<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33976?offset=140</link>
	<atom:link href="https://bioinformaticsonline.com/related/33976?offset=140" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37572/gtdb-tk-a-toolkit-for-assigning-objective-taxonomic-classifications-to-bacterial-and-archaeal-genomes</guid>
	<pubDate>Wed, 22 Aug 2018 03:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37572/gtdb-tk-a-toolkit-for-assigning-objective-taxonomic-classifications-to-bacterial-and-archaeal-genomes</link>
	<title><![CDATA[GTDB-Tk: A toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes.]]></title>
	<description><![CDATA[<p>GTDB-Tk is a software toolkit for assigning objective taxonomic classifications to bacterial and archaeal genomes. It is computationally efficient and designed to work with recent advances that allow hundreds or thousands of metagenome-assembled genomes (MAGs) to be obtained directly from environmental samples. It can also be applied to isolate and single-cell genomes. The GTDB-Tk is open source and released under the GNU General Public License (Version 3).</p>
<p>GTDB-Tk is&nbsp;<span>under active development and validation</span>. Please independently confirm the GTDB-Tk predictions by manually inspecting the tree and bringing any discrepencies to our attention. Notifications about GTDB-Tk releases will be available through the ACE Twitter account (<a href="https://twitter.com/ace_uq">https://twitter.com/ace_uq</a>).</p><p>Address of the bookmark: <a href="https://github.com/Ecogenomics/GTDBTk" rel="nofollow">https://github.com/Ecogenomics/GTDBTk</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</guid>
	<pubDate>Tue, 28 Jan 2020 03:21:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes</link>
	<title><![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]></title>
	<description><![CDATA[<p><span>Welcome to&nbsp;</span><span>kevlar</span><span>, software for predicting&nbsp;</span><em>de novo</em><span>&nbsp;genetic variants without mapping reads to a reference genome! kevlar's&nbsp;</span><em>k</em><span>-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.&nbsp;</span></p>
<p><span>More at&nbsp;<a href="https://kevlar.readthedocs.io/en/latest/">https://kevlar.readthedocs.io/en/latest/</a></span></p>
<p><span><a href="https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf">https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf</a></span></p><p>Address of the bookmark: <a href="https://github.com/kevlar-dev/kevlar" rel="nofollow">https://github.com/kevlar-dev/kevlar</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41918/phispy-phispy-identifies-prophages-in-bacterial-and-probably-archaeal-genomes</guid>
	<pubDate>Tue, 30 Jun 2020 21:36:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41918/phispy-phispy-identifies-prophages-in-bacterial-and-probably-archaeal-genomes</link>
	<title><![CDATA[PhiSpy: PhiSpy identifies prophages in Bacterial (and probably Archaeal) genomes]]></title>
	<description><![CDATA[<p>PhiSpy identifies prophages in Bacterial (and probably Archaeal) genomes. Given an annotated genome it will use several approaches to identify the most likely prophage regions.</p>
<p>Initial versions of PhiSpy were written by</p>
<p>Sajia Akhter (<a href="mailto:sajia@stanford.edu">sajia@stanford.edu</a>)&nbsp;<a href="http://edwards.sdsu.edu/research/">Edwards Bioinformatics Lab</a></p>
<p>Improvements, bug fixes, and other changes were made by</p>
<p>Katelyn McNair&nbsp;<a href="http://edwards.sdsu.edu/research/">Edwards Bioinformatics Lab</a>&nbsp;and Przemyslaw Decewicz&nbsp;<a href="http://ddlemb.com/">DEMB at the University of Warsaw</a></p><p>Address of the bookmark: <a href="https://github.com/linsalrob/PhiSpy" rel="nofollow">https://github.com/linsalrob/PhiSpy</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</guid>
	<pubDate>Wed, 23 Jun 2021 07:54:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43090/loretta-a-user-friendly-tool-for-assembling-viral-genomes-from-pacbio-sequence-data</link>
	<title><![CDATA[LoReTTA, a user-friendly tool for assembling viral genomes from PacBio sequence data]]></title>
	<description><![CDATA[<p>LoReTTA (Long Read Template-Targeted Assembler), a tool designed for performing <em>de novo</em> assembly of long reads generated from viral genomes on the PacBio platform. LoReTTA exploits a reference genome to guide the assembly process, an approach that has been successful with short reads.</p>
<p>https://academic.oup.com/ve/article/7/1/veab042/6248116</p><p>Address of the bookmark: <a href="https://academic.oup.com/ve/article/7/1/veab042/6248116" rel="nofollow">https://academic.oup.com/ve/article/7/1/veab042/6248116</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44561/bactopia-a-flexible-pipeline-for-complete-analysis-of-bacterial-genomes</guid>
	<pubDate>Sat, 08 Jun 2024 16:25:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44561/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>Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!</p>
<p>Bactopia was inspired by&nbsp;<a href="https://staphopia.github.io/">Staphopia</a>, a workflow we (Tim Read and myself) released that is targeted towards&nbsp;<em>Staphylococcus aureus</em>&nbsp;genomes. Using what we learned from Staphopia and user feedback, Bactopia was developed from scratch with usability, portability, and speed in mind from the start.</p>
<p>Bactopia uses&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>&nbsp;to manage the workflow, allowing for support of many types of environments (e.g. cluster or cloud). Bactopia allows for the usage of many public datasets as well as your own datasets to further enhance the analysis of your sequencing. Bactopia only uses software packages available from&nbsp;<a href="https://bioconda.github.io/">Bioconda</a>&nbsp;and&nbsp;<a href="https://conda-forge.org/">Conda-Forge</a>&nbsp;to make installation as simple as possible for&nbsp;<em>all</em>&nbsp;users.</p>
<p>To highlight the use of&nbsp;<a href="https://bactopia.github.io/latest/full-guide/">Bactopia</a>&nbsp;and&nbsp;<a href="https://bactopia.github.io/latest/bactopia-tools/">Bactopia Tools</a>, we performed an analysis of 1,664 public&nbsp;<em>Lactobacillus</em>&nbsp;genomes, focusing on&nbsp;<em>Lactobacillus crispatus</em>, a species that is a common part of the human vaginal microbiome. The results from this analysis are published in mSystems under the title:&nbsp;<em><a href="https://doi.org/10.1128/mSystems.00190-20">Bactopia: a flexible pipeline for complete analysis of bacterial genomes</a></em></p>
<p><a href="https://bactopia.github.io/latest/assets/bactopia-workflow.png"><img src="https://bactopia.github.io/latest/assets/bactopia-workflow.png" alt="Bactopia Workflow" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://bactopia.github.io/latest/" rel="nofollow">https://bactopia.github.io/latest/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39884/retrieving-taxonomic-information-with-r</guid>
	<pubDate>Thu, 29 Aug 2019 01:38:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39884/retrieving-taxonomic-information-with-r</link>
	<title><![CDATA[Retrieving Taxonomic Information with R]]></title>
	<description><![CDATA[<p>This vignette will introduce users to the retrieval of taxonomic information with&nbsp;<code>myTAI</code>. The&nbsp;<code>taxonomy()</code>&nbsp;function implemented in&nbsp;<code>myTAI</code>&nbsp;relies on the powerful package&nbsp;<a href="https://github.com/ropensci/taxize">taxize</a>. Nevertheless, taxonomic information retrieval has been customized for the&nbsp;<code>myTAI</code>&nbsp;standard and for organism specific information retrieval.</p>
<p>Specifically, the&nbsp;<code>taxonomy()</code>&nbsp;function implemented in&nbsp;<code>myTAI</code>&nbsp;can be used to classify genomes according to phylogenetic classification into Phylostrata (Phylostratigraphy) or to retrieve species specific taxonomic information when performing Divergence Stratigraphy (see&nbsp;<a href="https://cran.r-project.org/web/packages/myTAI/vignettes/Introduction.html">Introduction</a>&nbsp;for details).</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/myTAI/vignettes/Taxonomy.html" rel="nofollow">https://cran.r-project.org/web/packages/myTAI/vignettes/Taxonomy.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</guid>
	<pubDate>Tue, 18 Apr 2017 04:28:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop</link>
	<title><![CDATA[Metagenomics assembly workshop !!]]></title>
	<description><![CDATA[<div>
<div>
<div id="welcome-to-metagenomics-workshop">
<p>Welcome to the one-day metagenomics assembly workshop. This tutorial will guide you through the typical steps of metagenome assembly and binning.</p>
<div>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html">The Tutorial Data Set</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/qc/index.html">FastQC Quality Control</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/index.html">Assembly</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/velvet.html">Velvet Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/megahit.html">MEGAHIT Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/idba_ud.html">IDBA-UD Assembly</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/assembly/ray.html">Ray Assembly</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/geneprediction/index.html">Gene Prediction</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/index.html">Assembly Evaluation</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/mapping.html">Read Mapping</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/evaluation/metaquast.html">MetaQUAST</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/index.html">Binning</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/maxbin.html">MaxBin Binning</a></li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/binning/metabat.html">MetaBAT Binning</a></li>
</ul>
</li>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/index.html">Classification</a>
<ul>
<li><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/classification/kraken.html">Kraken Taxonomic Sequence Classification System</a></li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</div>
<div><a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/data.html" title="The Tutorial Data Set">Next&nbsp;<span></span></a>
<p>&nbsp;</p>
</div><p>Address of the bookmark: <a href="http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html" rel="nofollow">http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</guid>
	<pubDate>Mon, 10 Jul 2017 10:09:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</link>
	<title><![CDATA[DISCO : multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler]]></title>
	<description><![CDATA[<p><span>DISCO is a multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler. Disco was developed as a&nbsp;scalable assembler to assemble large metagenomes from billions of Illumina sequencing reads of complex microbial communities. Disco was parallelized for computer clusters in a hybrid architecture that integrated shared-memory multi-threading, point-to-point message passing, and remote direct memory access. The assembly and scaffolding were performed using an iterative overlap graph approach.</span></p><p>Address of the bookmark: <a href="http://disco.omicsbio.org/" rel="nofollow">http://disco.omicsbio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</guid>
	<pubDate>Wed, 20 Aug 2014 22:09:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</link>
	<title><![CDATA[Pimp your brain: Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/KqelGy6Q8nE" frameborder="0" allowfullscreen></iframe>Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research.

In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO

More videos are available on www.mpimp-golm.mpg.de]]></description>
	
</item>

</channel>
</rss>