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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/14024?offset=10</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</guid>
	<pubDate>Sat, 27 Dec 2014 06:50:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</link>
	<title><![CDATA[RStudio]]></title>
	<description><![CDATA[<p>RStudio IDE is a powerful and productive user interface for R. It&rsquo;s free and open source, and works great on Windows, Mac, and Linux.</p>
<p>The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.</p>
<p>More at http://www.rstudio.com/</p>
<p>http://www.rstudio.com/products/RStudio/</p><p>Address of the bookmark: <a href="http://www.rstudio.com/" rel="nofollow">http://www.rstudio.com/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</guid>
	<pubDate>Wed, 18 Feb 2015 00:43:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21312/r-for-microsoft-excel</link>
	<title><![CDATA[R for Microsoft Excel]]></title>
	<description><![CDATA[<div><p>If you currently use a spreadsheet like Microsoft Excel for data analysis, you might be interested in taking a look at this <a href="https://districtdatalabs.silvrback.com/intro-to-r-for-microsoft-excel-users" target="_blank">tutorial on how to transition from Excel to R</a>&nbsp;by Tony Ojeda. The tutorial explains how to use R functions in place of Excel formulas, including tools like =AVERAGE and =VLOOKUP. For the most part, it uses modern R packages to keep the R code clear and concise.</p><p>You'll likely still be using Excel as a data source, though, so you'll also want to check out this <a href="http://www.milanor.net/blog/?p=779" target="_blank">guide to importing data from Excel to R</a> from MilanoR.</p></div><p>Reference http://www.r-bloggers.com/an-r-tutorial-for-microsoft-excel-users/</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21367/a-guide-for-complete-r-beginners-r-syntax</guid>
	<pubDate>Fri, 20 Feb 2015 23:41:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21367/a-guide-for-complete-r-beginners-r-syntax</link>
	<title><![CDATA[A guide for complete R beginners :- R Syntax]]></title>
	<description><![CDATA[<p>R is a functional based language, the inputs to a function, including options, are in brackets. Note that all dat and options are separated by a comma</p><ul>
<li>Function(data, options)</li>
</ul><p>Even quit is a function</p><ul>
<li>q()</li>
</ul><p>So is help</p><blockquote><p><strong>help(read.table)</strong></p></blockquote><p>Provides the help page for the FUNCTION &lsquo;read.table&rsquo;</p><blockquote><p><strong>help.search(&ldquo;t test&rdquo;)</strong></p></blockquote><p>Searches for help pages that might relate to the phrase &lsquo;t test&rsquo;</p><p><strong>NOTE</strong>: quotes are needed for search strings, they are not needed when referring to data objects or function names.</p><p>There is a short cut for help,</p><p>? shows the help page on a function name, same as <em>help(function)</em></p><blockquote><p><strong>?read.table</strong></p></blockquote><p>?? searches for help pages on functions, same as <em>help.search(&lsquo;phrase&rsquo;)</em></p><blockquote><p><strong>??&ldquo;t test&rdquo;</strong></p></blockquote><p>Information is usually returned from a function, by default this is printed to screen</p><blockquote><p><strong>read.table(&lsquo;data.tsv&rsquo;)</strong></p></blockquote><p>This can always be stored, we call what it is stored in an &lsquo;object&rsquo;</p><p><strong>mydata </strong></p><p>here <strong>mydata</strong> is an object of type <span style="text-decoration: underline;">dataframe</span></p><p><strong>Reminder:</strong></p><ul>
<li>Vector: a list of numbers, equivalent to a column in a table</li>
<li>Data Frame = a collection of vectors. Equivalent to a table</li>
</ul><p><strong>Hint</strong>:</p><ul>
<li>Up/Down arrow keys can be use to cycle through previous commands</li>
</ul>]]></description>
	<dc:creator>Archana Malhotra</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/29635/r-graphs</guid>
	<pubDate>Fri, 04 Nov 2016 10:48:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29635/r-graphs</link>
	<title><![CDATA[R Graphs !!]]></title>
	<description><![CDATA[<p><span>The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!</span></p><p>Address of the bookmark: <a href="http://rgraphgallery.blogspot.be/" rel="nofollow">http://rgraphgallery.blogspot.be/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32152/upsetr-shiny-app</guid>
	<pubDate>Fri, 14 Apr 2017 06:19:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32152/upsetr-shiny-app</link>
	<title><![CDATA[UpSetR Shiny App!]]></title>
	<description><![CDATA[<p>UpSetR generates static&nbsp;<a href="http://vcg.github.io/upset/?dataset=0&amp;duration=1000&amp;orderBy=subsetSize&amp;grouping=groupByIntersectionSize&amp;selection=">UpSet plots</a>. 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>
<h4>To begin, input your data using one of the three input styles.</h4>
<ol>
<li>"File" takes a correctly formatted.csv file.</li>
<li>"List" takes up to 6 different lists that contain unique elements, similar to that used in the web applications BioVenn&nbsp;<a href="http://www.biomedcentral.com/content/pdf/1471-2164-9-488.pdf">(Hulsen et al., 2008)</a>&nbsp;and jvenn&nbsp;<a href="http://www.biomedcentral.com/content/pdf/1471-2105-15-293.pdf">(Bardou et al., 2014)</a></li>
<li>"Expression" takes the input used by the venneuler R package&nbsp;<a href="https://cran.r-project.org/web/packages/venneuler/venneuler.pdf">(Wilkinson, 2015)</a></li>
</ol><p>Address of the bookmark: <a href="https://gehlenborglab.shinyapps.io/upsetr/" rel="nofollow">https://gehlenborglab.shinyapps.io/upsetr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1720/postdoctoral-associate-bioinformatics-at-duke-university-medical-center</guid>
  <pubDate>Sat, 10 Aug 2013 18:38:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Associate - Bioinformatics  at Duke University Medical Center]]></title>
  <description><![CDATA[
<p>The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.</p>

<p>Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.</p>

<p>This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.</p>

<p>For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.</p>

<p>For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf</p>

<p>Duke University is an Equal Opportunity/Affirmative Action Employer.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2457/rdataminingcom-r-and-data-mining</guid>
	<pubDate>Thu, 15 Aug 2013 18:37:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2457/rdataminingcom-r-and-data-mining</link>
	<title><![CDATA[Rdatamining.com : R and Data Mining]]></title>
	<description><![CDATA[<p>This website presents examples, documents and resources on data mining with R. <br>Documents on using R for data mining are available to download for non-commercial personal use, including&nbsp;R Reference card for Data Mining, R and Data Mining: Examples and Case Studies and Time Series Analysis and Mining with R.</p><p>Address of the bookmark: <a href="http://www.rdatamining.com/" rel="nofollow">http://www.rdatamining.com/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</guid>
	<pubDate>Tue, 11 Jun 2019 21:27:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/39606/amity-university-bioinformatics-summer-program-kolkata</link>
	<title><![CDATA[Amity University Bioinformatics Summer Program - Kolkata]]></title>
	<description><![CDATA[<p>Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.</p><p>Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/</p>]]></description>
	<dc:creator>eliabrodsky</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40272/seq-a-high-performance-pythonic-language-for-bioinformatics</guid>
	<pubDate>Sat, 23 Nov 2019 08:58:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40272/seq-a-high-performance-pythonic-language-for-bioinformatics</link>
	<title><![CDATA[Seq: A high-performance, Pythonic language for bioinformatics]]></title>
	<description><![CDATA[<p>&nbsp;</p>
<p>Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.</p>
<p>Learn more by following the&nbsp;<a href="https://github.com/seq-lang/seq/blob/master/docs/sphinx/tutorial.rst">tutorial</a>&nbsp;or from the&nbsp;<a href="https://github.com/seq-lang/seq/blob/master/docs/sphinx/cookbook.rst">cookbook</a>.</p><p>Address of the bookmark: <a href="https://seq-lang.org" rel="nofollow">https://seq-lang.org</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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