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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41675?offset=40</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads</guid>
	<pubDate>Mon, 11 Jun 2018 05:14:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads</link>
	<title><![CDATA[npScarf: real-time scaffolder using SPAdes contigs and Nanopore sequencing reads]]></title>
	<description><![CDATA[npScarf (jsa.np.npscarf) is a program that connect contigs from a draft genomes to generate sequences that are closer to finish. These pipelines can run on a single laptop for microbial datasets. In real-time mode, it can be integrated with simple structural analyses such as gene ordering, plasmid forming.<p>Address of the bookmark: <a href="http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html" rel="nofollow">http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</guid>
	<pubDate>Thu, 14 May 2020 15:09:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</link>
	<title><![CDATA[LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly]]></title>
	<description><![CDATA[<p>LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.</p><p>Address of the bookmark: <a href="https://github.com/CAFS-bioinformatics/LR_Gapcloser" rel="nofollow">https://github.com/CAFS-bioinformatics/LR_Gapcloser</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/37198/understanding-blastn-output-format-6</guid>
	<pubDate>Wed, 27 Jun 2018 18:38:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/37198/understanding-blastn-output-format-6</link>
	<title><![CDATA[Understanding BLASTn output format 6 !]]></title>
	<description><![CDATA[<h3 id="sites-page-title-header" style="text-align: left;"><span>BLASTn output format 6</span></h3><div id="sites-canvas-main"><div id="sites-canvas-main-content"><div dir="ltr"><div><div><em>BLASTn</em> maps DNA against DNA, for example gene sequences against a reference genome<br /><br /><code><strong>blastn</strong>  -query <span>genes.ffn</span>  -subject <span>genome.fna</span>  -outfmt <strong>6</strong></code></div><h2>BLASTn tabular output format 6</h2>
<p><strong>Column headers:</strong><br /><code>qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore</code><br /></p>
<table border="1" cellspacing="0">
<tbody>
<tr>
<td> 1.</td>
<td> qseqid</td>
<td> query (e.g., gene) sequence id</td>
</tr>
<tr>
<td> 2.</td>
<td> sseqid</td>
<td> subject (e.g., reference genome) sequence id</td>
</tr>
<tr>
<td> 3.</td>
<td> pident</td>
<td> percentage of identical matches</td>
</tr>
<tr>
<td> 4.</td>
<td> length</td>
<td> alignment length</td>
</tr>
<tr>
<td> 5.</td>
<td> mismatch</td>
<td> number of mismatches</td>
</tr>
<tr>
<td> 6.</td>
<td> gapopen</td>
<td> number of gap openings</td>
</tr>
<tr>
<td> 7.</td>
<td> qstart</td>
<td> start of alignment in query</td>
</tr>
<tr>
<td> 8.</td>
<td> qend</td>
<td> end of alignment in query</td>
</tr>
<tr>
<td> 9.</td>
<td> sstart</td>
<td> start of alignment in subject</td>
</tr>
<tr>
<td> 10.</td>
<td> send</td>
<td> end of alignment in subject</td>
</tr>
<tr>
<td> 11.</td>
<td> evalue</td>
<td> <a href="http://www.metagenomics.wiki/tools/blast/evalue">expect value</a></td>
</tr>
<tr>
<td> 12.</td>
<td> bitscore</td>
<td> <a href="http://www.metagenomics.wiki/tools/blast/evalue"><strong>bit score</strong></a></td>
</tr>
</tbody>
</table>
<p><strong><br /></strong></p>
</div><h2><a name="TOC-Define-your-own-output-format" id="TOC-Define-your-own-output-format"></a>Define your own output format</h2><div><em>by adding the option -outfmt, as for example: </em><strong><br /></strong></div>
<p><code><strong>-outfmt</strong> <strong>"6</strong> <span>qseqid sseqid pident qlen length mismatch gapope evalue bitscore</span><strong>"</strong></code><br /><br /><em><strong>supported format specifiers are:</strong></em><br /><code>qseqid    </code>Query Seq-id<br /><code>qgi       </code>Query GI<br /><code>qacc      </code>Query accesion<br /><code>qaccver   </code>Query accesion.version<br /><code>qlen      </code>Query sequence length<br /><code>sseqid    </code>Subject Seq-id<br /><code>sallseqid </code>All subject Seq-id(s), separated by a ';'<br /><code>sgi       </code>Subject GI<br /><code>sallgi    </code>All subject GIs<br /><code>sacc      </code>Subject accession<br /><code>saccver   </code>Subject accession.version<br /><code>sallacc   </code>All subject accessions<br /><code>slen      </code>Subject sequence length<br /><code>qstart    </code>Start of alignment in query<br /><code>qend      </code>End of alignment in query<br /><code>sstart    </code>Start of alignment in subject<br /><code>send      </code>End of alignment in subject<br /><code>qseq      </code>Aligned part of query sequence<br /><code>sseq      </code>Aligned part of subject sequence<br /><code>evalue    </code>Expect value<br /><code>bitscore  </code>Bit score<br /><code>score     </code>Raw score<br /><code>length    </code>Alignment length<br /><code>pident    </code>Percentage of identical matches<br /><code>nident    </code>Number of identical matches<br /><code>mismatch  </code>Number of mismatches<br /><code>positive  </code>Number of positive-scoring matches<br /><code>gapopen   </code>Number of gap openings<br /><code>gaps      </code>Total number of gaps<br /><code>ppos      </code>Percentage of positive-scoring matches<br /><code>frames    </code>Query and subject frames separated by a '/'<br /><code>qframe    </code>Query frame<br /><code>sframe    </code>Subject frame<br /><code>btop      </code>Blast traceback operations (BTOP)<br /><code>staxids   </code>Subject Taxonomy ID(s), separated by a ';'<br /><code>sscinames </code>Subject Scientific Name(s), separated by a ';'<br /><code>scomnames </code>Subject Common Name(s), separated by a ';'<br /><code>sblastnames </code>Subject Blast Name(s), separated by a ';'   (in alphabetical order)<br /><code>sskingdoms  </code>Subject Super Kingdom(s), separated by a ';'     (in alphabetical order) <br /><code>stitle      </code>Subject Title<br /><code>salltitles  </code>All Subject Title(s), separated by a '&lt;&gt;'<br /><code>sstrand   </code>Subject Strand<br /><code>qcovs     </code>Query Coverage Per Subject<br /><code>qcovhsp   </code>Query Coverage Per HSP<br /><strong><br /><em>default values are:</em></strong><br /><code><code>-outfmt "</code>6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore"</code></p>
</div></div></div>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</guid>
	<pubDate>Fri, 30 May 2014 04:48:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</link>
	<title><![CDATA[Next generation sequencing(NGS) books]]></title>
	<description><![CDATA[<p>Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream.</p>
<p>This bookmark is created to provide NGS online books links.</p><p>Address of the bookmark: <a href="http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version" rel="nofollow">http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26309/ratt</guid>
	<pubDate>Sun, 07 Feb 2016 16:09:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26309/ratt</link>
	<title><![CDATA[RATT]]></title>
	<description><![CDATA[<p><strong>RATT</strong> is software to transfer annotation from a reference (annotated) genome to an unannotated query genome.</p>
<p>It was first developed to transfer annotations between different genome assembly versions. However, it can also transfer annotations between strains and even different species, like <em>Plasmodium chabaudi</em> onto <em> P. berghei</em>, between different Leishmania species or <em>Salmonella enterica</em> onto other Salmonella serotypes. <strong>RATT</strong> is able to transfer any entries present on a reference sequence, such as the systematic id or an annotator's notes; such information would be lost in a <em>de novo</em> annotation.</p>
<p>More at http://ratt.sourceforge.net/</p><p>Address of the bookmark: <a href="http://ratt.sourceforge.net/" rel="nofollow">http://ratt.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</guid>
	<pubDate>Thu, 15 Dec 2016 05:47:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30149/mypro-a-seamless-pipeline-for-automated-prokaryotic-genome-assembly-and-annotation</link>
	<title><![CDATA[MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation]]></title>
	<description><![CDATA[<p>MyPro is an improved genomics software pipeline for prokaryotic genomes. MyPro is user-friendly and requires minimal programming skills. High-quality prokaryotic genome assembly and annotation can be obtained with ease. It performed better than de novo assemblers and contig integration software. Produces more contiguous assemblies, higher N50 values and lower number of contigs.</p>
<p>More at https://sourceforge.net/projects/sb2nhri/files/MyPro/</p><p>Address of the bookmark: <a href="http://www.sciencedirect.com/science/article/pii/S0167701215001207" rel="nofollow">http://www.sciencedirect.com/science/article/pii/S0167701215001207</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34501/dnapipete-de-novo-assembly-annotation-pipeline-for-transposable-elements</guid>
	<pubDate>Sat, 02 Dec 2017 18:25:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34501/dnapipete-de-novo-assembly-annotation-pipeline-for-transposable-elements</link>
	<title><![CDATA[dnaPipeTE: de-novo assembly &amp; annotation Pipeline for Transposable Elements]]></title>
	<description><![CDATA[<p>dnaPipeTE (for de-novo assembly &amp; annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (&lt; 1X).</p>
<ul>
<li>
<p>dnaPipeTE is developped by Cl&eacute;ment Goubert, Laurent Modolo and the TREEP team of the LBBE:&nbsp;<a href="http://lbbe.univ-lyon1.fr/-Equipe-Elements-transposables-.html?lang=en">http://lbbe.univ-lyon1.fr/-Equipe-Elements-transposables-.html?lang=en</a></p>
</li>
<li>
<p>You can find the original publication in GBE here:&nbsp;<a href="https://academic.oup.com/gbe/article/7/4/1192/533768">https://academic.oup.com/gbe/article/7/4/1192/533768</a></p>
</li>
</ul>
<p><a href="https://github.com/clemgoub/dnaPipeTE/blob/dev/dnaPipefront.png" target="_blank"><img src="https://github.com/clemgoub/dnaPipeTE/raw/dev/dnaPipefront.png" alt="Front" style="border: 0px;"></a><em>output examples of quantification and TE landscape (relative age) produced by dnaPipeTE</em></p>
<p><em>&nbsp;</em></p><p>Address of the bookmark: <a href="https://github.com/clemgoub/dnaPipeTE" rel="nofollow">https://github.com/clemgoub/dnaPipeTE</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</guid>
	<pubDate>Tue, 22 Jan 2019 05:52:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38758/roary-the-pan-genome-pipeline</link>
	<title><![CDATA[Roary: the Pan Genome Pipeline]]></title>
	<description><![CDATA[<p><span>Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.</span></p><p>Address of the bookmark: <a href="https://sanger-pathogens.github.io/Roary/" rel="nofollow">https://sanger-pathogens.github.io/Roary/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Wed, 15 May 2024 14:36:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44539/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</link>
	<title><![CDATA[Bactopia: a Flexible Pipeline for Complete Analysis of Bacterial Genomes]]></title>
	<description><![CDATA[<p dir="auto">Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is to process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p dir="auto">Bactopia can be split into two main parts:&nbsp;<a href="https://bactopia.github.io/latest/beginners-guide/">Bactopia Analysis Pipeline</a>, and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>.</p>
<p dir="auto">Bactopia Analysis Pipeline is the main&nbsp;<em>per-isolate</em>&nbsp;workflow in Bactopia. Built with&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.</p>
<p dir="auto"><a href="https://github.com/bactopia/bactopia/blob/master/data/bactopia-workflow.png" target="_blank"><img src="https://github.com/bactopia/bactopia/raw/master/data/bactopia-workflow.png" alt="Bactopia Overview" style="border: 0px;"></a></p>
<p dir="auto">Bactopia Tools are a set a independent workflows fo</p><p>Address of the bookmark: <a href="https://github.com/bactopia/bactopia" rel="nofollow">https://github.com/bactopia/bactopia</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44741/bioinformatician-in-pipeline-development</guid>
  <pubDate>Tue, 17 Dec 2024 23:43:54 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatician in pipeline development]]></title>
  <description><![CDATA[
<p>Are you interested in working with pipeline development in bioinformatics, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a position as Bioinformatician in pipeline development at Uppsala University.</p>

<p>National Bioinformatics Infrastructure Sweden (NBIS) (nbis.se) plays an important role in advancing life science research in Sweden by providing expert support and developing cutting-edge bioinformatics infrastructure. Operating as a truly national initiative, NBIS employs more than 120 bioinformaticians, system developers, and data stewards across multiple locations in Sweden. It serves as the bioinformatics platform at SciLifeLab, a national resource that facilitates research in molecular biosciences by offering access to state-of-the-art technologies and technical expertise. With strong ties to data-producing facilities and ongoing collaborations with leading research groups, NBIS is ideally positioned to support world-class bioinformatics analyses. Furthermore, NBIS is the Swedish node in ELIXIR, the European infrastructure for biological information.</p>

<p>NBIS is seeking an experienced bioinformatician to support both Swedish and international projects. As part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills, attention to detail, and the ability to troubleshoot complex bioinformatics pipelines are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs of the Swedish research community.</p>

<p>More at https://www.uu.se/en/about-uu/join-us/jobs-and-vacancies/job-details?query=778701</p>
]]></description>
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