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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/22053?offset=980</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</guid>
	<pubDate>Tue, 10 May 2016 08:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</link>
	<title><![CDATA[segemehl]]></title>
	<description><![CDATA[<p><span>segemehl is a software to map short sequencer reads to reference genomes. Unlike other methods, segemehl is able to detect not only mismatches but also insertions and deletions. Furthermore, segemehl is not limited to a specific read length and is able to map&nbsp;primer- or polyadenylation contaminated reads correctly.&nbsp; segemehl implements a matching strategy based on enhanced suffix arrays (ESA).&nbsp;</span></p>
<p><span>More at&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/</span></p>
<p><span>Manual&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/segemehl_manual_0_1_7.pdf</span></p><p>Address of the bookmark: <a href="http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html" rel="nofollow">http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</guid>
	<pubDate>Tue, 03 May 2016 16:43:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</link>
	<title><![CDATA[Supposedly Educational R]]></title>
	<description><![CDATA[<p>R 3.3.0 (codename &ldquo;Supposedly Educational&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-3-0-is-released-td4720368.html" target="_blank">released today</a>.&nbsp;You can get the latest binaries version <strong><a href="http://cran.rstudio.com/" target="_blank">from here</a>.</strong>&nbsp;(or the .tar.gz&nbsp;<strong>source</strong> code from <a href="http://cran.r-project.org/src/base/R-3/R-3.3.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><p>If you are using <strong>Windows&nbsp;</strong>you can easily upgrade to the latest version of R using <a href="http://cran.r-project.org/web/packages/installr/" target="_blank">the installr package</a>. Simply run the following code in Rgui:</p><div><table width="710">
<tbody>
<tr id="p613882">
<td id="p61388code2">
<pre><span style="color: #0000ff; font-weight: bold;">install.<span>packages</span></span><span style="color: #080;">(</span><span style="color: #ff0000;">"installr"</span><span style="color: #080;">)</span> <span style="color: #228b22;"># install </span>
setInternet2<span style="color: #080;">(</span>TRUE<span style="color: #080;">)</span>
installr<span style="color: #080;">::</span><span>updateR</span><span style="color: #080;">(</span><span style="color: #080;">)</span> <span style="color: #228b22;"># updating R.</span></pre>
</td>
</tr>
</tbody>
</table></div><p><span>Running &ldquo;updateR()&rdquo; will detect if there is a new R version available, and if so it will download+install it (etc.). There is also <a href="http://www.r-statistics.com/2015/06/a-step-by-step-screenshots-tutorial-for-upgrading-r-on-windows/" target="_blank">a&nbsp;step by step tutorial (with screenshots) on how to upgrade R on Windows, using the <em>installr</em></a>&nbsp;package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).</span></p><p><em>I try to keep the <a href="https://github.com/talgalili/installr" target="_blank">installr</a> package updated and useful, so if you have any suggestions or remarks on the package &ndash; you are invited to <a href="https://github.com/talgalili/installr/issues" target="_blank">open an issue in the github page</a>.</em></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<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/bookmarks/view/27323/cutadapt</guid>
	<pubDate>Fri, 13 May 2016 04:54:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</link>
	<title><![CDATA[cutadapt]]></title>
	<description><![CDATA[<p>Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.</p>
<p>Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3&rsquo; sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don&rsquo;t want them to be in your reads.</p>
<p>Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.</p>
<p>Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.</p>
<p>If you use cutadapt, please cite <a href="http://dx.doi.org/10.14806/ej.17.1.200">DOI:10.14806/ej.17.1.200</a> .</p><p>Address of the bookmark: <a href="https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart" rel="nofollow">https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</guid>
	<pubDate>Tue, 17 May 2016 01:43:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27344/orffinder-with-smart-blast</link>
	<title><![CDATA[ORFfinder with smart BLAST]]></title>
	<description><![CDATA[<p><span>ORF Finder</span></p><p><span><a href="http://www.ncbi.nlm.nih.gov/orffinder">ORFfinder</a><span>&nbsp;is a graphical analysis tool for finding open reading frames (ORFs). We&rsquo;ve been working on a few updates, and we&rsquo;d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.</span></span></p><p>Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)</p><p>Select one or a group of ORFs and BLAST several databases at once, and use the newly developed&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/smartblast/">SmartBLAST</a>&nbsp;to verify protein names.&nbsp;Looking for the traditional results from&nbsp;<a href="http://blast.ncbi.nlm.nih.gov/Blast.cgi">BLAST</a>? They&rsquo;re there too.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</guid>
	<pubDate>Sat, 21 May 2016 22:50:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27465/stand-alone-programs-for-bioinformatician</link>
	<title><![CDATA[Stand-alone programs for Bioinformatician]]></title>
	<description><![CDATA[<p>This directory contains applications for stand-alone use, built specifically for a Linux 64-bit machine.</p>
<p>For help on the bigBed and bigWig applications see:<br>http://genome.ucsc.edu/goldenPath/help/bigBed.html<br>http://genome.ucsc.edu/goldenPath/help/bigWig.html</p>
<p>View the file 'FOOTER' to see the usage statement for each of the applications.</p><p>Address of the bookmark: <a href="http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/" rel="nofollow">http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</guid>
	<pubDate>Thu, 02 Jun 2016 11:11:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27685/biodbnet</link>
	<title><![CDATA[BioDBnet]]></title>
	<description><![CDATA[<p><span>Database to Database Conversions</span> </p>
<p>db2db allows for conversions of identifiers from one database to other database identifiers or annotations. To use db2db select the input type of your data, changing the input type automatically changes the output options to the ones specific for the input selected. Then select one or more output types and add your identifiers in the ID list box. Set the remove duplicate values to 'No' if you do not want duplicates to be removed. Clicking on submit then returns a table of your inputs matched against all the outputs selected in the exact order as entered. Results can be limited to a particular taxon by entering it's <a href="https://biodbnet-abcc.ncifcrf.gov/tools/orgTaxon.php">Taxon ID</a>. The performance will vary widely depending on the number of outputs and the options selected. Conversions to a single output with the default options should complete in a few seconds</p><p>Address of the bookmark: <a href="https://biodbnet-abcc.ncifcrf.gov/db/db2db.php" rel="nofollow">https://biodbnet-abcc.ncifcrf.gov/db/db2db.php</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27806/blobology</guid>
	<pubDate>Mon, 13 Jun 2016 10:18:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27806/blobology</link>
	<title><![CDATA[Blobology]]></title>
	<description><![CDATA[<p><span>Tools for making blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step</span></p>
<p>Blaxter Lab, Institute of Evolutionary Biology, University of Edinburgh</p>
<p><span>Goal</span>: To create blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step.</p>
<p>This repository accompanies the paper:<br><span>Blobology: exploring raw genome data for contaminants, symbionts and parasites using taxon-annotated GC-coverage plots.</span>&nbsp;<em>Sujai Kumar, Martin Jones, Georgios Koutsovoulos, Michael Clarke, Mark Blaxter</em><br>(submitted 2013-10-01 to&nbsp;<em>Frontiers in Bioinformatics and Computational Biology special issue : Quality assessment and control of high-throughput sequencing data</em>).</p>
<p>It contains bash/perl/R scripts for running the analysis presented in the paper to create a preliminary assembly, and to create and collate GC content, read coverage and taxon annotation for the preliminary assembly, which can be visualised, such as Figure 2a from the paper showing TAGC plots/blobplots for&nbsp;<em>Caenorhabditis</em>&nbsp;sp. 5:&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/blaxterlab/blobology" rel="nofollow">https://github.com/blaxterlab/blobology</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27839/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads-such-those-produced-by-pacific-biosciences-sequencing-machines</guid>
	<pubDate>Wed, 15 Jun 2016 17:18:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27839/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads-such-those-produced-by-pacific-biosciences-sequencing-machines</link>
	<title><![CDATA[LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines]]></title>
	<description><![CDATA[<p>LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.</p>
<p>Publication:</p>
<ul>
<li>L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.</li>
</ul>
<p>Download:</p>
<ul>
<li><a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/LoRMA-0.3.tar.gz">LoRMA 0.3 source files</a></li>
<li><a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/README.txt">README</a></li>
</ul><p>Address of the bookmark: <a href="https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/" rel="nofollow">https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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