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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39114?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</guid>
	<pubDate>Tue, 28 Jan 2020 05:12:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application</link>
	<title><![CDATA[EFS: an ensemble feature selection tool implemented as R-package and web-application]]></title>
	<description><![CDATA[<p><span>The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.</span></p>
<p><a href="https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8">https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8</a></p><p>Address of the bookmark: <a href="http://efs.heiderlab.de/" rel="nofollow">http://efs.heiderlab.de/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19272/translate2r</guid>
	<pubDate>Fri, 21 Nov 2014 01:16:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19272/translate2r</link>
	<title><![CDATA[translate2R]]></title>
	<description><![CDATA[<p>After their presentation at the international &ldquo;user!&rdquo; conference, data analysis specialist <a href="http://www.eoda.de/en/" target="_blank">eoda</a> starts the public alpha testing of <a href="http://www.eoda.de/en/translate2R.html" target="_blank">translate2R</a>. With the start of alpha testing the innovative migration solution by the company hailing from Kassel discards the working title &ldquo;translateR&rdquo; and takes on the final product brand name &ldquo;translate2R&rdquo;. translate2R is a service for the automated translation of SPSS&reg; syntax to R code, therefore supporting data analysts with a quick and low-risk migration to R.</p><p>The manual translation of many, frequently rather complex SPSS scripts often presents itself as a tedious and error-prone task, and represents a rather large obstacle for many analysts and companies to migrate to a modern, open source data management and analysis tool like R. With translate2R this hurdle will be diminished substantially.</p><p>Find at https://service.eoda.de/translater/?lang=en</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/19087/dcgor</guid>
	<pubDate>Sat, 08 Nov 2014 14:54:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19087/dcgor</link>
	<title><![CDATA[dcGOR]]></title>
	<description><![CDATA[<p>An R package for analysing ontologies and protein domain annotations has been published in PLoS Computational Biology (http://dx.doi.org/10.1371/journal.pcbi.1003929). The package is distributed as part of CRAN (http://cran.r-project.org/package=dcGOR), and also at GitHub for version control.<br /><br />The dedicated website is available in http://supfam.org/dcGOR, from which several demos are also provided:<br /><br />1. Analysing SCOP domains: http://supfam.org/dcGOR/demo-Fang.html<br /><br />2. Analysing Pfam domains: http://supfam.org/dcGOR/demo-Basu.html<br /><br />3. Analysing InterPro domains: http://supfam.org/dcGOR/demo-Customisation.html<br /><br />&nbsp;</p>]]></description>
	<dc:creator>Martin Jones</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties</guid>
	<pubDate>Mon, 28 Jan 2019 18:38:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties</link>
	<title><![CDATA[UpSetR: An R Package for the Visualization of Intersecting Sets and their Properties]]></title>
	<description><![CDATA[<p>UpSetR generates static&nbsp;<a href="http://vcg.github.io/upset/">UpSet</a>&nbsp;plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.</p>
<p>For further details about the original technique see the&nbsp;<a href="http://vcg.github.io/upset/about/">UpSet website</a>. You can also check out the&nbsp;<a href="https://gehlenborglab.shinyapps.io/upsetr/">UpSetR shiny app</a>.&nbsp;<a href="https://github.com/hms-dbmi/UpSetR-shiny">Here is the source code</a>&nbsp;for the shiny wrapper.</p>
<p>A&nbsp;<a href="https://github.com/ImSoErgodic/py-upset">Python package</a>&nbsp;called&nbsp;<a href="https://github.com/ImSoErgodic/py-upset">py-upset</a>&nbsp;to create UpSet plots has been created by GitHub user&nbsp;<a href="https://github.com/ImSoErgodic">ImSoErgodic</a>.</p><p>Address of the bookmark: <a href="https://github.com/hms-dbmi/UpSetR/" rel="nofollow">https://github.com/hms-dbmi/UpSetR/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<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/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41362/genemates-an-r-package-for-detecting-horizontal-gene-co-transfer-between-bacteria-using-gene-gene-associations-controlled-for-population-structure</guid>
	<pubDate>Sat, 07 Mar 2020 05:52:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41362/genemates-an-r-package-for-detecting-horizontal-gene-co-transfer-between-bacteria-using-gene-gene-associations-controlled-for-population-structure</link>
	<title><![CDATA[GeneMates: an R package for Detecting Horizontal Gene Co-transfer between Bacteria Using Gene-gene Associations Controlled for Population Structure]]></title>
	<description><![CDATA[<p><span>GeneMates is an R package implementing a network approach to identify horizontal gene co-transfer (HGcoT) between bacteria using whole-genome sequencing (WGS) data. It is particularly useful for investigating intra-species HGcoT, where presence-absence status of acquired genes is usually confounded by bacterial population structure due to clonal reproduction.</span></p>
<p><a href="https://www.biorxiv.org/content/10.1101/2020.02.29.970970v1">https://www.biorxiv.org/content/10.1101/2020.02.29.970970v1</a></p><p>Address of the bookmark: <a href="https://github.com/wanyuac/GeneMates" rel="nofollow">https://github.com/wanyuac/GeneMates</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</guid>
	<pubDate>Thu, 14 Dec 2023 12:33:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements</link>
	<title><![CDATA[ReConPlot: an R package for the visualization and interpretation of genomic rearrangements]]></title>
	<description><![CDATA[<p>ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false" rel="nofollow">https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21241/pacman</guid>
	<pubDate>Mon, 16 Feb 2015 12:15:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21241/pacman</link>
	<title><![CDATA[Pacman]]></title>
	<description><![CDATA[<p><span>The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.<br /><br />Function names in the pacman package follow the format of p_xxx where &lsquo;xxx&rsquo; is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn&rsquo;t available locally it will install it for you.<br /><br /></span></p><p><strong>Installation</strong></p><p><span>To download the development version of pacman:</span></p><p><span>Download the </span><a href="https://github.com/trinker/pacman/zipball/master">zip ball</a><span> or </span><a href="https://github.com/trinker/pacman/tarball/master">tar ball</a><span>, decompress and run </span><code>R CMD INSTALL</code><span> on it, or use th</span><span>e </span><strong>devtools</strong><span> package to install the development version:</span></p><pre title="">## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")
</pre><p>Note: Windows users need <a href="http://www.murdoch-sutherland.com/Rtools/">Rtools</a> and <a href="http://CRAN.R-project.org/package=devtools">devtools</a> to install this way.</p><p>More at https://github.com/trinker/pacman</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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