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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37610?offset=280</link>
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	<item>
	<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/pages/view/11313/linux-sort-commands-for-bioinformatics</guid>
	<pubDate>Sat, 31 May 2014 15:41:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</link>
	<title><![CDATA[Linux Sort Commands for Bioinformatics]]></title>
	<description><![CDATA[<p>Almost all the scripting languages such as Perl, Python etc have built-in sort, but unfortunately none of them are as flexible as sort command. But one when it come to space efficiency GNU sort stands at the top. It can sort a 20Gb file with less than 2Gb memory. It is not trivial to implement so powerful a sort by yourself.</p><p>sort a space-delimited file based on its first column, then the second if the first is the same, and so on:<br />sort input.txt</p><p>sort a huge file (GNU sort ONLY):<br />sort -S 1500M -t $HOME/tmp input.txt &gt; sorted.txt</p><p>sort starting from the third column, skipping the first two columns:<br />sort +2 input.txt</p><p>sort the second column as numbers, descending order; if identical, sort the 3rd as strings, ascending order:<br />sort -k2,2nr -k3,3 input.txt</p><p>sort starting from the 4th character at column 2, as numbers:<br />sort -k2.4n input.txt</p><p>More Linxu sort command information<br /><br />If you have any sort commands you'd like to share, please add them to our comments section below. For more help, you can also type:<br /><br />man sort<br /><br />or<br /><br />sort --help<br /><br />on your Unix/Linux system.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37732/making-2d-hilbert-curve</guid>
	<pubDate>Mon, 17 Sep 2018 05:43:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37732/making-2d-hilbert-curve</link>
	<title><![CDATA[Making 2D Hilbert Curve]]></title>
	<description><![CDATA[<p><a href="https://en.wikipedia.org/wiki/Hilbert_curve">Hilbert curve</a>&nbsp;is a type of space-filling curves that folds one dimensional axis into a two dimensional space, but still keeps the locality. It has advantages to visualize data with long axis in following two aspects:</p>
<ol>
<li>greatly improve resolution of the visualization fron n to&nbsp;<span><span><span><span><span><span><span>&radic;</span></span><span><span><span><span>n</span></span></span></span></span></span></span></span><span>n</span></span>;</li>
<li>easy to visualize clusters because generally data points in the axis will also be close in the 2D space.</li>
</ol>
<p>This package aims to provide an easy and flexible way to visualize data through Hilbert curve. The implementation and example figures are based on following sources:</p>
<ul>
<li><a href="http://mkweb.bcgsc.ca/hilbert/">http://mkweb.bcgsc.ca/hilbert/</a></li>
<li><a href="http://corte.si/posts/code/hilbert/portrait/index.html">http://corte.si/posts/code/hilbert/portrait/index.html</a></li>
<li><a href="http://bioconductor.org/packages/devel/bioc/html/HilbertVis.html">http://bioconductor.org/packages/devel/bioc/html/HilbertVis.html</a></li>
</ul><p>Address of the bookmark: <a href="https://bioconductor.org/packages/devel/bioc/vignettes/HilbertCurve/inst/doc/HilbertCurve.html" rel="nofollow">https://bioconductor.org/packages/devel/bioc/vignettes/HilbertCurve/inst/doc/HilbertCurve.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11494/postdoc-position-at-centre-mediterraneen-de-medecine-moleculaire-nice-france</guid>
  <pubDate>Wed, 04 Jun 2014 07:20:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoc position at Centre Méditerranéen de Médecine Moléculaire - Nice - France]]></title>
  <description><![CDATA[
<p>The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).<br />The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ). </p>

<p>The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.<br /> <br />Candidates should hold a Ph.D. degree and have strong background in bioinformatics.<br />The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.</p>

<p>Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )</p>

<p>Homepage: http://www.unice.fr/c3m/EN/Equipe10.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</guid>
	<pubDate>Wed, 13 Mar 2019 19:20:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39114/plumberan-r-package-that-converts-your-existing-r-code-to-a-web-api</link>
	<title><![CDATA[plumber:An R package that converts your existing R code to a web API]]></title>
	<description><![CDATA[<p>plumber allows you to create a REST API by merely decorating your existing R source code with special comments. Take a look at an example.</p>
<pre><code><span># plumber.R
</span><span>
</span><span>#* Echo back the input
#* @param msg The message to echo
#* @get /echo
</span><span>function</span><span>(</span><span>msg</span><span>=</span><span>""</span><span>){</span><span>
  </span><span>list</span><span>(</span><span>msg</span><span> </span><span>=</span><span> </span><span>paste0</span><span>(</span><span>"The message is: '"</span><span>,</span><span> </span><span>msg</span><span>,</span><span> </span><span>"'"</span><span>))</span><span>
</span><span>}</span><span>

</span><span>#* Plot a histogram
#* @png
#* @get /plot
</span><span>function</span><span>(){</span><span>
  </span><span>rand</span><span> </span><span>&lt;-</span><span> </span><span>rnorm</span><span>(</span><span>100</span><span>)</span><span>
  </span><span>hist</span><span>(</span><span>rand</span><span>)</span><span>
</span><span>}</span><span>

</span><span>#* Return the sum of two numbers
#* @param a The first number to add
#* @param b The second number to add
#* @post /sum
</span><span>function</span><span>(</span><span>a</span><span>,</span><span> </span><span>b</span><span>){</span><span>
  </span><span>as.numeric</span><span>(</span><span>a</span><span>)</span><span> </span><span>+</span><span> </span><span>as.numeric</span><span>(</span><span>b</span><span>)</span><span>
</span><span>}</span></code></pre><p>Address of the bookmark: <a href="https://www.rplumber.io/" rel="nofollow">https://www.rplumber.io/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</guid>
	<pubDate>Sun, 08 Jun 2014 10:06:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11611/ten-recommendations-for-creating-usable-bioinformatics-command-line-software</link>
	<title><![CDATA[Ten recommendations for creating usable bioinformatics command line software]]></title>
	<description><![CDATA[<p><span>Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author&rsquo;s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user&rsquo;s time, and improve the quality of scientific analyses.</span></p><p>Address of the bookmark: <a href="http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer" rel="nofollow">http://www.gigasciencejournal.com/content/2/1/15?utm_content=buffer25ee0&amp;utm_medium=social&amp;utm_source=twitter.com&amp;utm_campaign=buffer</a></p>]]></description>
	<dc:creator>RAJESH DETROJA</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/12206/bioinformatics-algorithms-tutorials</guid>
	<pubDate>Tue, 24 Jun 2014 00:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12206/bioinformatics-algorithms-tutorials</link>
	<title><![CDATA[Bioinformatics algorithms tutorials]]></title>
	<description><![CDATA[<p>Useful bioinformatics tutorial, such as</p>
<p>De Bruijn Graphs for NGS Assembly<br>Algorithms for PacBio Reads<br>Software and Hardware Concepts for Bioinformatics<br>Finding us in Homolog.us (Search Algorithms)<br>NGS Genome and RNAseq Assembly - a Hands on Primer<br>Introduction to PERL, Python, R and C/C++ for Bioinformatics</p><p>Address of the bookmark: <a href="http://www.homolog.us/Tutorials/" rel="nofollow">http://www.homolog.us/Tutorials/</a></p>]]></description>
	<dc:creator>John Parker</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>

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