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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31564?offset=90</link>
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	<item>
	<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/27328/platanus</guid>
	<pubDate>Fri, 13 May 2016 05:12:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27328/platanus</link>
	<title><![CDATA[Platanus]]></title>
	<description><![CDATA[<p>Platanus is a novel <em>de novo</em> sequence assembler that can reconstruct genomic sequences of<br> highly heterozygous diploids from massively parallel shotgun sequencing data.</p>
<p>The latest version is <a href="http://platanus.bio.titech.ac.jp/platanus/?page_id=14">1.2.4</a>.</p>
<p>To cite Platanus, please use the following:</p>
<p>Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, Yabana M, Harada M, Nagayasu E, Maruyama H, Kohara Y, Fujiyama A, Hayashi T, Itoh T, &ldquo;Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads&rdquo;.&nbsp;Genome Res. 2014 Aug;24(8):1384-95. doi: 10.1101/gr.170720.113. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/24755901">abstract</a> |<a href="http://genome.cshlp.org/content/24/8/1384.long"> full text</a>]</p><p>Address of the bookmark: <a href="http://platanus.bio.titech.ac.jp/" rel="nofollow">http://platanus.bio.titech.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping</guid>
	<pubDate>Fri, 20 May 2016 18:53:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping</link>
	<title><![CDATA[MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping]]></title>
	<description><![CDATA[<p><span>MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery.</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581</a></p>]]></description>
	<dc:creator>Neel</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/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/28119/kraken-ultrafast-metagenomic-sequence-classification-using-exact-alignments</guid>
	<pubDate>Mon, 27 Jun 2016 11:01:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28119/kraken-ultrafast-metagenomic-sequence-classification-using-exact-alignments</link>
	<title><![CDATA[Kraken: ultrafast metagenomic sequence classification using exact alignments]]></title>
	<description><![CDATA[<p>Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of <em>k</em>-mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at <a href="http://ccb.jhu.edu/software/kraken/" target="pmc_ext">http://ccb.jhu.edu/software/kraken/</a>.</p>
<p>Krona</p>
<p>https://sourceforge.net/p/krona/home/krona/</p><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</guid>
	<pubDate>Thu, 07 Jul 2016 12:05:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28303/fancy-oneliner-for-bioinformatics</link>
	<title><![CDATA[Fancy Oneliner for Bioinformatics !!]]></title>
	<description><![CDATA[<p><span>This webpage lists some of the one-liners that we frequently use in metagenomic analyses. You can click on the following links to browse through different topics. You can copy/paste the commands as they are in your terminal screen, provided you follow the same naming conventions and folder structures as we have. We are sharing these codes with the intention that if they are useful and help you in your analyses, then we will be appropriately credited as considerable effort has been put into devising them.</span></p><p>Address of the bookmark: <a href="http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html" rel="nofollow">http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/oneliners.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28554/megan6</guid>
	<pubDate>Mon, 25 Jul 2016 05:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28554/megan6</link>
	<title><![CDATA[MEGAN6]]></title>
	<description><![CDATA[<p>Microbiome analysis using a single application</p>
<p>MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.</p>
<ul>
<li>Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA</li>
<li>Functional analysis using InterPro2GO, SEED, eggNOG or KEGG</li>
<li>Bar charts, word clouds, Voronoi tree maps and many other charts</li>
<li>PCoA, clustering and networks</li>
<li>Supports metadata</li>
<li>MEGAN parses many different types of input</li>
</ul>
<p>Why use MEGAN6?</p>
<div>&nbsp;The software is:</div>
<div><ol>
<li>Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.</li>
<li>Powerful. MEGAN6 allows you to work with hundreds of samples containing&nbsp;hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.</li>
<li>Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.</li>
</ol></div><p>Address of the bookmark: <a href="https://ab.inf.uni-tuebingen.de/software/megan6" rel="nofollow">https://ab.inf.uni-tuebingen.de/software/megan6</a></p>]]></description>
	<dc:creator>Neel</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>

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