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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36752?offset=110</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</guid>
	<pubDate>Wed, 15 Jun 2016 18:08:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27841/covcal-coverage-read-count-calculator</link>
	<title><![CDATA[CovCal: Coverage / Read Count Calculator]]></title>
	<description><![CDATA[<h2>Coverage / Read Count Calculator</h2>
<h4>Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).</h4>
<p><span>Instructions:</span> set the read length/configuration and genome size, then select what you want to calculate.</p>
<p>Written by <a href="http://stephenturner.us/" target="blank">Stephen Turner</a>, based on the <a href="http://www.ncbi.nlm.nih.gov/pubmed/3294162" target="_blank">Lander-Waterman formula</a>, inspired by <a href="http://core-genomics.blogspot.com/2016/05/how-many-reads-to-sequence-genome.html" target="_blank">a similar calculator</a> written by James Hadfield. Coverage is calculated as <em>C=LN/G</em> and reads as <em>N=CG/L</em> where <em>C</em> = Coverage (X),<em>L</em> = Read length (bp), <em>G</em> = Haploid genome size (bp), and <em>N</em> = Number of reads. Source code <a href="https://github.com/stephenturner/covcalc" target="_blank">on GitHub</a>.</p><p>Address of the bookmark: <a href="http://apps.bioconnector.virginia.edu/covcalc/" rel="nofollow">http://apps.bioconnector.virginia.edu/covcalc/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</guid>
	<pubDate>Thu, 16 Feb 2017 11:39:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30971/hiveplot</link>
	<title><![CDATA[HivePlot]]></title>
	<description><![CDATA[<p>The&nbsp;<em>hive plot</em>&nbsp;is a rational visualization method for drawing networks. Nodes are mapped to and positioned on radially distributed linear axes &mdash; this mapping is based on network structural properties. Edges are drawn as curved links. Simple and interpretable.</p>
<p>The purpose of the hive plot is to establish a new baseline for visualization of large networks &mdash; a method that is both general and tunable and useful as a starting point in visually exploring network structure.</p>
<p>More at&nbsp;http://www.hiveplot.com/</p><p>Address of the bookmark: <a href="http://www.hiveplot.com/" rel="nofollow">http://www.hiveplot.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</guid>
	<pubDate>Thu, 14 Dec 2017 15:51:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data</link>
	<title><![CDATA[SVfinder: Tool for detecting genomic rearrangement form DNA-seq data]]></title>
	<description><![CDATA[<p><span>SVfinder provides genome-wide detection of structural variants from next generation paired-end sequencing reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cauyrd/SVfinder" rel="nofollow">https://github.com/cauyrd/SVfinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</guid>
	<pubDate>Wed, 21 Mar 2018 12:25:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</link>
	<title><![CDATA[GMOL: An Interactive Tool for 3D Genome Structure Visualization]]></title>
	<description><![CDATA[<p><span>GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/srep20802" rel="nofollow">https://www.nature.com/articles/srep20802</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</guid>
	<pubDate>Sun, 31 May 2020 02:01:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</link>
	<title><![CDATA[SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.]]></title>
	<description><![CDATA[<p>SynVisio lets you explore the results of&nbsp;<a href="http://chibba.pgml.uga.edu/mcscan2/">McScanX</a>&nbsp;a popular synteny and collinearity detection toolkit and generate publication ready images.</p>
<p>SynVisio requires two files to run:</p>
<ul>
<li>The&nbsp;<strong>simplified gff file</strong>&nbsp;that was used as an input for a McScanX query.</li>
<li>The&nbsp;<strong>collinearity file</strong>&nbsp;generated as an output by McScanX for the same input query.</li>
<li>Optional&nbsp;<strong>track file</strong>&nbsp;in bedgraph format to annotate the generated charts.</li>
</ul>
<p>SynVisio offers different types of visualizations such as&nbsp;<strong>Linear Parallel plots</strong>,&nbsp;<strong>Hive plots</strong>,&nbsp;<strong>Stacked Parallel Plots&nbsp;</strong>and&nbsp;<strong>Dot plots</strong>. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.</p><p>Address of the bookmark: <a href="https://synvisio.github.io/#/" rel="nofollow">https://synvisio.github.io/#/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</guid>
	<pubDate>Fri, 14 Jun 2024 14:42:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</link>
	<title><![CDATA[Panacus : A Counting Tool for Pangenome Graphs]]></title>
	<description><![CDATA[<p dir="auto"><code>panacus</code>&nbsp;is a tool for calculating statistics for&nbsp;<a href="https://github.com/GFA-spec/GFA-spec/blob/master/GFA1.md">GFA</a>&nbsp;files. It supports GFA files with&nbsp;<code>P</code>&nbsp;and&nbsp;<code>W</code>&nbsp;lines, but requires that the graph is&nbsp;<code>blunt</code>, i.e., nodes do not overlap and consequently, each link (<code>L</code>) points from the end of one segment (<code>S</code>) to the start of another.</p>
<p dir="auto"><code>panacus</code>&nbsp;supports the following calculations:</p>
<ul dir="auto">
<li>coverage histogram</li>
<li>pangenome growth statistics</li>
<li>path-/group-resolved coverage table</li>
</ul><p>Address of the bookmark: <a href="https://github.com/marschall-lab/panacus" rel="nofollow">https://github.com/marschall-lab/panacus</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42303/fqc-dashboard-integrates-fastqc-results-into-a-web-based-interactive-and-extensible-fastq-quality-control-tool</guid>
	<pubDate>Tue, 10 Nov 2020 01:30:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42303/fqc-dashboard-integrates-fastqc-results-into-a-web-based-interactive-and-extensible-fastq-quality-control-tool</link>
	<title><![CDATA[FQC Dashboard: Integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool]]></title>
	<description><![CDATA[<p>FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data.</p><p>Address of the bookmark: <a href="https://github.com/pnnl/fqc" rel="nofollow">https://github.com/pnnl/fqc</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33866/perlbrew-admin-free-perl-installation-management-tool</guid>
	<pubDate>Wed, 12 Jul 2017 03:53:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33866/perlbrew-admin-free-perl-installation-management-tool</link>
	<title><![CDATA[Perlbrew: admin-free perl installation management tool.]]></title>
	<description><![CDATA[<p>perlbrew is an admin-free perl installation management tool. The latest version is 0.79, read the release note:&nbsp;<a href="https://perlbrew.pl/Release-0.79.html">Release 0.79</a>.&nbsp;</p>
<p>Copy &amp; Paste this line into your terminal:</p>
<pre><code>\curl -L https://install.perlbrew.pl | bash
</code></pre>
<p>Or, if your system does not have curl but something else:</p>
<pre><code># Linux
\wget -O - https://install.perlbrew.pl | bash

# FreeBSD
\fetch -o- https://install.perlbrew.pl | sh
</code></pre>
<p>If you prefer to install with cpan, there are two steps:</p>
<pre><code>sudo cpan App::perlbrew
perlbrew init
</code></pre>
<p>If it is installed with cpan, the perlbrew executable should be installed as&nbsp;<code>/usr/bin/perlbrew</code>&nbsp;or&nbsp;<code>/usr/local/bin/perlbrew</code>. For all users who want to use perlbrew, a prior&nbsp;<code>perlbrew init</code>&nbsp;needs to be executed.</p>
<p>The default perlbrew root directory is&nbsp;<code>~/perl5/perlbrew</code>, which can be changed by setting&nbsp;<code>PERLBREW_ROOT</code>environment variable before the installation and initialization. For more advanced installation process, please read&nbsp;<a href="http://metacpan.org/module/App::perlbrew">the perlbrew document</a>.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://perlbrew.pl/" rel="nofollow">https://perlbrew.pl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</guid>
	<pubDate>Fri, 01 Dec 2017 04:10:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool</link>
	<title><![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]></title>
	<description><![CDATA[<p><strong>PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.</strong></p>
<p><strong>Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.</strong></p>
<p>PLAST stands for&nbsp;<em>Parallel Local Sequence Alignment Search Tool&nbsp;</em>and is was&nbsp;<a href="http://www.biomedcentral.com/1471-2105/10/329" target="_blank">published in BMC Bioinformatics.</a></p>
<p>PLAST is a general purpose sequence comparison tool providing the following benefits:</p>
<ul>
<li>PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),</li>
<li>Reduces the processing time of sequences comparisons while providing highest quality results,</li>
<li>Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),</li>
<li>Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,</li>
<li>Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.</li>
</ul>
<p>https://plast.inria.fr/</p><p>Address of the bookmark: <a href="https://plast.inria.fr/" rel="nofollow">https://plast.inria.fr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</guid>
	<pubDate>Fri, 08 Dec 2017 17:41:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34571/mugsy-multiple-whole-genome-alignment-tool</link>
	<title><![CDATA[Mugsy: multiple whole genome alignment tool]]></title>
	<description><![CDATA[<p><span>Mugsy is a multiple whole genome aligner. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy accepts draft genomes in the form of multi-FASTA files and does not require a reference genome.</span></p>
<p>To cite Mugsy, use:</p>
<p>Angiuoli SV and Salzberg SL.&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/27/3/334">Mugsy: Fast multiple alignment of closely related whole genomes.</a><em>Bioinformatics</em>&nbsp;2011 27(3):334-4</p><p>Address of the bookmark: <a href="http://mugsy.sourceforge.net/" rel="nofollow">http://mugsy.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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