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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/21241?offset=1360</link>
	<atom:link href="https://bioinformaticsonline.com/related/21241?offset=1360" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34585/r-googlevis-examples</guid>
	<pubDate>Sun, 10 Dec 2017 06:13:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34585/r-googlevis-examples</link>
	<title><![CDATA[R googleVis examples]]></title>
	<description><![CDATA[<p>It may take a little while to load all charts. Please be patient. All charts require an Internet connection.</p>
<p>These examples are taken from the googleVis demo. You can execute the demo via</p>
<pre><code><span>library</span><span>(</span><span>googleVis</span><span>)</span>
<span>demo</span><span>(</span><span>googleVis</span><span>)</span>
</code></pre>
<p>For more details about the charts and further examples see the helpfiles of the individual googleVis function and review the&nbsp;<a href="https://developers.google.com/chart/interactive/docs/gallery">Google Charts API documentation</a>&nbsp;and&nbsp;<a href="https://developers.google.com/terms">Terms of Service</a>.</p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html" rel="nofollow">https://cran.r-project.org/web/packages/googleVis/vignettes/googleVis_examples.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</guid>
	<pubDate>Sun, 09 Dec 2018 19:06:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38385/decipher-a-software-toolset-for-deciphering-and-managing-biological-sequences-efficiently-using-the-r</link>
	<title><![CDATA[DECIPHER; a software toolset for deciphering and managing biological sequences efficiently using the R]]></title>
	<description><![CDATA[<p><span>DECIPHER is a software toolset that can be used for deciphering and managing biological sequences efficiently using the&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;programming language. The&nbsp;</span><a href="http://www.r-project.org/">R</a><span>&nbsp;package is distributed as platform independent source code under the&nbsp;</span><a href="http://www.gnu.org/copyleft/gpl.html">GPL version 3 license</a><span>. Some functionality of the program is accessible online through web tools.</span></p>
<p><span style="font-size: medium; text-align: justify;">&nbsp;</span></p><p>Address of the bookmark: <a href="http://www2.decipher.codes/" rel="nofollow">http://www2.decipher.codes/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</guid>
	<pubDate>Tue, 17 Sep 2019 23:01:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39947/radar-charts-with-ggplot2</link>
	<title><![CDATA[radar charts with ggplot2]]></title>
	<description><![CDATA[<p><code>ggradar</code>&nbsp;allows you to build radar charts with ggplot2. This package is based on&nbsp;<a href="http://rstudio-pubs-static.s3.amazonaws.com/5795_e6e6411731bb4f1b9cc7eb49499c2082.html">Paul Williamson&rsquo;s</a>&nbsp;code, with new aesthetics and compatibility with ggplot2 2.0.</p>
<p>It was inspired by&nbsp;<a href="http://www.buildingwidgets.com/blog/2015/12/9/week-49-d3radarr">d3radaR</a>, an htmlwidget built by&nbsp;<a href="https://github.com/timelyportfolio">timelyportfolio</a>.</p><p>Address of the bookmark: <a href="https://github.com/ricardo-bion/ggradar" rel="nofollow">https://github.com/ricardo-bion/ggradar</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</guid>
	<pubDate>Tue, 21 Jan 2020 04:22:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40583/trelliscope-flexibly-visualize-large-complex-data-in-great-detail-from-within-the-r-statistical-programming-environment</link>
	<title><![CDATA[Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.]]></title>
	<description><![CDATA[<p>Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the<span>&nbsp;</span><a href="http://deltarho.org/docs-trelliscope/deltarho.org">DeltaRho</a><span>&nbsp;</span>environment.</p>
<p>For those familiar with<span>&nbsp;</span><a href="http://cm.bell-labs.com/cm/ms/departments/sia/project/trellis/">Trellis Display</a>,<span>&nbsp;</span><a href="http://docs.ggplot2.org/0.9.3.1/facet_wrap.html">faceting in ggplot</a>, or the notion of<span>&nbsp;</span><a href="http://en.wikipedia.org/wiki/Small_multiple">small multiples</a>, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.</p><p>Address of the bookmark: <a href="http://deltarho.org/docs-trelliscope/#introduction" rel="nofollow">http://deltarho.org/docs-trelliscope/#introduction</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</guid>
	<pubDate>Fri, 28 Feb 2020 23:27:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model</link>
	<title><![CDATA[RAINBOWR: Reliable Association INference By Optimizing Weights with R (R package for SNP-set GWAS and multi-kernel mixed model)]]></title>
	<description><![CDATA[<p><code>RAINBOWR</code>(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of <code>GWAS</code> as follows.</p>
<ul>
<li>Single-SNP GWAS with <code>RGWAS.normal</code> function</li>
<li>SNP-set (or gene set) GWAS with <code>RGWAS.multisnp</code> function (which tests multiple SNPs at the same time)</li>
<li>Check epistatic (SNP-set x SNP-set interaction) effects with <code>RGWAS.epistasis</code> (very slow and less reliable)</li>
</ul>
<p>https://github.com/KosukeHamazaki/RAINBOWR</p>
<p>https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663</p>
<p>https://cran.r-project.org/web/packages/RAINBOWR/index.html</p><p>Address of the bookmark: <a href="https://github.com/KosukeHamazaki/RAINBOWR" rel="nofollow">https://github.com/KosukeHamazaki/RAINBOWR</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43546/introduction-to-phylogenies-in-r</guid>
	<pubDate>Wed, 13 Oct 2021 02:27:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43546/introduction-to-phylogenies-in-r</link>
	<title><![CDATA[Introduction to phylogenies in R]]></title>
	<description><![CDATA[<p><span>R phylogenetics is built on the contributed packages for phylogenetics in R, and there are many such packages. Let's begin today by installing a few critical packages, such as ape, phangorn, phytools, and geiger. To get the most recent CRAN version of these packages, you will need to have R 3.3.x installed on your computer!</span></p><p>Address of the bookmark: <a href="http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html" rel="nofollow">http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44648/modern-statistics-with-r</guid>
	<pubDate>Thu, 22 Aug 2024 04:44:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44648/modern-statistics-with-r</link>
	<title><![CDATA[Modern Statistics with R]]></title>
	<description><![CDATA[<p>This is the online version of the second edition of&nbsp;<em>Modern Statistics with R</em>. It is free to use, and always will be.&nbsp;<a href="https://www.routledge.com/Modern-Statistics-with-R-From-Wrangling-and-Exploring-Data-to-Inference-and-Predictive-Modelling/Thulin/p/book/9781032512440">Printed copies</a>&nbsp;are available from CRC Press.</p>
<p><span>Live&nbsp;<a href="https://statistikakademin.se/in-english-r/">online courses on statistics with R</a></span>&nbsp;based on this book, led by the author, are offered regularly; see&nbsp;<a href="https://statistikakademin.se/in-english-r/">this page</a>&nbsp;for more information and dates.</p>
<p>The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of&nbsp;<em>Modern Statistics with R</em>&nbsp;is to introduce you to key parts of the modern statistical toolkit. It teaches you:</p>
<ul>
<li><span>Data wrangling</span>&nbsp;- importing, formatting, reshaping, merging, and filtering data in R.</li>
<li><span>Exploratory data analysis</span>&nbsp;- using visualisations and multivariate techniques to explore datasets.</li>
<li><span>Statistical inference</span>&nbsp;- modern methods for testing hypotheses and computing confidence intervals.</li>
<li><span>Predictive modelling</span>&nbsp;- regression models and machine learning methods for prediction, classification, and forecasting.</li>
<li><span>Simulation</span>&nbsp;- using simulation techniques for sample size computations and evaluations of statistical methods.</li>
<li><span>Ethics in statistics</span>&nbsp;- ethical issues and good statistical practice.</li>
<li><span>R programming</span>&nbsp;- writing code that is fast, readable, and (hopefully!) free from bugs.</li>
</ul>
<p>The book includes plenty of examples and more than 200 exercises with worked solutions.&nbsp;<a href="http://www.modernstatisticswithr.com/data.zip">The datasets used for the examples and the exercises can be downloaded here.</a></p><p>Address of the bookmark: <a href="https://www.modernstatisticswithr.com/" rel="nofollow">https://www.modernstatisticswithr.com/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17505/kau-thrissur-biotechbioinformatics-rasrfjrftraineestudentships</guid>
  <pubDate>Fri, 26 Sep 2014 20:07:28 -0500</pubDate>
  <link></link>
  <title><![CDATA[KAU Thrissur Biotech/Bioinformatics RA/SRF/JRF/Trainee/Studentships]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates for the following posts at Bioinformatics Centre (DIC), IT- BT Complex, College of Horticulture, Kerala Agricultural University, Vellanikkara, Thrissur.</p>

<p>1. Research Associate <br />Emoluments*: 14880/- + HRA 	<br />Qualification needed: Ph.D/M.Sc in Bioinformatics or Ph.D/M.Sc in Agriculture or Biotechnology with advanced Diploma in Bioinformatics <br />Desirable: 2 year experience in Bioinformatics.</p>

<p>2 Senior Research Fellow <br />Emoluments*: 10230/- 	<br />Qualification needed: M.Sc/ M.tech in Bioinformatics or M.Sc in Agriculture/ Biotechnology with Diploma in Bioinformatics. <br />Desirable: One year experience in Bioinformatics</p>

<p>3 Junior Research Fellow <br />Emoluments*: 9300/- 	<br />Qualification needed: M.Sc/ M.tech in Bioinformatics or M.Sc in Agriculture/Biotechnology/Plant Sciences with Diploma in Bioinformatics.</p>

<p>4 .Trainee/Studentship Bioinformatics <br />Emoluments*: 5000/- 	<br />Qualification needed: M.Sc in Bioinformatics with good knowledge of Bioinformatics softwares and tools.</p>

<p>5 Trainee/ Studentship Biotechnology <br />Emoluments*: 5000/- 	<br />Qualification needed: M.Sc in Biotechnology, with working knowledge in tissue culture, molecular markers and cloning of genes.</p>

<p>Candidates with the required qualifications and experience may give an application in the prescribed format with attested copies of certificates to prove eligibility on or before 30th November 2014. The applications are to be addressed to The Associate Dean, College of Horticulture and send to "Professor &amp; Coordinator, Bioinformatics Centre (DIC), IT-BT Complex, Kerala Agricultural University, Vellanikkara, Thrissur, Kerala 680 656”. The envelope may be superscribed “Application for the post at Bioinformatics Centre”.</p>

<p>*Emoluments are likely to be revised in 2014-2015</p>

<p>More at http://www.kaubic.in/downloads/Notification_bic.pdf<br />http://www.kaubic.in/downloads/Application%20form.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</guid>
	<pubDate>Mon, 06 Oct 2014 12:41:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17924/software-developed-in-pevsner-lab</link>
	<title><![CDATA[Software developed in pevsner lab]]></title>
	<description><![CDATA[<div>
<div id="block-system-main">
<div>
<div id="node-7">
<div>
<div>
<div>
<div>
<p><a href="http://pevsnerlab.kennedykrieger.org/dragon.htm">DRAGON</a>: Database Referencing of Array Genes Online</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/96">SNOMAD</a>: Standardization and Normalization of Microarray Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/70">SNPduo</a>: SNP Analysis Between Two Individuals</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/71">SNPtrio</a>: Analyzing and Visualizing and Inheritance Patterns in Trios</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">SNPscan</a>: Data Analysis and Visualization of SNP Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/64">pediSNP</a>: Analyze SNP Data From a Pedigree of Two Generations</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/73">kcoeff</a>: Calculate Cotterman Coefficients of SNP Genotype Data</p>
<p><a href="http://pevsnerlab.kennedykrieger.org/php/node/113">triPOD:</a> Detects chromosomal abnormalities in parent-child trio-based microarray data</p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div><p>Address of the bookmark: <a href="http://pevsnerlab.kennedykrieger.org/php/?q=software" rel="nofollow">http://pevsnerlab.kennedykrieger.org/php/?q=software</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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