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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38762?offset=140</link>
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	<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/44470/phyloherb-phylogenomic-analysis-pipeline-for-herbarium-specimens</guid>
	<pubDate>Wed, 21 Feb 2024 06:15:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44470/phyloherb-phylogenomic-analysis-pipeline-for-herbarium-specimens</link>
	<title><![CDATA[PhyloHerb: Phylogenomic Analysis Pipeline for Herbarium Specimens]]></title>
	<description><![CDATA[<p><span>What is PhyloHerb</span><span>: PhyloHerb is a wrapper program to process&nbsp;</span><span>genome skimming</span><span>&nbsp;data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include&nbsp;</span><span>low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming</span><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/lmcai/PhyloHerb/" rel="nofollow">https://github.com/lmcai/PhyloHerb/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</guid>
	<pubDate>Fri, 05 Feb 2016 06:43:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/26290/webinar-on-streamlining-large-scale-analysis-using-the-strand-ngs-pipeline-manager-on-24-feb-2016</link>
	<title><![CDATA[Webinar on Streamlining large scale analysis using the Strand NGS Pipeline Manager on 24 Feb 2016]]></title>
	<description><![CDATA[<p><a href="http://www.strand-ngs.com/webinar_registration" title="webinar"><strong>Live Webinar on Streamlining large scale NGS data analysis using the Strand NGS Pipeline Manager on 24 Feb 2016</strong></a></p><p><strong>Abstract:</strong> Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.</p><p>In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.</p><p><strong>Speaker:</strong> Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences</p><p><strong>Details:</strong> Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST<br /><strong>Register here:</strong> http://www.strand-ngs.com/webinar_registration</p><h3>&nbsp;</h3>]]></description>
	<dc:creator>Yeshodari</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34398/ont-assembly-and-illumina-polishing-pipeline</guid>
	<pubDate>Thu, 23 Nov 2017 10:13:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34398/ont-assembly-and-illumina-polishing-pipeline</link>
	<title><![CDATA[ONT assembly and Illumina polishing pipeline]]></title>
	<description><![CDATA[<p>This pipeline performs the following steps:</p>
<ul>
<li>Assembly of nanopore reads using&nbsp;<a href="http://canu.readthedocs.io/">Canu</a>.</li>
<li>Polish canu contigs using&nbsp;<a href="https://github.com/isovic/racon">racon</a>&nbsp;(<em>optional</em>).</li>
<li>Map a paired-end Illumina dataset onto the contigs obtained in the previous steps using&nbsp;<a href="http://bio-bwa.sourceforge.net/">BWA</a>&nbsp;mem.</li>
<li>Perform correction of contigs using&nbsp;<a href="https://github.com/broadinstitute/pilon/wiki">pilon</a>&nbsp;and the Illumina dataset.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/nanoporetech/ont-assembly-polish" rel="nofollow">https://github.com/nanoporetech/ont-assembly-polish</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</guid>
	<pubDate>Thu, 26 Jul 2018 09:20:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37414/arc-pipeline-which-facilitates-iterative-reference-guided-de-novo-assemblies</link>
	<title><![CDATA[ARC: pipeline which facilitates iterative, reference guided de novo assemblies]]></title>
	<description><![CDATA[<p>ARC is a pipeline which facilitates iterative, reference guided&nbsp;<em>de novo</em>&nbsp;assemblies with the intent of:</p>
<ol>
<li>Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.</li>
<li>Reducing/removing reference bias as compared to mapping based approaches.</li>
</ol>
<p><span>The software is designed to work in situations where a whole-genome assembly is not the objective, but rather when the researcher wishes to assemble discreet 'targets' contained within next-generation shotgun sequence data. ARC decomplexifies the traditionally difficult problem of assembly by breaking the reads into small, manageable subsets which can then be assembled quickly and efficiently in parallel. Applications include those in which the researcher wishes to&nbsp;</span><em>de novo</em><span>&nbsp;assemble specific content and a set of semi-similar reference targets is available to initialize the assembly process.</span></p>
<p>https://ibest.github.io/ARC/</p><p>Address of the bookmark: <a href="https://ibest.github.io/ARC/" rel="nofollow">https://ibest.github.io/ARC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</guid>
	<pubDate>Thu, 16 May 2019 00:17:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates</link>
	<title><![CDATA[multiPhATE: bioinformatics pipeline for functional annotation of phage isolates]]></title>
	<description><![CDATA[<p><span>multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a&nbsp;</span><em>de novo</em><span>&nbsp;phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases.&nbsp;</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/carolzhou/multiPhATE" rel="nofollow">https://github.com/carolzhou/multiPhATE</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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