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<channel>
	<title><![CDATA[BOL: R and Bioconductor's News]]></title>
	<link>https://bioinformaticsonline.com/news/group/93/all?</link>
	<atom:link href="https://bioinformaticsonline.com/news/group/93/all?" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/36585/custom-r-charts-coming-to-excel</guid>
	<pubDate>Sat, 12 May 2018 07:30:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/36585/custom-r-charts-coming-to-excel</link>
	<title><![CDATA[Custom R charts coming to Excel !]]></title>
	<description><![CDATA[<p>This week at the BUILD conference, Microsoft&nbsp;<a href="https://dev.office.com/blogs/azure-machine-learning-javascript-custom-functions-and-power-bi-custom-visuals-further-expand-developers-capabilities-with-excel" target="_blank">announced</a>&nbsp;that Power BI custom visuals will soon be available as charts with Excel. You'll be able to choose a range of data within an Excel workbook, and pass those data to one of the built-in Power BI custom visuals, or one you've&nbsp;<a href="https://github.com/Microsoft/PowerBI-Visuals/" target="_blank">created yourself using the API</a>.</p><p><a href="http://a0.typepad.com/6a0105360ba1c6970c0224e038fa08200d-pi" target="_blank"><img src="https://www.r-bloggers.com/wp-content/plugins/lazy-load/images/1x1.trans.gif" alt="Excel custom visuals" title="Excel custom visuals" style="border: 0px; border: 0px;"></a></p><p>Since you can&nbsp;<a href="https://docs.microsoft.com/en-us/power-bi/desktop-r-visuals?WT.mc_id=Revolutions-blog-davidsmi" target="_blank">create Power BI custom visuals using R</a>, that means you'll be able to design a custom R-based chart, and make it available to people using Excel &mdash; even if they don't know how to use R themselves. There also many&nbsp;<a href="https://appsource.microsoft.com/en-us/marketplace/apps?product=power-bi-visuals&amp;page=1&amp;src=office" target="_blank">pre-defined custom visuals available</a>, including some familiar R charts like&nbsp;<a href="https://appsource.microsoft.com/en-us/product/power-bi-visuals/WA104380817?tab=Overview" target="_blank">decision trees</a>,&nbsp;<a href="https://appsource.microsoft.com/en-us/product/power-bi-visuals/WA104380905?tab=Overview" target="_blank">calendar heatmaps</a>, and&nbsp;<a href="https://appsource.microsoft.com/en-us/product/power-bi-visuals/WA104381492?tab=Overview" target="_blank">hexbin scatterplots</a>.</p><p>For more details on how you'll be able to use custom R visuals in Excel, check out the blog post linked below.</p><p>PowerBI Blog:&nbsp;<a href="https://powerbi.microsoft.com/en-us/blog/excel-announces-new-data-visualization-capabilities-with-power-bi-custom-visuals/" target="_blank">Excel announces new data visualization capabilities with Power BI custom visuals</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/36418/r-350-has-been-released</guid>
	<pubDate>Thu, 26 Apr 2018 11:31:58 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/36418/r-350-has-been-released</link>
	<title><![CDATA[R 3.5.0 has been Released!]]></title>
	<description><![CDATA[<ul>
<li>The latest version of R is a major release! It comes with a ton of new features, including performance and speed improvements</li>
<li>All R packages will now be byte-compiled, hence boosting packages installed from GitHub</li>
<li>You may need to re-install all previously installed R packages; old scripts however will continue to work normally</li>
</ul><p>More at&nbsp;<a href="https://cran.r-project.org/doc/manuals/r-release/NEWS.html">https://cran.r-project.org/doc/manuals/r-release/NEWS.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/23160/opencpu</guid>
	<pubDate>Sun, 05 Jul 2015 18:34:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/23160/opencpu</link>
	<title><![CDATA[OpenCPU]]></title>
	<description><![CDATA[<p>OpenCPU is a system for embedded scientific computing and reproducible research. The OpenCPU server provides a reliable and interoperable <a href="https://www.opencpu.org/api.html">HTTP API</a> for data analysis based on R.</p><p>The OpenCPU <a href="https://www.opencpu.org/jslib.html">JavaScript client library</a> provides the most seamless integration of R and JavaScript available today.</p><p>OpenCPU uses standard R packaging to develop, ship and deploy web applications. Several open source <a href="https://www.opencpu.org/apps.html">example apps</a> are available from Github.</p><p>Installing your own OpenCPU server is <a href="https://www.opencpu.org/download.html">super easy</a> and only takes a few minutes.</p><p>More at https://www.opencpu.org/</p>]]></description>
	<dc:creator>Rahul Nayak</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/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>
</item>
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	<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/news/view/19272/translate2r</guid>
	<pubDate>Fri, 21 Nov 2014 01:16:06 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/19272/translate2r</link>
	<title><![CDATA[translate2R]]></title>
	<description><![CDATA[<p>After their presentation at the international &ldquo;user!&rdquo; conference, data analysis specialist <a href="http://www.eoda.de/en/" target="_blank">eoda</a> starts the public alpha testing of <a href="http://www.eoda.de/en/translate2R.html" target="_blank">translate2R</a>. With the start of alpha testing the innovative migration solution by the company hailing from Kassel discards the working title &ldquo;translateR&rdquo; and takes on the final product brand name &ldquo;translate2R&rdquo;. translate2R is a service for the automated translation of SPSS&reg; syntax to R code, therefore supporting data analysts with a quick and low-risk migration to R.</p><p>The manual translation of many, frequently rather complex SPSS scripts often presents itself as a tedious and error-prone task, and represents a rather large obstacle for many analysts and companies to migrate to a modern, open source data management and analysis tool like R. With translate2R this hurdle will be diminished substantially.</p><p>Find at https://service.eoda.de/translater/?lang=en</p>]]></description>
	<dc:creator>Rahul Nayak</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/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/news/view/14186/pybedtools</guid>
	<pubDate>Wed, 20 Aug 2014 01:03:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14186/pybedtools</link>
	<title><![CDATA[pybedtools]]></title>
	<description><![CDATA[<p>pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.</p><p>More at http://pythonhosted.org/pybedtools/</p><p>A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>

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