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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38819?offset=30</link>
	<atom:link href="https://bioinformaticsonline.com/related/38819?offset=30" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</guid>
	<pubDate>Wed, 12 Feb 2020 12:40:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis</link>
	<title><![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]></title>
	<description><![CDATA[<p>netGO is an R/Shiny package for network-integrated pathway enrichment analysis.<br>netGO provides user-interactive visualization of enrichment analysis results and related networks.</p>
<p>Currently, netGO supports analysis for four species (<em><a href="https://github.com/unistbig/netGO-Data/tree/master/Human">Human</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Mouse">Mouse</a>,&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Arabidopsis">Arabidopsis thaliana</a>,and&nbsp;<a href="https://github.com/unistbig/netGO-Data/tree/master/Yeast">Yeast</a></em>)<br>These data are available from&nbsp;<a href="https://github.com/unistbig/netGO-Data">netGO-Data</a>&nbsp;repository.</p>
<p><a href="https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635">https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635</a></p><p>Address of the bookmark: <a href="https://github.com/unistbig/netGO" rel="nofollow">https://github.com/unistbig/netGO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</guid>
	<pubDate>Fri, 04 Mar 2022 00:14:11 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43815/kebabs-package-provides-functionality-for-kernel-based-analysis-of-biological-sequences-via-support-vector-machine-svm-based-methods</link>
	<title><![CDATA[kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods]]></title>
	<description><![CDATA[<p><span>The&nbsp;</span><tt>kebabs</tt><span>&nbsp;package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.</span></p>
<p>http://www.bioinf.jku.at/software/kebabs/</p>
<p>http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf</p><p>Address of the bookmark: <a href="http://www.bioinf.jku.at/software/kebabs/" rel="nofollow">http://www.bioinf.jku.at/software/kebabs/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/120/user</guid>
	<pubDate>Wed, 10 Jul 2013 14:41:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/120/user</link>
	<title><![CDATA[useR!]]></title>
	<description><![CDATA[<p><span>The R project actively supports two conference series, organized regularly by members from the R community: useR! - providing a forum to the R user community - and DSC - a platform for developers of statistical software.</span></p><p><span>Recently useR! conference have been organized&nbsp;<span>University of Castilla-La Mancha, Albacete, Spain.</span></span></p><p><a href="http://www.edii.uclm.es/~useR-2013//">http://www.edii.uclm.es/~useR-2013//</a></p><p>&nbsp;</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</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/8848/upgrade-r-303</guid>
	<pubDate>Mon, 10 Mar 2014 11:23:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/8848/upgrade-r-303</link>
	<title><![CDATA[Upgrade R 3.0.3]]></title>
	<description><![CDATA[<p>R is a free software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls and surveys of data miners are showing R's popularity has increased substantially in recent years. Recently the new version of R codename &ldquo;Warm Puppy" have been released.<br /><br />You can download the latest version from here http://cran.rstudio.com/ . Or, if you are using Windows, you can upgrade to the latest version using the installr package http://cran.r-project.org/web/packages/installr/ . Simply run the following code:<br /><br /># installing/loading the package:<br />if(!require(installr)) { <br />install.packages("installr"); require(installr)} #load / install+load installr<br />&nbsp;<br />updateR()<br /><br />I try to keep the installr package updated and useful. If you have any suggestions or remarks on the package, you&rsquo;re invited to leave a comment below.<br /><br />If you use the global library system http://www.r-statistics.com/2010/04/changing-your-r-upgrading-strategy-and-the-r-code-to-do-it-on-windows/ , you can run the following in the new version of R:<br /><br />source("http://www.r-statistics.com/wp-content/uploads/2010/04/upgrading-R-on-windows.r.txt")<br />New.R.RunMe()</p><p>Reference:</p><p>http://www.r-statistics.com/2014/03/r-3-0-3-is-released/</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/18738/surrogate-variable-analysis-sva</guid>
	<pubDate>Thu, 30 Oct 2014 08:01:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/18738/surrogate-variable-analysis-sva</link>
	<title><![CDATA[Surrogate Variable Analysis (SVA)]]></title>
	<description><![CDATA[<p>The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in three ways:</p><p>(1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS),</p><p>(2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics) and</p><p>(3) removing batch effects with known control probes (Leek 2014 biorXiv).</p><p>Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics).</p><p>More at http://www.bioconductor.org/packages/release/bioc/html/sva.html</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners</guid>
	<pubDate>Fri, 20 Feb 2015 23:36:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners</link>
	<title><![CDATA[A guide for complete R beginners !]]></title>
	<description><![CDATA[<p>This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that &nbsp;biologists need to perform &nbsp;some basic analysis: &nbsp;load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).</p><p><em><span style="text-decoration: underline;">R-language: </span></em><a href="http://www.r-project.org/"><span style="color: #000080;"><span style="text-decoration: underline;"><em>http://www.</em></span></span><span style="color: #000080;"><span style="text-decoration: underline;"><em><strong>r</strong></em></span></span><span style="color: #000080;"><span style="text-decoration: underline;"><em>-project.org</em></span></span></a></p><p><em>BioConductor</em>:&nbsp;<a href="http://www.bioconductor.org/">http://www.bioconductor.org</a></p><p><strong>Advantages of R</strong></p><ul>
<li>Free!</li>
<li>Powerful, many libraries have been created to perform application specific tasks. e.g. analysis of microarray experiments and Next-Gen sequencing (bioconductor: including Bioseq group).</li>
<li>Presentation quality graphics
<ul>
<li>Save as a png, pdf or svg</li>
</ul>
</li>
<li>History
<ul>
<li>What you do can be saved for the next time you use R.</li>
<li>Ability to turn it into an automated script to perform again and again on different data</li>
</ul>
</li>
</ul><p><strong>Disadvantages</strong></p><ul>
<li>Lack of a comprehensive graphical user interface, but two do exist: However some do exist:&nbsp;R commander: <a href="http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/">http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/</a> and&nbsp;Limma-gui (microarrays) : <a href="http://bioinf.wehi.edu.au/limmaGUI/">http://bioinf.wehi.edu.au/limmaGUI/</a></li>
</ul><p><strong>Preparation</strong></p><ul>
<li>(Optional) Download and save the tutorial data set from
<ul>
<li>http://bioinformatics.knowledgeblog.org/wp-content/uploads/bioinf/kerr/data.tsv</li>
<li>Start R (type R on a Linux or Mac terminal, or find the starting link from PC)</li>
</ul>
</li>
</ul><p><strong>Getting More Help</strong></p><ul>
<li>Project Home page
<ul>
<li><span style="color: #000080;"><span style="text-decoration: underline;"><a href="http://www.r-project.org/">http://www.r-project.org/</a></span></span></li>
<li>Check out the &lsquo;introduction to R&rsquo;, which is a much more in depth guide .</li>
<li>Also R has a built-in help system (see later)</li>
</ul>
</li>
</ul><p><strong>Working directory</strong></p><p>This is the directory used to store your data and results. It is useful if it is also the directory where your input data is stored.</p><ul>
<li>Mac/Linux: this is the directory where you typed in R</li>
<li>PC: Change using the change working directory option</li>
</ul>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22133/r-320-is-released</guid>
	<pubDate>Sat, 18 Apr 2015 05:06:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22133/r-320-is-released</link>
	<title><![CDATA[R 3.2.0 is released]]></title>
	<description><![CDATA[<p>R 3.2.0 (codename &ldquo;Full of Ingredients&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-2-0-is-released-td4705933.html" target="_blank">released yesterday</a>.&nbsp;You can get the latest binaries version <strong><a href="http://cran.rstudio.com/" target="_blank">from here</a>.</strong>&nbsp;(or the .tar.gz&nbsp;<strong>source</strong> code from <a href="http://cran.r-project.org/src/base/R-3/R-3.2.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><h3>Upgrading to R 3.2.0 on Windows</h3><p>If you are using <strong>Windows&nbsp;</strong>you can easily upgrade to the latest version of R using <a href="http://cran.r-project.org/web/packages/installr/" target="_blank">the installr package</a>. Simply run the following code:</p><div><table>
<tbody>
<tr id="p612572">
<td id="p61257code2">
<pre><span style="color: #228b22;"># installing/loading the latest installr package:</span>
<span style="color: #0000ff; font-weight: bold;">install.<span>packages</span></span><span style="color: #080;">(</span><span style="color: #ff0000;">"installr"</span><span style="color: #080;">)</span><span style="color: #080;">;</span> <span style="color: #0000ff; font-weight: bold;">library</span><span style="color: #080;">(</span>installr<span style="color: #080;">)</span> <span style="color: #228b22;">#load / install+load installr</span>
&nbsp;
updateR<span style="color: #080;">(</span><span style="color: #080;">)</span> <span style="color: #228b22;"># updating R.</span></pre>
</td>
</tr>
</tbody>
</table></div><p><span>Running &ldquo;updateR()&rdquo; will detect if there is a new R version available, and if so it will download+install it (etc.).</span></p><p><span><strong>If you are an R blogger yourself</strong> you are invited to <a href="http://www.r-bloggers.com/add-your-blog/">add your own R content feed to this site</a> (<strong>Non-English</strong> R bloggers should add themselves- <a href="http://www.r-bloggers.com/lang/add-your-blog">here</a>)</span></p><h4>NEW FEATURES</h4><ul>
<li><code>anyNA()</code> gains a <code>recursive</code> argument.</li>
<li>When <code>x</code> is missing and <code>names</code> is not false (including the default value), <code>Sys.getenv(x, names)</code> returns an object of class <code>"Dlist"</code> and hence prints tidily.</li>
<li>(Windows.) <code>shell()</code> no longer consults the environment variable <span>SHELL</span>: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). <span>R_SHELL</span>, the preferred way to select a non-default shell, can be used instead.</li>
<li>Some unusual arguments to <code>embedFonts()</code> can now be specified as character vectors, and the defaults have been changed accordingly.</li>
<li>Functions in the <code>Summary</code> group duplicate less. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15798" target="_blank">PR#15798</a>)</li>
<li>(Unix-alikes.) <code>system(cmd, input = )</code> now uses &lsquo;shell-execution-environment&rsquo; redirection, which will be more natural if <code>cmd</code> is not a single command (but requires a POSIX-compliant shell). (Wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15508" target="_blank">PR#15508</a>)</li>
<li><code>read.fwf()</code> and <code>read.DIF()</code> gain a <code>fileEncoding</code> argument, for convenience.</li>
<li>Graphics devices can add attributes to their description in <code>.Device</code> and <code>.Devices</code>. Several of those included with <strong>R</strong> use a <code>"filepath"</code> attribute.</li>
<li><code>pmatch()</code> uses hashing in more cases and so is faster at the expense of using more memory. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15697" target="_blank">PR#15697</a>)</li>
<li><code>pairs()</code> gains new arguments to select sets of variables to be plotted against each other.</li>
<li><code>file.info(, extra_cols = FALSE)</code> allows a minimal set of columns to be computed on Unix-alikes: on some systems without properly-configured caching this can be significantly faster with large file lists.</li>
<li>New function <code>dir.exists()</code> in package <span>base</span> to test efficiently whether one or more paths exist and are directories.</li>
<li><code>dput()</code> and friends gain new controls <span>hexNumeric</span> and <span>digits17</span> which output double and complex quantities as, respectively, binary fractions (exactly, see <code>sprintf("%a")</code>) and as decimals with up to 17 significant digits.</li>
<li><code>save()</code>, <code>saveRDS()</code> and <code>serialize()</code> now support <code>ascii = NA</code> which writes ASCII files using <code>sprintf("%a")</code> for double/complex quantities. This is read-compatible with <code>ascii = TRUE</code> but avoids binary-&gt;decimal-&gt;binary conversions with potential loss of precision. Unfortunately the Windows C runtime&rsquo;s lack of C99 compliance means that the format cannot be read correctly there in <strong>R</strong> before 3.1.2.</li>
<li>The default for <code>formatC(decimal.mark =)</code> has been changed to be <code>getOption("OutDec")</code>; this makes it more consistent with <code>format()</code> and suitable for use in print methods, e.g. those for classes <code>"density"</code>, <code>"ecdf"</code>, <code>"stepfun"</code> and <code>"summary.lm"</code>.
<p><code>getOption("OutDec")</code> is now consulted by the print method for class <code>"kmeans"</code>, by <code>cut()</code>, <code>dendrogram()</code>, <code>plot.ts()</code> and <code>quantile()</code> when constructing labels and for the report from<code>legend(trace = TRUE)</code>.</p>
<p>(In part, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15819" target="_blank">PR#15819</a>.)</p>
</li>
<li><code>printNum()</code> and hence <code>format()</code> and <code>formatC()</code> give a warning if <code>big.mark</code> and <code>decimal.mark</code> are set to the same value (period and comma are not uncommonly used for each, and this is a check that conventions have not got mixed).</li>
<li><code>merge()</code> can create a result which uses long vectors on 64-bit platforms.</li>
<li><code>dget()</code> gains a new argument <code>keep.source</code> which defaults to <code>FALSE</code> for speed (<code>dput()</code> and <code>dget()</code> are most often used for data objects where this can make <code>dget()</code> many times faster).</li>
<li>Packages may now use a file of common macro definitions in their help files, and may import definitions from other packages.</li>
<li>A number of macros have been added in the new &lsquo;<span>share/Rd</span>&rsquo; directory for use in package overview help pages, and <code>promptPackage()</code> now makes use of them.</li>
<li><code>tools::parse_Rd()</code> gains a new <code>permissive</code> argument which converts unrecognized macros into text. This is used by <code>utils:::format.bibentry</code> to allow LaTeX markup to be ignored.</li>
<li><code>options(OutDec =)</code> can now specify a multi-byte character, e.g., <code>options(OutDec = "u00b7")</code> in a UTF-8 locale.</li>
<li><code>is.recursive(x)</code> is no longer true when <code>x</code> is an external pointer, a weak reference or byte code; the first enables <code>all.equal(x, x)</code> when <code>x .</code></li>
<li><code>ls()</code> (aka <code>objects()</code>) and <code>as.list.environment()</code> gain a new argument <code>sorted</code>.</li>
<li>The <code>"source"</code> attribute (which has not been added to functions by <strong>R</strong> since before <strong>R</strong> version 2.14.0) is no longer treated as special.</li>
<li>Function <code>returnValue()</code> has been added to give <code>on.exit()</code> code access to a function&rsquo;s return value for debugging purposes.</li>
<li><code>crossprod(x, y)</code> allows more matrix coercions when <code>x</code> or <code>y</code> are vectors, now equalling <code>t(x) %*% y</code> in these cases (also reported by Radford Neal). Similarly, <code>tcrossprod(x,y)</code> and <code>%*%</code> work in more cases with vector arguments.</li>
<li>Utility function <code>dynGet()</code> useful for detecting cycles, aka infinite recursions.</li>
<li>The byte-code compiler and interpreter include new instructions that allow many scalar subsetting and assignment and scalar arithmetic operations to be handled more efficiently. This can result in significant performance improvements in scalar numerical code.</li>
<li><code>apply(m, 2, identity)</code> is now the same as the matrix <code>m</code> when it has <em>named</em> row names.</li>
<li>A new function <code>debuggingState()</code> has been added, allowing to temporarily turn off debugging.</li>
<li><code>example()</code> gets a new optional argument <code>run.donttest</code> and <code>tools::Rd2ex()</code> a corresponding <code>commentDonttest</code>, with a default such that <code>example(..)</code> in help examples will run <code>donttest</code> code only if used interactively (a change in behaviour).</li>
<li><code>rbind.data.frame()</code> gains an optional argument <code>make.row.names</code>, for potential speedup.</li>
<li>New function <code>extSoftVersion()</code> to report on the versions of third-party software in use in this session. Currently reports versions of <code>zlib</code>, <code>bzlib</code>, the <code>liblzma</code> from <code>xz</code>, PCRE, ICU, TRE and the <code>iconv</code> implementation.
<p>A similar function <code>grSoftVersion()</code> in package <span>grDevices</span> reports on third-party graphics software.</p>
<p>Function <code>tcltk::tclVersion()</code> reports the Tcl/Tk version.</p>
</li>
<li>Calling <code>callGeneric()</code> without arguments now works with primitive generics to some extent.</li>
<li><code>vapply(x, FUN, FUN.VALUE)</code> is more efficient notably for large <code>length(FUN.VALUE)</code>; as extension of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16061" target="_blank">PR#16061</a>.</li>
<li><code>as.table()</code> now allows tables with one or more dimensions of length 0 (such as <code>as.table(integer())</code>).</li>
<li><code>names(x) now clears the names of call and <code>...</code> objects.</code></li>
<li><code>library()</code> will report a warning when an insufficient dependency version is masking a sufficient one later on the library search path.</li>
<li>A new <code>plot()</code> method for class <code>"raster"</code> has been added.</li>
<li>New <code>check_packages_in_dir_changes()</code> function in package <span>tools</span> for conveniently analyzing how changing sources impacts the check results of their reverse dependencies.</li>
<li>Speed-up from Peter Haverty for <code>ls()</code> and <code>methods:::.requirePackage()</code> speeding up package loading. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16133" target="_blank">PR#16133</a>)</li>
<li>New <code>get0()</code> function, combining <code>exists()</code> and <code>get()</code> in one call, for efficiency.</li>
<li><code>match.call()</code> gains an <code>envir</code> argument for specifying the environment from which to retrieve the <code>...</code> in the call, if any; this environment was wrong (or at least undesirable) when the<code>definition</code> argument was a function.</li>
<li><code>topenv()</code> has been made <code>.Internal()</code> for speedup, based on Peter Haverty&rsquo;s proposal in <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16140" target="_blank">PR#16140</a>.</li>
<li><code>getOption()</code> no longer calls <code>options()</code> in the main case.</li>
<li>Optional use of <code>libcurl</code> (version 7.28.0 from Oct 2012 or later) for Internet access:
<ul>
<li><code>capabilities("libcurl")</code> reports if this is available.</li>
<li><code>libcurlVersion()</code> reports the version in use, and other details of the <code>"libcurl"</code> build including which URL schemes it supports.</li>
<li><code>curlGetHeaders()</code> retrieves the headers for <code>http://</code>, <code>https://</code>, <code>ftp://</code> and <code>ftps://</code> URLs: analysis of these headers can provide insights into the &lsquo;existence&rsquo; of a URL (it might for example be permanently redirected) and is so used in <code>R CMD check --as-cran</code>.</li>
<li><code>download.file()</code> has a new optional method <code>"libcurl"</code> which will handle more URL schemes, follow redirections, and allows simultaneous downloads of multiple URLs.</li>
<li><code>url()</code> has a new method <code>"libcurl"</code> which handles more URL schemes and follows redirections. The default method is controlled by a new option <code>url.method</code>, which applies also to the opening of URLs <em>via</em> <code>file()</code> (which happens implicitly in functions such as <code>read.table</code>.)</li>
<li>When <code>file()</code> or <code>url()</code> is invoked with a <code>https://</code> or <code>ftps://</code> URL which the current method cannot handle, it switches to a suitable method if one is available.</li>
</ul>
</li>
<li>(Windows.) The DLLs &lsquo;<span>internet.dll</span>&rsquo; and &lsquo;<span>internet2.dll</span>&rsquo; have been merged. In this version it is safe to switch (repeatedly) between the internal and Windows internet functions within an <strong>R</strong>session.
<p>The Windows internet functions are still selected by flag <span>&ndash;internet2</span> or <code>setInternet2()</code>. This can be overridden for an <code>url()</code> connection <em>via</em> its new <code>method</code> argument.</p>
<p><code>download.file()</code> has new method <code>"wininet"</code>, selected as the default by <span>&ndash;internet2</span> or <code>setInternet2()</code>.</p>
</li>
<li><code>parent.env&lt;-</code> can no longer modify the parent of a locked namespace or namespace imports environment. Contributed by Karl Millar.</li>
<li>New function <code>isLoadedNamespace()</code> for readability and speed.</li>
<li><code>names(env)</code> now returns all the object names of an <code>environment</code> <code>env</code>, equivalently to <code>ls(env, all.names = TRUE, sorted = FALSE)</code> and also to the names of the corresponding list,<code>names(as.list(env, all.names = TRUE))</code>. Note that although <code>names()</code> returns a character vector, the names have no particular ordering.</li>
<li>The memory manager now grows the heap more aggressively. This reduces the number of garbage collections, in particular while data or code are loaded, at the expense of slightly increasing the memory footprint.</li>
<li>New function <code>trimws()</code> for removing leading/trailing whitespace.</li>
<li><code>cbind()</code> and <code>rbind()</code> now consider S4 inheritance during S3 dispatch and also obey <code>deparse.level</code>.</li>
<li><code>cbind()</code> and <code>rbind()</code> will delegate recursively to <code>methods::cbind2</code> (<code>methods::rbind2</code>) when at least one argument is an S4 object and S3 dispatch fails (due to ambiguity).</li>
<li>(Windows.) <code>download.file(quiet = FALSE)</code> now uses text rather than Windows progress bars in non-interactive use.</li>
<li>New function <code>hsearch_db()</code> in package <span>utils</span> for building and retrieving the help search database used by <code>help.search()</code>, along with functions for inspecting the concepts and keywords in the help search database.</li>
<li>New function <code>.getNamespaceInfo()</code>, a no-check version of <code>getNamespaceInfo()</code> mostly for internal speedups.</li>
<li>The help search system now takes <span>keyword</span> entries in Rd files which are not standard keywords (as given in &lsquo;<span>KEYWORDS</span>&rsquo; in the <strong>R</strong> documentation directory) as concepts. For standard keyword entries the corresponding descriptions are additionally taken as concepts.</li>
<li>New <code>lengths()</code> function for getting the lengths of all elements in a list.</li>
<li>New function <code>toTitleCase()</code> in package <span>tools</span>, tailored to package titles.</li>
<li>The matrix methods of <code>cbind()</code> and <code>rbind()</code> allow matrices as inputs which have <em>2^31</em> or more elements. (For <code>cbind()</code>, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>.)</li>
<li>The default method of <code>image()</code> has an explicit check for a numeric or logical matrix (which was always required).</li>
<li><code>URLencode()</code> will not by default encode further URLs which appear to be already encoded.</li>
<li><code>BIC(mod)</code> and <code>BIC(mod, mod2)</code> now give non-NA numbers for <code>arima()</code> fitted models, as <code>nobs(mod)</code> now gives the number of &ldquo;used&rdquo; observations for such models. This fixes <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>, quite differently than proposed there.</li>
<li>The <code>print()</code> methods for <code>"htest"</code>, <code>"pairwise.htest"</code> and <code>"power.htest"</code> objects now have a <code>digits</code> argument defaulting to (a function of) <code>getOption("digits")</code>, and influencing all printed numbers coherently. Unavoidably, this changes the display of such test results in some cases.</li>
<li>Code completion for namespaces now recognizes all loaded namespaces, rather than only the ones that are also attached.</li>
<li>The code completion mechanism can now be replaced by a user-specified completer function, for (temporary) situations where the usual code completion is inappropriate.</li>
<li><code>unzip()</code> will now warn if it is able to detect truncation when unpacking a file of 4GB or more (related to <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16243" target="_blank">PR#16243</a>).</li>
<li><code>methods()</code> reports S4 in addition to S3 methods; output is simplified when the <code>class</code> argument is used. <code>.S3methods()</code> and <code>methods::.S4methods()</code> report S3 and S4 methods separately.</li>
<li>Higher order functions such as the <code>apply</code> functions and <code>Reduce()</code> now force arguments to the functions they apply in order to eliminate undesirable interactions between lazy evaluation and variable capture in closures. This resolves <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16093" target="_blank">PR#16093</a>.</li>
</ul><p>More at http://cran.rstudio.com/</p><p>Reference: http://www.r-bloggers.com/r-3-2-0-is-released-using-the-installr-package-to-upgrade-in-windows-os/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24178/essentials-of-statistics-and-data-analysis-using-r</guid>
  <pubDate>Mon, 31 Aug 2015 01:32:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[Essentials of Statistics and Data Analysis using R]]></title>
  <description><![CDATA[
<p>Clinical Development Services Agency (CDSA) is an extramural unit of Translational Health Science and Technology Institute (THSTI), Department of Biotechnology, Ministry of Science &amp; Technology, Government of India. CDSA has a national mandate of strengthening capacity and capability building in the area of Clinical development and Translational Research.</p>

<p>CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&amp;A sessions are added advantages of this workshop.</p>

<p>Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.</p>

<p>Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</guid>
	<pubDate>Wed, 29 Jun 2016 07:33:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</link>
	<title><![CDATA[CSBB-v1.0]]></title>
	<description><![CDATA[<p>CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux, UNIX, MAC OS and Windows platforms.</p>
<p>Currently CSBB provides 13 modules focused on analytical tasks like performing upper-quantile normalization on expression data or convert genome wide gene expression to z-scores when comparing expression data from different platforms.</p>
<p>More at&nbsp;https://github.com/skygenomics/CSBB-v1.0</p><p>Address of the bookmark: <a href="https://github.com/skygenomics/CSBB-v1.0" rel="nofollow">https://github.com/skygenomics/CSBB-v1.0</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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