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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28855?offset=950</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22287/research-fellows-at-aimscs-hyderabad</guid>
  <pubDate>Wed, 06 May 2015 06:23:33 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Fellows at AIMSCS, Hyderabad]]></title>
  <description><![CDATA[
<p>C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) - Hyderabad, Andhra Pradesh<br />Advertisement No.: 5/2015</p>

<p>Research Fellows Systems Biology job vacancy in C.R.Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS)</p>

<p>JRF : Qualification - M. Sc in Bioinformatics, Systems Biology, M. Sc statistics, or M. Tech in Bioinformatics,</p>

<p>Pay Scale : Rs. 25,000</p>

<p>SRF : Qualification- Qualification prescribed for JRF with 2 years of research experience.</p>

<p>Pay Scale : Rs. 28,000*</p>

<p>No.of Post: 2</p>

<p>Desirable: Candidates should have strong background in Computational biology, bioinformatics, statistics and algorithmic development. In addition to that previous experience of working on Linux, bio-informatics, NGS data analysis and Basic knowledge of biology is desirable. Programming on any one of the programming languages (C, C++, perl, python) and statistical framework (e.g. R, matlab, etc.) is highly desirable.</p>

<p>More at http://www.crraoaimscs.org/jrf_application_form_2015.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</guid>
	<pubDate>Sun, 24 May 2015 09:28:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/22388/perl-one-liner-basics</link>
	<title><![CDATA[Perl One liner basics !!]]></title>
	<description><![CDATA[<p>Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:<br /><br />$ perl -e 'print "Hello, World!\n"'<br />Hello, World!<br /><br />It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.<br /><br />I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?<br /><br />$ perl -e 'print "$^O\n"'<br />linux<br /><br />It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:<br /><br />$ perl -E 'say "$^O"'<br />linux<br /><br />Pretty handy! say is a nifty feature that you'll use again and again.</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44557/fundamentals-of-data-visualization-by-claus-o-wilke</guid>
	<pubDate>Sat, 08 Jun 2024 16:07:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44557/fundamentals-of-data-visualization-by-claus-o-wilke</link>
	<title><![CDATA[Fundamentals of Data Visualization by Claus O. Wilke]]></title>
	<description><![CDATA[<p><span><span>The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. It has grown out of my experience of working with students and postdocs in my laboratory on thousands of data visualizations. Over the years, I have noticed that the same issues arise over and over. I have attempted to collect my accumulated knowledge from these interactions in the form of this book.</span></span></p>
<p><span>The entire book is written in R Markdown, using RStudio as my text editor and the&nbsp;</span><span>bookdown</span><span>&nbsp;package to turn a collection of markdown documents into a coherent whole. The book&rsquo;s source code is hosted on GitHub, at&nbsp;</span><a href="https://github.com/clauswilke/dataviz">https://github.com/clauswilke/dataviz</a><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="https://clauswilke.com/dataviz/" rel="nofollow">https://clauswilke.com/dataviz/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22416/rosenberg-lab</guid>
  <pubDate>Wed, 27 May 2015 17:52:24 -0500</pubDate>
  <link></link>
  <title><![CDATA[Rosenberg lab]]></title>
  <description><![CDATA[
<p>Research. Research in the lab focuses on mathematical, statistical, and computational problems in evolutionary biology and human genetics. Long-term interests of the lab include topics such as:</p>

<p>    Human genetic variation<br />    Inference of human evolutionary history from genetic markers<br />    Statistical analysis of population-genetic data<br />    Mathematical models of gene genealogies<br />    Theoretical population genetics<br />    Combinatorics of evolutionary trees<br />    The relationship between gene trees and species trees<br />    The role of human evolutionary genetics in the search for genes that contribute to disease-susceptibility <br />More at https://web.stanford.edu/group/rosenberglab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</guid>
	<pubDate>Fri, 08 Dec 2017 07:16:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34562/harvest-a-suite-of-core-genome-alignment-and-visualization-tools</link>
	<title><![CDATA[Harvest: a suite of core-genome alignment and visualization tools]]></title>
	<description><![CDATA[<p>Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.</p>
<p><a href="https://harvest.readthedocs.io/en/latest/_images/screen.png"><img src="https://harvest.readthedocs.io/en/latest/_images/screen.png" alt="_images/screen.png" style="border: 0px;"></a><span></span></p>
<p><strong>Tools</strong></p>
<ul>
<li><a href="https://harvest.readthedocs.io/en/latest/content/parsnp.html">Parsnp</a>&nbsp;- Core-genome alignment and analysis</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/gingr.html">Gingr</a>&nbsp;- Interactive visualization of alignments, trees and variants</li>
<li><a href="https://harvest.readthedocs.io/en/latest/content/harvest-tools.html">HarvestTools</a>&nbsp;- Archiving and postprocessing</li>
<li></li>
</ul><p>Address of the bookmark: <a href="https://harvest.readthedocs.io/en/latest/" rel="nofollow">https://harvest.readthedocs.io/en/latest/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22437/jrf-bioinformatics-icar-national-research-centre-for-orchids-pakyong</guid>
  <pubDate>Thu, 28 May 2015 19:33:19 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF Bioinformatics @ ICAR - National Research Centre for Orchids  Pakyong]]></title>
  <description><![CDATA[
<p>ICAR - National Research Centre for Orchids</p>

<p>Pakyong</p>

<p>F.No:NRCO/Admn/DBT /136 /</p>

<p>Walk-in-Interviews will be held at 737106, Sikkim for the post of 01 (One Project ‘DBT’s Twinning programme for the NE’ titled “Assessment of some fragrant orchids of north-east India for sustainable improvement of community livelihood”, indicated below. The appointment will be on contractual basis and the incumbents shall not have any regular appointment in ICAR.</p>

<p>‘DBT’s Twinning programme for the NE’ titled “Assessment of chemical and genetic divergence of some fragrant orchids of north-east India for sustainable improvement of community livelihood”</p>

<p>Junior Research Fellow (One post)</p>

<p>Essential Qualification : a. MSc (with NET qualification) / M.Tech degree (with or without NET) with minimum 55% marks in Biotechnology/ Bioinformatics/ Molecular Biology or any other related field.</p>

<p>Desirable Qualification: Computer Skills (Linux, Perl, Java, MySQL) with experience in advanced molecular Biology techniques</p>

<p>2nd June 2015</p>

<p>Advertisement: www.nrcorchids.nic.in/Employments/Vacancy%20-%20JRF.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</guid>
	<pubDate>Mon, 09 Jul 2018 05:27:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37259/epiviz-an-interactive-visualization-tool-for-functional-genomics-data</link>
	<title><![CDATA[Epiviz: an interactive visualization tool for functional genomics data.]]></title>
	<description><![CDATA[<p><span>Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the&nbsp;</span><a href="http://barcode.luhs.org/" target="_blank">Gene Expression Barcode project</a><span>&nbsp;for transcriptome visualization. It has a flexible plugin framework so users can add</span><a href="http://d3js.org/" target="_blank">d3</a><span>&nbsp;visualizations. You can see a video tour&nbsp;</span><a href="http://youtu.be/099c4wUxozA" target="_blank">here</a><span>.</span></p>
<p><span>https://bioconductor.org/packages/release/bioc/html/epivizr.html</span></p>
<p><span>https://github.com/epiviz</span></p>
<p><span>https://github.com/epiviz/epiviz</span></p><p>Address of the bookmark: <a href="https://epiviz.github.io/" rel="nofollow">https://epiviz.github.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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