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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/3046?offset=60</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</guid>
	<pubDate>Tue, 03 May 2016 16:43:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r</link>
	<title><![CDATA[Supposedly Educational R]]></title>
	<description><![CDATA[<p>R 3.3.0 (codename &ldquo;Supposedly Educational&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-3-0-is-released-td4720368.html" target="_blank">released today</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-3.3.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><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 in Rgui:</p><div><table width="710">
<tbody>
<tr id="p613882">
<td id="p61388code2">
<pre><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: #228b22;"># install </span>
setInternet2<span style="color: #080;">(</span>TRUE<span style="color: #080;">)</span>
installr<span style="color: #080;">::</span><span>updateR</span><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.). There is also <a href="http://www.r-statistics.com/2015/06/a-step-by-step-screenshots-tutorial-for-upgrading-r-on-windows/" target="_blank">a&nbsp;step by step tutorial (with screenshots) on how to upgrade R on Windows, using the <em>installr</em></a>&nbsp;package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).</span></p><p><em>I try to keep the <a href="https://github.com/talgalili/installr" target="_blank">installr</a> package updated and useful, so if you have any suggestions or remarks on the package &ndash; you are invited to <a href="https://github.com/talgalili/installr/issues" target="_blank">open an issue in the github page</a>.</em></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</guid>
	<pubDate>Fri, 20 May 2016 11:01:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots</link>
	<title><![CDATA[RCircos: an R package for Circos 2D track plots]]></title>
	<description><![CDATA[<p>RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.</p>
<p>More at https://bitbucket.org/henryhzhang/rcircos/src</p><p>Address of the bookmark: <a href="https://bitbucket.org/henryhzhang/rcircos/src" rel="nofollow">https://bitbucket.org/henryhzhang/rcircos/src</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</guid>
	<pubDate>Sat, 21 May 2016 22:42:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27463/bpipe-a-tool-for-running-and-managing-bioinformatics-pipelines</link>
	<title><![CDATA[Bpipe - a tool for running and managing bioinformatics pipelines]]></title>
	<description><![CDATA[<p>Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.</p>
<ul>
<li>January 20th, 2016 - New! Bpipe 0.9.9 released!</li>
<li>Download <a href="http://download.bpipe.org/versions/bpipe-0.9.9.tar.gz">latest</a>, <a href="http://download.bpipe.org">all</a></li>
<li><a href="http://docs.bpipe.org">Documentation</a></li>
<li><a href="https://groups.google.com/forum/#%21forum/bpipe-discuss">Mailing List</a> (Google Group)</li>
</ul>
<p>Bpipe has been published in <a href="http://bioinformatics.oxfordjournals.org/content/early/2012/04/11/bioinformatics.bts167.abstract">Bioinformatics</a>! If you use Bpipe, please cite:</p>
<p><em>Sadedin S, Pope B &amp; Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics</em></p><p>Address of the bookmark: <a href="http://docs.bpipe.org/" rel="nofollow">http://docs.bpipe.org/</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28855/vcfr</guid>
	<pubDate>Fri, 19 Aug 2016 07:38:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28855/vcfr</link>
	<title><![CDATA[vcfR]]></title>
	<description><![CDATA[<p><span>Most variant calling pipelines result in files containing large quantities of variant information. The&nbsp;</span><a href="http://samtools.github.io/hts-specs/" title="VCF format at hts-specs">variant call format (vcf)</a><span>&nbsp;is an increasingly popular format for this data. The format of these files and their content is discussed in the vignette &lsquo;vcf data.&rsquo; These files are typically intended to be post-processed (i.e., filtered) as an attempt to remove false positives or otherwise problematic sites. The R package vcfR provides tools to facilitate this filtering as well as to visualize the effects of choices made during this process.</span></p><p>Address of the bookmark: <a href="https://cran.r-project.org/web/packages/vcfR/vignettes/visualization_1.html" rel="nofollow">https://cran.r-project.org/web/packages/vcfR/vignettes/visualization_1.html</a></p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</guid>
	<pubDate>Mon, 13 Feb 2017 09:47:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30901/ideoplot</link>
	<title><![CDATA[Ideoplot]]></title>
	<description><![CDATA[<p>Simple ideogram plotting and annotation in R.</p>
<p>Basic usage:</p>
<p>Rscript Ideoplot.R --heatmap hm.bed --annotate annotations.bed --out ideogram.pdf<br> -or-<br> Rscript Ideoplot.R --annotate annotations.bed</p>
<pre>Options
  --ideobed, i      A bed file of reference contig lengths/chromosome names
  --heatmap, -h     Fill chromosomes with normalized heatmap
                   (described below)
  --annotate, -a    Add character annotations.
  --out, -o         PDF output name.
  --stripes, -s     Specify a file containing the layout of the
                    annotations (description below)
  --bars, -b        Add track annotations
  --reference, -f   Either hg19, or hg38
  --topdown, r      Flag, when set, flips the orientation (P arms
                    drawn on top).
</pre><p>Address of the bookmark: <a href="https://github.com/mchaisso/Ideoplot" rel="nofollow">https://github.com/mchaisso/Ideoplot</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</guid>
	<pubDate>Tue, 17 Apr 2018 04:33:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36239/scilifelab-tutorial-for-bioinformatics-analysis</link>
	<title><![CDATA[SciLifeLab tutorial for bioinformatics analysis !]]></title>
	<description><![CDATA[<p>SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.</p>
<h2 id="courses">Courses</h2>
<p><a href="http://uppnex.se/twiki/bin/view/Courses/">Old courses (2012-2014)</a></p>
<h3 id="metagenomics-workshop">Metagenomics Workshop</h3>
<p><a href="https://scilifelab.github.io/courses/Metagenomics/1511/">2015 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/Metagenomics/1711/">2017 November - Uppsala</a></p>
<h3 id="introduction-to-bioinformatics-using-ngs-data">Introduction to Bioinformatics Using NGS Data</h3>
<p><a href="https://scilifelab.github.io/courses/ngsintro/1502/">2015 February - Uppsala</a>&nbsp;<br><a href="https://scilifelab.github.io/courses/ngsintro/1505/">2015 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1509/">2015 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1511/">2015 November - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1601/">2016 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1604/">2016 April - Link&ouml;ping</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1609/">2016 September - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1611/">2016 November - Ume&aring;</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1701/">2017 January - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1705/">2017 May - Gothenburg</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1709/">2017 September - Lund</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/ngsintro/1802/">2018 February - Uppsala</a></p>
<h3 id="introduction-to-genome-annotation">Introduction to Genome Annotation</h3>
<p><a href="https://scilifelab.github.io/courses/annotation/2015/">2015 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2016/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2017/">2017 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/annotation/2018/">2018 May - Uppsala</a></p>
<h3 id="de-novo-genome-assembly">De Novo Genome Assembly</h3>
<p><a href="https://scilifelab.github.io/courses/assembly/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/assembly/2017-11-15/">2017 November - Uppsala</a></p>
<h3 id="rna-seq-course">RNA-seq course</h3>
<p><a href="https://scilifelab.github.io/courses/rnaseq/1510/">2015 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1604/">2016 April - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1610/">2016 October - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1703/">2017 March - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/1711/">2017 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/rnaseq/labs">RNAseq tutorials</a></p>
<h3 id="r-programming-foundations-for-life-scientists">R Programming Foundations for Life Scientists</h3>
<p><a href="https://scilifelab.github.io/courses/r_programming/1611/">2016 November - Uppsala</a><br><a href="https://scilifelab.github.io/courses/r_programming/1703/">2017 Mars - Uppsala</a></p>
<h3 id="single-cell-rna-sequencing-analysis">Single cell RNA sequencing analysis</h3>
<p><a href="https://scilifelab.github.io/courses/scrnaseq/1710/">2017 October - Uppsala</a></p><p>Address of the bookmark: <a href="https://scilifelab.github.io/courses/" rel="nofollow">https://scilifelab.github.io/courses/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</guid>
	<pubDate>Tue, 31 Dec 2019 19:33:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40489/machine-learning-training-and-courses-in-bioinformatics</link>
	<title><![CDATA[Machine learning training and courses in bioinformatics !]]></title>
	<description><![CDATA[<p>Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models and machine learning techniques. We will focus on probabilistic models (Markov models, Hidden Markov models, and Bayesian networks) for biological sequence analysis and systems biology. Other machine learning techniques, such as Naive bayes, neural networks and SVMs will only be covered briefly.</p>
<p>More at&nbsp;http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</p>
<p>More tutorial at&nbsp;</p>
<p><a href="http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm">http://calla.rnet.missouri.edu/cheng_courses/mlbioinfo/mlbioinfo.htm</a></p>
<p><a href="http://www.raetschlab.org/lectures/MLBioinformatics">http://www.raetschlab.org/lectures/MLBioinformatics</a></p>
<p><a href="http://www.raetschlab.org/lectures/bertinoro08">http://www.raetschlab.org/lectures/bertinoro08</a></p>
<p>Book at&nbsp;</p>
<p><a href="https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf">https://personal.utdallas.edu/~pradiptaray/teaching/7_deep_learning_bioinfo.pdf</a></p><p>Address of the bookmark: <a href="http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/" rel="nofollow">http://homes.sice.indiana.edu/yye/lab/teaching/spring2017-I529/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 06:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</link>
	<title><![CDATA[Python and BioPython Tutorial]]></title>
	<description><![CDATA[<p>A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.</p><p>Address of the bookmark: <a href="http://www.biotnet.org/training-materials/python-programmers" rel="nofollow">http://www.biotnet.org/training-materials/python-programmers</a></p>]]></description>
	<dc:creator>Manshi Raghubanshi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43292/bioinformatics-scientist-production-bioinformatics-south-san-francisco-ca</guid>
  <pubDate>Thu, 19 Aug 2021 08:45:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA]]></title>
  <description><![CDATA[
<p>wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.</p>

<p>More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</guid>
	<pubDate>Mon, 22 Aug 2022 23:56:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43943/bioinformatics-tutorial</link>
	<title><![CDATA[Bioinformatics Tutorial !]]></title>
	<description><![CDATA[<p>This site aims to be a useful resource for bioinformatics beginners. Feel free to jump right in with the section most relevant to you, and if you're not sure, then the place to start is definitely Unix <p>Address of the bookmark: <a href="https://astrobiomike.github.io/" rel="nofollow">https://astrobiomike.github.io/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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