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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30149?offset=90</link>
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	<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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</guid>
	<pubDate>Thu, 18 Aug 2016 04:05:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28835/a5-miseq</link>
	<title><![CDATA[A5-miseq]]></title>
	<description><![CDATA[<p><span><span>_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_. </span></span></p>
<p><span>Point to note:</span></p>
<p><span>There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ngopt/" rel="nofollow">https://sourceforge.net/projects/ngopt/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29235/valet</guid>
	<pubDate>Thu, 22 Sep 2016 04:27:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29235/valet</link>
	<title><![CDATA[valet]]></title>
	<description><![CDATA[<div>
<div>
<div>VALET is a pipeline for performing&nbsp;<em>de novo</em>&nbsp;validation of metagenomic assemblies. VALET checks a number of properties that should hold true for a correct assembly (e.g., mate-pairs are aligned at the correct distance from each other in the assembly, the depth of coverage is fairly uniform along contigs, etc.). The violations of these invariants are reported allowing one to pinpoint areas that were potentially mis-assembled, or to compare the quality of different assemblies. For comparing multiple assemblies of the same data-sets, VALET also reports an overall estimate of the likelihood a particular assembly is correct.</div>
</div>
</div>
<div>
<div>Home Page:&nbsp;</div>
<div>
<div><a href="https://github.com/jgluck/VALET">VALET code repository</a></div>
</div>
</div><p>Address of the bookmark: <a href="https://www.cbcb.umd.edu/software/valet" rel="nofollow">https://www.cbcb.umd.edu/software/valet</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</guid>
	<pubDate>Thu, 18 Aug 2016 09:57:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28842/repeatmodeler</link>
	<title><![CDATA[RepeatModeler]]></title>
	<description><![CDATA[<p><span>RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.</span></p><p>Address of the bookmark: <a href="http://www.repeatmasker.org/RepeatModeler.html" rel="nofollow">http://www.repeatmasker.org/RepeatModeler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29208/srf-bioinformatics-job-position-in-national-institute-of-plant-genome-research-nipgr</guid>
  <pubDate>Mon, 19 Sep 2016 05:43:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)]]></title>
  <description><![CDATA[
<p>SRF Bioinformatics job position in National Institute of Plant Genome Research (NIPGR)<br />Title : “Transcriptome and small RNA diversity analysis of developing seed contrasting rice varieties” <br />Qualification : Candidates having M.Sc./M.Tech. degree or equivalent (with minimum 60% marks) in Bioinformatics with a minimum of two years of post M.Sc./M.Tech research experience are eligible to apply.<br />No. of Post : 01<br />How to apply<br />Application should reach to Dr. Pinky Agarwal, Staff Scientist, National Institute of Plant Genome Research (NIPGR) Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi - 110067 on or before 30/09/2016</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28903/genevalidator-identify-problems-with-predicted-genes</guid>
	<pubDate>Fri, 26 Aug 2016 06:00:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28903/genevalidator-identify-problems-with-predicted-genes</link>
	<title><![CDATA[GeneValidator - Identify problems with predicted genes]]></title>
	<description><![CDATA[<p>GeneValidator helps in identifing problems with gene predictions and provide useful information extracted from analysing orthologs in BLAST databases. The results produced can be used by biocurators and researchers who need accurate gene predictions.</p>
<p>If you would like to use GeneValidator on a few sequences, see our online&nbsp;<a href="http://genevalidator.sbcs.qmul.ac.uk/">GeneValidator Web App</a>&nbsp;-<a href="http://genevalidator.sbcs.qmul.ac.uk/">http://genevalidator.sbcs.qmul.ac.uk</a>.</p>
<p>If you use GeneValidator in your work, please cite us as follows:</p>
<blockquote>
<p><a href="http://bioinformatics.oxfordjournals.org/content/early/2016/02/26/bioinformatics.btw015">Dragan M<span>&Dagger;</span>, Moghul MI<span>&Dagger;</span>, Priyam A, Bustos C &amp; Wurm Y. 2016. GeneValidator: identify problems with protein-coding gene predictions.&nbsp;<em>Bioinformatics</em>, doi: 10.1093/bioinformatics/btw015</a>.</p>
<p>&nbsp;</p>
</blockquote>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/wurmlab/genevalidator" rel="nofollow">https://github.com/wurmlab/genevalidator</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29004/r-chie</guid>
	<pubDate>Thu, 01 Sep 2016 11:47:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29004/r-chie</link>
	<title><![CDATA[R-chie]]></title>
	<description><![CDATA[<p><strong>R-chie</strong><span>&nbsp;allows you to make arc diagrams of RNA secondary structures, allowing for easy comparison and overlap of two structures, rank and display basepairs in colour and to also visualize corresponding multiple sequence alignments and co-variation information.</span><br><strong>R4RNA</strong><span>&nbsp;is the R package powering R-chie, available for&nbsp;</span><a href="http://www.e-rna.org/r-chie/download.cgi">download</a><span>&nbsp;and local use for more customized figures and scripting.</span></p>
<p>http://www.e-rna.org/r-chie/plot.cgi?eg=single</p><p>Address of the bookmark: <a href="http://www.e-rna.org/r-chie/plot.cgi?eg=single" rel="nofollow">http://www.e-rna.org/r-chie/plot.cgi?eg=single</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29108/assembly-tutorial-ppt</guid>
	<pubDate>Wed, 07 Sep 2016 03:12:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29108/assembly-tutorial-ppt</link>
	<title><![CDATA[Assembly tutorial PPT]]></title>
	<description><![CDATA[<p>Saved Cornell University assembly workshop PPT.</p><p>Reference:&nbsp;</p><p>http://cbsu.tc.cornell.edu/lab/doc/assembly_workshop_20150420_lecture1.pdf</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29108" length="1617402" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29142/opera-optimal-paired-end-read-assembler</guid>
	<pubDate>Fri, 09 Sep 2016 05:28:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29142/opera-optimal-paired-end-read-assembler</link>
	<title><![CDATA[OPERA : Optimal Paired-End Read Assembler]]></title>
	<description><![CDATA[<p>OPERA (Optimal Paired-End Read Assembler) is a sequence assembly program (<a href="http://en.wikipedia.org/wiki/Sequence_assembly">http://en.wikipedia.org/wiki/Sequence_assembly</a>). It uses information from paired-end/mate-pair/long reads to order and orient the intermediate contigs/scaffolds assembled in a genome assembly project, in a process known as Scaffolding. OPERA is based on an exact algorithm that is guaranteed to minimize the discordance of scaffolds with the information provided by the paired-end/mate-pair/long reads (for further details see Gao et al, 2011).</p>
<p>Note that since the original publication, we have made significant changes to OPERA (v1.0 onwards) including refinements to its basic algorithm (to reduce local errors, improve efficiency etc.) and incorporated features that are important for scaffolding large genomes (multi-library support, better repeat-handling etc.), in addition to other scalability and usability improvements (bam and gzip support, smaller memory footprint). We therefore encourage you to download and use our latest version: OPERA-LG. In our benchmarks, it has significantly improved corrected N50 and reduced the number of scaffolding errors. Furthermore, our latest release contains the wrapper script OPERA-long-read that enables scaffolding with long-reads from third-generation sequencing technologies (PacBio or Oxford Nanopore). The manuscript describing the new features and algorithms is available at&nbsp;<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0951-y">Genome Biology</a>. We look forward to getting your feedback to improve it further.</p><p>Address of the bookmark: <a href="https://sourceforge.net/p/operasf/wiki/The%20OPERA%20wiki/" rel="nofollow">https://sourceforge.net/p/operasf/wiki/The%20OPERA%20wiki/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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