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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42299?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</guid>
	<pubDate>Wed, 13 Mar 2019 19:20:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</link>
	<title><![CDATA[plumber:An R package that converts your existing R code to a web API]]></title>
	<description><![CDATA[<p>plumber allows you to create a REST API by merely decorating your existing R source code with special comments. Take a look at an example.</p>
<pre><code><span># plumber.R
</span><span>
</span><span>#* Echo back the input
#* @param msg The message to echo
#* @get /echo
</span><span>function</span><span>(</span><span>msg</span><span>=</span><span>""</span><span>){</span><span>
  </span><span>list</span><span>(</span><span>msg</span><span> </span><span>=</span><span> </span><span>paste0</span><span>(</span><span>"The message is: '"</span><span>,</span><span> </span><span>msg</span><span>,</span><span> </span><span>"'"</span><span>))</span><span>
</span><span>}</span><span>

</span><span>#* Plot a histogram
#* @png
#* @get /plot
</span><span>function</span><span>(){</span><span>
  </span><span>rand</span><span> </span><span>&lt;-</span><span> </span><span>rnorm</span><span>(</span><span>100</span><span>)</span><span>
  </span><span>hist</span><span>(</span><span>rand</span><span>)</span><span>
</span><span>}</span><span>

</span><span>#* Return the sum of two numbers
#* @param a The first number to add
#* @param b The second number to add
#* @post /sum
</span><span>function</span><span>(</span><span>a</span><span>,</span><span> </span><span>b</span><span>){</span><span>
  </span><span>as.numeric</span><span>(</span><span>a</span><span>)</span><span> </span><span>+</span><span> </span><span>as.numeric</span><span>(</span><span>b</span><span>)</span><span>
</span><span>}</span></code></pre><p>Address of the bookmark: <a href="https://www.rplumber.io/" rel="nofollow">https://www.rplumber.io/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study</guid>
	<pubDate>Thu, 30 Jul 2020 22:06:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42012/phewas-r-package-is-designed-to-provide-an-accessible-interface-to-the-phenome-wide-association-study</link>
	<title><![CDATA[PheWAS: R package is designed to provide an accessible interface to the phenome wide association study]]></title>
	<description><![CDATA[<p>The PheWAS R package is designed to provide an accessible interface to the phenome wide association study. For a description of the methods available and some simple examples, please see the&nbsp;<a href="https://github.com/PheWAS/PheWAS/blob/master/inst/doc/PheWAS-package.pdf?raw=true">package vignette</a>&nbsp;or the R documentation. For installation help, see below. ##Installing the PheWAS Package The PheWAS package can be installed using the devtools package. The following code when executed in R will get you started:</p>
<pre><code>install.packages("devtools")
#It may be necessary to install required as not all package dependencies are installed by devtools:
install.packages(c("dplyr","tidyr","ggplot2","MASS","meta","ggrepel","DT"))
devtools::install_github("PheWAS/PheWAS")
library(PheWAS)</code></pre><p>Address of the bookmark: <a href="https://github.com/PheWAS/PheWAS" rel="nofollow">https://github.com/PheWAS/PheWAS</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</guid>
	<pubDate>Tue, 03 May 2016 05:31:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27225/painless-package-development-for-r</link>
	<title><![CDATA[Painless package development for R]]></title>
	<description><![CDATA[<p>Devtools makes package development a breeze: it works with R&rsquo;s existing conventions for code structure, adding efficient tools to support the cycle of package development. With devtools, developing a package becomes so easy that it will be your default layout whenever you&rsquo;re writing a significant amount of code.</p>
<p>Before you get started be sure to check out:</p>
<ul>
<li><a href="https://groups.google.com/forum/#%21forum/rdevtools" title="Google devtools Group">devtools Google Group &ndash;&nbsp;https://groups.google.com/forum/#!forum/rdevtools</a></li>
<li><a href="http://adv-r.had.co.nz/" title="Hadley W Online Book">book on &ldquo;Advanced R programming&rdquo; &ndash;&nbsp;http://adv-r.had.co.nz/</a></li>
<li><a href="https://github.com/hadley/devtools" title="devtools GitHub">GitHub repository &ndash;&nbsp;https://github.com/hadley/devtools</a></li>
</ul>
<h3 id="getting_started">&nbsp;</h3><p>Address of the bookmark: <a href="https://www.rstudio.com/products/rpackages/devtools/" rel="nofollow">https://www.rstudio.com/products/rpackages/devtools/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</guid>
	<pubDate>Sun, 04 Feb 2018 14:28:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35437/dupradar-package</link>
	<title><![CDATA[dupRadar package]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><em>dupRadar</em><span>&nbsp;package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance</span></p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html" rel="nofollow">https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</guid>
	<pubDate>Sun, 09 Feb 2020 12:41:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40964/panev-an-r-package-for-a-pathway-based-network-visualization</link>
	<title><![CDATA[PANEV: an R package for a pathway-based network visualization]]></title>
	<description><![CDATA[<p><span>PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to&nbsp;</span><em>n</em><span>) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes.</span></p>
<p><span><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7</a></span></p><p>Address of the bookmark: <a href="https://github.com/vpalombo/PANEV" rel="nofollow">https://github.com/vpalombo/PANEV</a></p>]]></description>
	<dc:creator>Jit</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>

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