<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44414?offset=10</link>
	<atom:link href="https://bioinformaticsonline.com/related/44414?offset=10" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps</guid>
	<pubDate>Thu, 27 Dec 2018 19:45:52 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38541/geneoverlap-an-r-package-to-test-and-visualize-gene-overlaps</link>
	<title><![CDATA[GeneOverlap: An R package to test and visualize gene overlaps]]></title>
	<description><![CDATA[<p>Overlapping gene lists can reveal biological meanings and may lead to novel hypotheses. For example, histone modification is an important cellular mechanism that can pack and re-pack chromatin. By making the chromatin structure more dense or loose, the gene expression can be turned on or off. Tri-methylation on lysine 4 of histone H3 (H3K4me3) is associated with gene activation and its genome-wide enrichment can be mapped by using ChIP-seq experiments. Because of its activating role, if we overlap the genes that are bound by H3K4me3 with the genes that are highly expressed, we should expect a positive association. Similary, we can perform such kind of overlapping between the gene lists of different histone modifications with that of various expression groups and establish each histone modification&rsquo;s role in gene regulation.</p><p>Address of the bookmark: <a href="https://bioconductor.org/packages/release/bioc/vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf" rel="nofollow">https://bioconductor.org/packages/release/bioc/vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf</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/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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</guid>
	<pubDate>Thu, 16 Jun 2016 18:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler</link>
	<title><![CDATA[clusterProfiler]]></title>
	<description><![CDATA[<p>statistical analysis and visulization of functional profiles for genes and gene clusters<br><br>Bioconductor version: Release (3.3)<br><br>This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.<br><br>Author: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt; with contributions from Li-Gen Wang and Giovanni Dall'Olio.<br><br>Maintainer: Guangchuang Yu &lt;guangchuangyu at gmail.com&gt;<br><br>Citation (from within R, enter citation("clusterProfiler")):<br><br>Yu G, Wang L, Han Y and He Q (2012). &ldquo;clusterProfiler: an R package for comparing biological themes among gene clusters.&rdquo; OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.<br>Installation<br><br>To install this package, start R and enter:<br><br>## try http:// if https:// URLs are not supported<br>source("https://bioconductor.org/biocLite.R")<br>biocLite("clusterProfiler")</p>
<p>https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</guid>
	<pubDate>Tue, 17 Sep 2024 02:34:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44663/svbyeye-r-package-to-visualize-alignments-between-two-or-multiple-dna-sequences</link>
	<title><![CDATA[SVbyEye: R Package to visualize alignments between two or multiple DNA sequences]]></title>
	<description><![CDATA[<p dir="auto">R Package to visualize alignments between two or multiple DNA sequences including<br>a number of functionalities to facilitate processing of alignments in PAF format.</p>
<p dir="auto"><span>SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process alignments in PAF format. The tool facilitates the characterization of complex SVs in the context of sequence homology helping resolve the mechanisms underlying their formation. Availability and implementation SVbyEye is available at https://github.com/daewoooo/SVbyEye.</span></p>
<p dir="auto">Author: David Porubsky</p><p>Address of the bookmark: <a href="https://github.com/daewoooo/SVbyEye" rel="nofollow">https://github.com/daewoooo/SVbyEye</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<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/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</guid>
	<pubDate>Sat, 01 Feb 2020 13:38:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40814/accesssyri-finding-genomic-rearrangements-and-local-sequence-differences-from-whole-genome-assemblies</link>
	<title><![CDATA[AccessSyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies]]></title>
	<description><![CDATA[<p><span>Access</span><span>SyRI: finding genomic rearrangements and</span><span>local sequence differences from whole-</span><span>genome assemblies</span><span><br></span></p>
<p><span><span>SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.</span></span></p>
<p><span><a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0</a></span></p><p>Address of the bookmark: <a href="https://github.com/schneebergerlab/syri" rel="nofollow">https://github.com/schneebergerlab/syri</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41169/instructions-for-creating-your-own-r-package</guid>
	<pubDate>Wed, 19 Feb 2020 01:22:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41169/instructions-for-creating-your-own-r-package</link>
	<title><![CDATA[Instructions for Creating Your Own R Package]]></title>
	<description><![CDATA[<p>The following is a step-by-step guide to creating your own R package.&nbsp; Even beyond this course, youmay find this useful for storing functions you create for your own research or for editing existingR packages to suit your needs.</p>
<p>This guide contains three different sets of instructions.&nbsp; If you use RStudio, you can follow the &ldquo;Ba-sic Instructions&rdquo; in Section 2 which involve using RStudio&rsquo;s interface.&nbsp; </p><p>Address of the bookmark: <a href="http://web.mit.edu/insong/www/pdf/rpackage_instructions.pdf" rel="nofollow">http://web.mit.edu/insong/www/pdf/rpackage_instructions.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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