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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40531?offset=610</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</guid>
	<pubDate>Tue, 30 Oct 2018 10:49:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38041/synima-a-synteny-imaging-tool-for-annotated-genome-assemblies</link>
	<title><![CDATA[Synima: a Synteny imaging tool for annotated genome assemblies]]></title>
	<description><![CDATA[<p><span>Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><a href="https://github.com/rhysf/Synima" target="_blank">https://github.com/rhysf/Synima</a><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</guid>
	<pubDate>Wed, 14 Nov 2018 04:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains</link>
	<title><![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]></title>
	<description><![CDATA[<p><span>ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.</span></p>
<p><span>https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454</span></p><p>Address of the bookmark: <a href="http://ani.mypathogen.cn/" rel="nofollow">http://ani.mypathogen.cn/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</guid>
	<pubDate>Fri, 21 Dec 2018 22:06:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg</link>
	<title><![CDATA[Versatile genome assembly evaluation with QUAST-LG]]></title>
	<description><![CDATA[<p>QUAST-LG is an extension of&nbsp;<a href="http://cab.spbu.ru/software/quast/">QUAST</a>&nbsp;intended for evaluating large-scale genome assemblies (up to mammalian-size).</p>
<p>QUAST-LG&nbsp;is included in the QUAST&nbsp; package starting from version 5.0.0 (<a href="https://sourceforge.net/projects/quast/files/latest/download?source=files">download the latest release</a>). Run QUAST as usual and do not forget to add&nbsp;<span>‐‐large</span>&nbsp;option to your command!</p>
<p>A short list of the new features (see&nbsp;<a href="http://cab.spbu.ru/files/quast/latest-docs/CHANGES.txt">CHANGES</a>&nbsp;for all):</p>
<ul>
<li>Significant speedup achieved by both&nbsp;use of new fast aligner (<a href="https://github.com/lh3/minimap2">minimap2</a>) and the refactoring of alignment analyzing&nbsp;modules</li>
<li>New k-mer-based completeness and correctness metrics</li>
<li>BUSCO added for enhanced reference-free analysis</li>
<li>The concept of upper bound&nbsp;assembly (theoretical limits on the assembly&nbsp;completeness and&nbsp;contiguity for a given genome and set of reads)</li>
</ul><p>Address of the bookmark: <a href="http://cab.spbu.ru/software/quast-lg/" rel="nofollow">http://cab.spbu.ru/software/quast-lg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</guid>
	<pubDate>Sun, 13 Jan 2019 07:05:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38670/ltr-finder-an-efficient-program-for-finding-full-length-ltr-retrotranspsons-in-genome-sequences</link>
	<title><![CDATA[LTR_Finder: an efficient program for finding full-length LTR retrotranspsons in genome sequences.]]></title>
	<description><![CDATA[<p>LTR_Finder is an efficient program for finding full-length LTR retrotranspsons in genome sequences.</p>
<p>The Program first constructs all exact match pairs by a suffix-array based algorithm and extends them to long highly similar pairs. Then Smith-Waterman algorithm is used to adjust the ends of LTR pair candidates to get alignment boundaries. These boundaries are subject to re-adjustment using supporting information of TG..CA box and TSRs and reliable LTRs are selected. Next, LTR_FINDER tries to identify PBS, PPT and RT inside LTR pairs by build-in aligning and counting modules. RT identification includes a dynamic programming to process frame shift. For other protein domains, LTR_FINDER calls ps_scan (from PROSITE,&nbsp;<a href="http://www.expasy.org/prosite/">http://www.expasy.org/prosite/</a>) to locate cores of important enzymes if they occur.</p><p>Address of the bookmark: <a href="https://github.com/xzhub/LTR_Finder" rel="nofollow">https://github.com/xzhub/LTR_Finder</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</guid>
	<pubDate>Tue, 09 Apr 2019 07:23:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants</link>
	<title><![CDATA[CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants]]></title>
	<description><![CDATA[<p><span>Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.</span></p>
<p><a href="https://www.nature.com/articles/nm.3975">https://www.nature.com/articles/nm.3975</a></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/nm.3975" rel="nofollow">https://www.nature.com/articles/nm.3975</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</guid>
	<pubDate>Fri, 21 Feb 2020 00:17:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</link>
	<title><![CDATA[BlobToolKit: A toolkit for genome assembly QC]]></title>
	<description><![CDATA[<p>Filtering raw genomic datasets is essential to avoid chimeric assemblies and to increase the validity of sequence-based biological inference. BlobToolKit extends the BlobTools<span>1</span>/Blobology<span>2</span>&nbsp;approach to simplify interactive and reproducible filtering.</p>
<p>BlobToolKit is comprised of four components:</p>
<ol>
<li><a href="https://blobtoolkit.genomehubs.org/btk-viewer/">BlobToolKit Viewer</a>&nbsp;allows browser-based interactive visualisation and filtering of preliminary or published genomic datasets even for highly fragmented assemblies.</li>
<li><a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;is a command-line program to convert assemblies and analysis results into datasets that can be further processed using&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and/or visualised in the Viewer.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/specification/">BlobToolKit Specification</a>&nbsp;features a formal schema and validator for the JSON-based BlobDir format used by&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/pipeline/">BlobToolKit Pipeline</a>&nbsp;is a configurable Snakemake pipeline that automates all steps from retrieving public datasets through running analyses and generating a BlobDir dataset with&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>, ready for visualisation in the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
</ol>
<p>Paper&nbsp;<a href="https://www.biorxiv.org/content/10.1101/844852v1.full.pdf">https://www.biorxiv.org/content/10.1101/844852v1.full.pdf</a></p><p>Address of the bookmark: <a href="https://blobtoolkit.genomehubs.org/" rel="nofollow">https://blobtoolkit.genomehubs.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</guid>
	<pubDate>Tue, 17 Mar 2020 07:30:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41464/phytozome-v121-plant-science-community-hub-for-accessing-palnts-genomic-data</link>
	<title><![CDATA[Phytozome  v12.1: plant science community hub for accessing palnts genomic data]]></title>
	<description><![CDATA[<p>Phytozome, the Plant Comparative Genomics portal of the Department of Energy's Joint Genome Institute, provides JGI users and the broader plant science community a hub for accessing, visualizing and analyzing JGI-sequenced plant genomes, as well as selected genomes and datasets that have been sequenced elsewhere. As of release v12.1.6, Phytozome hosts 93 assembled and annotated genomes, from 82 Viridiplantae species. More than half of these genomes have been sequenced, assembled and/or annotated with JGI Plant Science program resources. By integrating this large collection of plant genomes into a single resource and performing comprehensive and uniform annotation and analyses, Phytozome facilitates accurate and insightful comparative genomics studies.</p><p>Address of the bookmark: <a href="https://phytozome.jgi.doe.gov/pz/portal.html" rel="nofollow">https://phytozome.jgi.doe.gov/pz/portal.html</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</guid>
	<pubDate>Fri, 19 Jun 2020 07:34:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41896/kad-assessing-genome-assemblies-using-k-mer-copies-in-assemblies-and-k-mer-abundance-in-illumina-reads</link>
	<title><![CDATA[KAD: Assessing genome assemblies using K-mer copies in assemblies and K-mer abundance in Illumina reads]]></title>
	<description><![CDATA[<p>KAD is designed for evaluating the accuracy of nucleotide base quality of genome assemblies. Briefly, abundance of k-mers are quantified for both sequencing reads and assembly sequences. Comparison of the two values results in a single value per k-mer, K-mer Abundance Difference (KAD), which indicates how well the assembly matches read data for each k-mer.</p>
<p><a href="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" target="_blank"><img src="https://render.githubusercontent.com/render/math?math=KAD=log_{2}\begin{pmatrix}\frac{c%2Bm}{m(n%2B1)}\end{pmatrix}" alt="image" style="border: 0px;"></a></p>
<p>where,&nbsp;<em>c</em>&nbsp;is the count of a k-mer from reads,&nbsp;<em>m</em>&nbsp;is the mode of counts of read k-mers, and&nbsp;<em>n</em>&nbsp;is the copy of the k-mer in the assembly.</p><p>Address of the bookmark: <a href="https://github.com/liu3zhenlab/KAD" rel="nofollow">https://github.com/liu3zhenlab/KAD</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42206/pollard-lab</guid>
  <pubDate>Fri, 25 Sep 2020 20:20:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pollard Lab]]></title>
  <description><![CDATA[
<p>We are a bioinformatics research lab focused on developing novel methods and using them to study genome evolution, organization, and regulation. Our mission is to decode biomedical knowledge that is missed without rigorous statistical approaches.</p>

<p>http://docpollard.org/</p>

<p>Tools</p>

<p>http://docpollard.org/resources/software/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</guid>
	<pubDate>Sat, 26 Jun 2021 15:37:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</link>
	<title><![CDATA[Calling variants in non-diploid systems]]></title>
	<description><![CDATA[<p><span>The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been accomplished on human mitochondrial&nbsp;</span><span>DNA</span><span>&nbsp;although the same approaches will work equally good on viral and bacterial genomes (</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Rebolledo-Jaramillo2014">Rebolledo-Jaramillo&nbsp;<em>et al.</em>&nbsp;2014</a><span>,&nbsp;</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Li2015">Li&nbsp;<em>et al.</em>&nbsp;2015</a><span>).</span></p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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