hadley W Online Book">book on &ldquo;Advanced R programming&rdquo; &ndash;&nbsp;http://adv-r.had.co.nz/</a></li>
<li><a href="https://github.com/hadley/devtools" title="devtools GitHub">GitHub repository &ndash;&nbsp;https://github.com/hadley/devtools</a></li>
</ul>
<h3 id="getting_started">&nbsp;</h3><p>Address of the bookmark: <a href="https://www.rstudio.com/products/rpackages/devtools/" rel="nofollow">https://www.rstudio.com/products/rpackages/devtools/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27238/slurm</guid>
	<pubDate>Wed, 04 May 2016 05:13:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27238/slurm</link>
	<title><![CDATA[SLURM]]></title>
	<description><![CDATA[<p><a href="http://www.schedmd.com/">SLURM</a> workload manager software, a free open-source workload manager designed specifically to satisfy the demanding needs of high performance computing.</p>
<p>This page is a <em>HOWTO</em> guide for setting up a <a href="http://www.schedmd.com/">SLURM</a> installation, currently focused on a CentOS 7 Linux OS. Please send feedback to Ole.H.Nielsen /at/ fysik.dtu.dk.</p>
<p>See the <a href="http://www.schedmd.com/">SLURM</a> homepage (also <a href="https://computing.llnl.gov/linux/slurm/">https://computing.llnl.gov/linux/slurm/</a>).</p><p>Address of the bookmark: <a href="https://wiki.fysik.dtu.dk/niflheim/SLURM" rel="nofollow">https://wiki.fysik.dtu.dk/niflheim/SLURM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/27290/scientists-post-at-monsanto</guid>
  <pubDate>Wed, 11 May 2016 07:58:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Scientists post at Monsanto]]></title>
  <description><![CDATA[
<p>Sustainable agriculture is at the core of Monsanto. We develop technologies that enable farmers to produce more crops while conserving natural resources. Monsanto scientists are conducting research and development (R&amp;D) to revolutionize plant breeding and biotechnology.</p>

<p>Monsanto is seeking a very talented Genomics Scientistto become an integral member of our Global Pipeline Analytics team with a focus on quantitative genetics. The ideal candidate will have familiarity with modeling and analysis of genetic data sets using a variety of statistical techniques.</p>

<p>Major Responsibilities:<br />- Provide guidance on experimental design for genomic-related experiments<br />- Familiarity with analysis of the following methods: GWS, QTL, eQTL, RNA-Seq<br />- Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.<br />- Ensure timely delivery and clear communication of results<br />- Develop strong and successful collaborations among various Monsanto enabling teams.</p>

<p>Required Skills:</p>

<p>- PhD degree in Statistics, Biostatistics, Statistical Genetics, Quantitative Genetics, Breeding, Bioinformatics or a related field with 2 years of experience<br />- Working knowledge and experience with one of the following quantitative languages:R, Python, Perl, SAS<br />- Background in Windows and Linux operating systems<br />- Very strong problem solving skills will be required to work well as a member of a dynamic team<br />- Strong verbal and written communication skills.<br />- Demonstrated ability to deliver timely results and be results oriented.<br />- Extensive knowledge of quantitative genetics and experimental design.&nbsp;<br />- Demonstrated track record of solving challenging and complex problems.</p>

<p>Desired Skills/Experience:</p>

<p>- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines.<br />- Experience in agronomy and/or plant breeding in vegetables or row crops.</p>

<p>Please apply to<br />https://jobs.monsanto.com/job/st-louis/genomics-scientist/769/2081771</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/27318/sample-binc-question-paper-2016-part2</guid>
	<pubDate>Fri, 13 May 2016 03:42:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/27318/sample-binc-question-paper-2016-part2</link>
	<title><![CDATA[Sample BINC question paper 2016 - part2]]></title>
	<description><![CDATA[<p>Download the sample question paper for BINC 2016 - paer II</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/27318" length="52024" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</guid>
	<pubDate>Fri, 20 May 2016 19:08:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27438/hagfish-assess-an-assembly-through-creative-use-of-coverage-plots</link>
	<title><![CDATA[Hagfish - assess an assembly through creative use of coverage plots]]></title>
	<description><![CDATA[<p>Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of&nbsp;<em style="font-size: 12.8px;">de novo</em>&nbsp;genome assembly or identification of structural variation in a genome re-sequencing experiment.</p>
<p>Hagfish requires a reference sequence and a&nbsp;<span>paired end</span>&nbsp;re-sequencing data set. Hagfish has more power the larger the insert size of the paired end library is.</p>
<p>Quick links:&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Install">Installation</a>,<a href="https://github.com/mfiers/hagfish/wiki/Operation">Operation</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/ReadMappers">Read mappers</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Scripts">Hagfish scripts</a>,&nbsp;<a href="https://github.com/mfiers/hagfish/wiki/Plots">Hagfish plots</a></p><p>Address of the bookmark: <a href="https://github.com/mfiers/hagfish" rel="nofollow">https://github.com/mfiers/hagfish</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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