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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37576?offset=140</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</guid>
	<pubDate>Sun, 24 Mar 2024 20:06:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44487/r-package-for-pca-analysis</link>
	<title><![CDATA[R Package for PCA Analysis]]></title>
	<description><![CDATA[<p><span>An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub:&nbsp;https://github.com/Devashish13/PopulationStructure</span></p><p>Address of the bookmark: <a href="https://rpubs.com/Devashish13/PCAGenomics" rel="nofollow">https://rpubs.com/Devashish13/PCAGenomics</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</guid>
	<pubDate>Tue, 17 Sep 2024 02:28:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44659/figeno-tool-for-plotting-sequencing-data-along-genomic-coordinates</link>
	<title><![CDATA[Figeno: Tool for plotting sequencing data along genomic coordinates.]]></title>
	<description><![CDATA[<p><span>Tool for plotting sequencing data along genomic coordinates.</span></p>
<div>
<pre><code>FIGENO is a
  FIGure
    GENerator
for GENOmics</code></pre>
</div>
<p dir="auto">With figeno, you can plot various types of sequencing data along genomic coordinates. Video overview:&nbsp;<a href="https://www.youtube.com/watch?v=h1cBeXoSYTA">https://www.youtube.com/watch?v=h1cBeXoSYTA</a>.</p>
<p dir="auto"><a href="https://github.com/CompEpigen/figeno/blob/main/docs/content/images/figeno.png" target="_blank"><img src="https://github.com/CompEpigen/figeno/raw/main/docs/content/images/figeno.png" alt="figeno" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/CompEpigen/figeno" rel="nofollow">https://github.com/CompEpigen/figeno</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</guid>
	<pubDate>Fri, 02 Feb 2018 04:23:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35420/telomerehunter</link>
	<title><![CDATA[TelomereHunter]]></title>
	<description><![CDATA[<p><span>TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.</span><br><br><span>TelomereHunter is available for download at the following address:&nbsp;</span><a href="https://pypi.python.org/pypi/telomerehunter/" target="_blank">https://pypi.python.org/pypi/telomerehunter/</a></p><p>Address of the bookmark: <a href="http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html" rel="nofollow">http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</guid>
	<pubDate>Mon, 07 Aug 2017 18:49:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</link>
	<title><![CDATA[RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities]]></title>
	<description><![CDATA[<p>RAMI, which clusters related nodes in a phylogenetic tree based on the patristic distance. RAMI also produces indices of cluster properties and other indices used in population and community studies on-the-fly.</p>
<p><strong>Availability:</strong>&nbsp;RAMI is licensed under GNU GPL and can be run or downloaded from&nbsp;<a href="http://www.acgt.se/online.html" target="">http://www.acgt.se/online.html</a>.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051" rel="nofollow">https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</guid>
	<pubDate>Fri, 08 Dec 2017 16:26:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34567/jobtree-based-python-wrapper-to-run-the-genome-simulation-tool-suite-evolver</link>
	<title><![CDATA[jobTree based python wrapper to run the genome simulation tool suite Evolver]]></title>
	<description><![CDATA[<p><span>evolverSimControl</span><span>&nbsp;(</span><span>eSC</span><span>) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (</span><a href="http://evolution.genetics.washington.edu/phylip/newicktree.html">Newick format</a><span>). In addition to simply running evolver,&nbsp;</span><span>eSC</span><span>&nbsp;also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (</span><a href="http://genome.ucsc.edu/FAQ/FAQformat.html#format5">.maf</a><span>) from leaf and branch nodes from a completed simulation and with the help of&nbsp;</span><a href="https://github.com/dentearl/mafTools/">mafJoin</a><span>, join them together into a single maf covering the entire simulation.</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/evolverSimControl" rel="nofollow">https://github.com/dentearl/evolverSimControl</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34922/camsa-a-tool-for-comparative-analysis-and-merging-of-scaffold-assemblies</guid>
	<pubDate>Thu, 28 Dec 2017 09:10:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34922/camsa-a-tool-for-comparative-analysis-and-merging-of-scaffold-assemblies</link>
	<title><![CDATA[CAMSA :: a tool for Comparative Analysis and Merging of Scaffold Assemblies]]></title>
	<description><![CDATA[<p>CAMSA &ndash; is a tool for&nbsp;<span>C</span>omparative&nbsp;<span>A</span>nalysis and&nbsp;<span>M</span>erging of&nbsp;<span>S</span>caffold&nbsp;<span>A</span>ssemblies, distributed both as a standalone software package and as Python library under the MIT license.</p>
<p>Main features:</p>
<ol>
<li>works with any number of scaffold assemblies in de-novo non-progressive fashion</li>
<li>allows to simultaneously work with scaffold assemblies obtained from any&nbsp;<em>in silico</em>&nbsp;and&nbsp;<em>in vitro</em>&nbsp;techniques, supporting multiple existing formats via built-in converters</li>
<li>creates an extensive report with several comparative quality metrics (both on assembly level and on the level of individual assembly points)</li>
<li>constructs a merged combined scaffold assembly</li>
<li>provides an interactive framework for a visual comparative analysis of the given assemblies</li>
</ol><p>Address of the bookmark: <a href="https://cblab.org/camsa/" rel="nofollow">https://cblab.org/camsa/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</guid>
	<pubDate>Thu, 24 May 2018 02:53:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36752/minmax-a-versatile-tool-for-calculating-and-comparing-synonymous-codon-usage-and-its-impact-on-protein-folding</link>
	<title><![CDATA[%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding.]]></title>
	<description><![CDATA[%MM calculates whether a given gene sequence encodes amino acids using the most common codons possible, the least common codons possible, or (most typically) some combination of these extremes. See our PLoS ONE paper for more details on how the %MinMax algorithm works. 

%MinMax results are averaged over an 18-codon sliding window; hence the result for "codon window = 1" is the average codon usage for codons 1-18, codon window 2 = codons 2-19, etc.<p>Address of the bookmark: <a href="http://www.codons.org/" rel="nofollow">http://www.codons.org/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:39:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37672/seqmonka-tool-to-visualise-and-analyse-high-throughput-mapped-sequence-data</link>
	<title><![CDATA[SeqMonk:A tool to visualise and analyse high throughput mapped sequence data]]></title>
	<description><![CDATA[<p>SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:</p>
<ul>
<li>Import of mapped data from mapped data (BAM/SAM/bowtie etc)</li>
<li>Creation of data groups for visualisation and analysis</li>
<li>Visualisation of mapped regions against an annotated genome.</li>
<li>Flexible quantitation of the mapped data to allow comparisons between data sets</li>
<li>Statistical analysis of data to find regions of interest</li>
<li>Creation of reports containing data and genome annotation</li>
</ul><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<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>

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