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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36111?offset=10</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</guid>
	<pubDate>Thu, 25 Jan 2018 05:47:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</link>
	<title><![CDATA[RGFA: powerful and convenient handling of assembly graphs]]></title>
	<description><![CDATA[<p><span>RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.</span></p>
<p><span>https://github.com/ggonnella/rgfa</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40969/leaflet-javascript-libraries-for-interactive-maps</guid>
	<pubDate>Mon, 10 Feb 2020 01:35:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40969/leaflet-javascript-libraries-for-interactive-maps</link>
	<title><![CDATA[Leaflet: JavaScript libraries for interactive maps]]></title>
	<description><![CDATA[<p><a href="http://leafletjs.com/">Leaflet</a><span>&nbsp;is one of the most popular open-source JavaScript libraries for interactive maps.</span></p>
<h3>Features</h3>
<ul>
<li>Interactive panning/zooming</li>
<li>Compose maps using arbitrary combinations of:
<ul>
<li>Map tiles</li>
<li>Markers</li>
<li>Polygons</li>
<li>Lines</li>
<li>Popups</li>
<li>GeoJSON</li>
</ul>
</li>
<li>Create maps right from the R console or RStudio</li>
<li>Embed maps in&nbsp;<a href="http://yihui.name/knitr/">knitr</a>/<a href="http://rmarkdown.rstudio.com/">R Markdown</a>&nbsp;documents and&nbsp;<a href="http://shiny.rstudio.com/">Shiny</a>&nbsp;apps</li>
<li>Easily render spatial objects from the&nbsp;<code>sp</code>&nbsp;or&nbsp;<code>sf</code>&nbsp;packages, or data frames with latitude/longitude columns</li>
<li>Use map bounds and mouse events to drive Shiny logic</li>
<li>Display maps in non spherical mercator projections</li>
<li>Augment map features using chosen plugins from&nbsp;<a href="http://leafletjs.com/plugins">leaflet plugins repository</a></li>
</ul>
<p><a href="https://rstudio.github.io/leaflet/">https://rstudio.github.io/leaflet/</a></p><p>Address of the bookmark: <a href="https://rstudio.github.io/leaflet/" rel="nofollow">https://rstudio.github.io/leaflet/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</guid>
	<pubDate>Fri, 28 Oct 2016 07:59:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</link>
	<title><![CDATA[Graph Genome Suite]]></title>
	<description><![CDATA[<p><span>Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the&nbsp;</span><strong>Graph Genome Suite</strong><span>&nbsp;&mdash; the most advanced population genomics tools in the world.</span></p><p>Address of the bookmark: <a href="https://www.sbgenomics.com/graph/" rel="nofollow">https://www.sbgenomics.com/graph/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</guid>
	<pubDate>Sun, 20 Jan 2019 05:34:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</link>
	<title><![CDATA[Osprey: Network Visualization System]]></title>
	<description><![CDATA[<p>Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from&nbsp;<a href="http://geneontology.org/" title="GENE ONTOLOGY CONSORTIUM">Gene Ontology (GO)</a>&nbsp;annotated interaction data maintained by the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>.</p>
<p>Osprey is developed by the&nbsp;<a href="http://www.tyerslab.com/">TyersLab</a>&nbsp;and is a part of the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>&nbsp;family of software. It utilizes both&nbsp;<a href="https://www.mysql.com/" title="MySQL Database">MySQL</a>&nbsp;and&nbsp;<a href="http://openjdk.java.net/" title="OpenJDK">Java</a>&nbsp;to operate and is compatible with&nbsp;<a href="https://www.microsoft.com/en-us/windows/" title="Microsoft Windows">Windows</a>,&nbsp;<a href="http://www.ubuntu.com/">Linux</a>, and&nbsp;<a href="http://www.apple.com/" title="Apple">Apple</a>&nbsp;operating systems.</p>
<p>These works were published in&nbsp;<strong>Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22</strong>&nbsp;<a href="http://genomebiology.com/2003/4/3/R22" title="Genome Biology">[Genome Biology]</a>&nbsp;<a href="http://genomebiology.com/content/pdf/gb-2003-4-3-r22.pdf" title="Osprey PDF">[PDF]</a>&nbsp;<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;list_uids=12620107&amp;dopt=Abstract" title="Pubmed">[PubMed]</a>&nbsp;and supported by the&nbsp;<a href="http://www.nih.gov/" title="NIH">National Institutes of Health</a>,&nbsp;<a href="http://www.cihr-irsc.gc.ca/" title="CIHR">Canadian Institutes of Health Research</a>, and&nbsp;<a href="http://www.genomecanada.ca/en/" title="Genome Canada">Genome Canada</a>.</p><p>Address of the bookmark: <a href="https://osprey.thebiogrid.org/" rel="nofollow">https://osprey.thebiogrid.org/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/view/119</guid>
	<pubDate>Wed, 10 Jul 2013 14:35:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/view/119</link>
	<title><![CDATA[Which are the best statistical programming languages to study for a bioinformatician?]]></title>
	<description><![CDATA[<p><span>In Bio-informatics based&nbsp;genome sequencing and predicting metabolic pathways&nbsp;research jobs&nbsp;I used Matlab, SAS, SPSS, R and several Bioconductor packages. Matlab had a lot of powerful tools and was easy to use, whereas SPSS is for non-programmers and R need programming skills. I am wondering what other people think is best? or there might not be one specific language but a few that lend themselves best to Bio-informatics work that is math heavy and deals with a large amount of data.</span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1720/postdoctoral-associate-bioinformatics-at-duke-university-medical-center</guid>
  <pubDate>Sat, 10 Aug 2013 18:38:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Associate - Bioinformatics  at Duke University Medical Center]]></title>
  <description><![CDATA[
<p>The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.</p>

<p>Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.</p>

<p>This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.</p>

<p>For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.</p>

<p>For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf</p>

<p>Duke University is an Equal Opportunity/Affirmative Action Employer.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/5894/rna-seq-data-pathway-and-gene-set-analysis-workflows</guid>
	<pubDate>Fri, 25 Oct 2013 08:00:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/5894/rna-seq-data-pathway-and-gene-set-analysis-workflows</link>
	<title><![CDATA[RNA-Seq Data Pathway and Gene-set Analysis Workflows]]></title>
	<description><![CDATA[<p>It describe the GAGE (Luo et al., 2009) /Pahview (Luo and Brouwer, 2013) workflows on&nbsp;RNA-Seq data pathway analysis and gene-set analysis.&nbsp;<span>The gage package (2.12.0) now includes a new tutorial, &ldquo;RNA-Seq Data Pathway and Gene-set Analysis Workflows&ldquo;.</span></p><p>First cover a full workflow from preparation, reads counting, data preprocessing, gene set test, to pathway visualization in about 40 lines of codes. The same workflow can be used for GO analysis or other types of gene set analysis too. We also describe joint workflows, i.e. to do gene-level analysis using one of the major RNA-Seq analysis tools, DEseq/DEseq2, edgeR, limma and Cufflinks, and feed the results into GAGE/Pahview for pathway analysis or visualization. All these workflows are implemented in R/Bioconductor.</p><p>The work ows cover the most common situations and issues for RNA-Seq data pathway analysis. Issues like&nbsp;data quality assessment are relevant for data analysis in general yet out the scope of this tutorial. Although we&nbsp;focus on RNA-Seq data here, but pathway analysis work ow remains similar for microarray, particularly step&nbsp;3-4 would be the same. Please check gage and pathview vigenttes for details.</p><p>Note: You need to update to current release versions of R(3.0.2)/ Bioconductor(2.13) to use all the features.&nbsp;</p><p>Reference:&nbsp;</p><p>Please check it out:<br /><a href="http://bioconductor.org/packages/release/bioc/html/gage.html">http://bioconductor.org/packages/release/bioc/html/gage.html</a><br /><a href="http://bioconductor.org/packages/release/bioc/vignettes/gage/inst/doc/RNA-seqWorkflow.pdf">http://bioconductor.org/packages/release/bioc/vignettes/gage/inst/doc/RNA-seqWorkflow.pdf</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/14024/grapher</guid>
	<pubDate>Thu, 14 Aug 2014 14:02:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/14024/grapher</link>
	<title><![CDATA[GrapheR !!!]]></title>
	<description><![CDATA[<p>What a wonderful gem <em>GrapheR</em> is.... Oh yes it is. <em>GrapheR</em> is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console. <br /><br />Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.<br />Here is a little example using the iris data set.<br /><br />library(GrapheR)<br />data(iris)<br />run.GrapheR()<br /><br />This will bring up a window that helps me to create the chart and tweak the various parameters.</p><p><img src="http://4.bp.blogspot.com/-NbnCM1dPh3E/U9aW9YxJ9oI/AAAAAAAABgo/gEPzPhOpf2Y/s1600/GrapheR.png" alt="image" width="878" height="868" style="border: 0px; border: 0px;"><br /><br />Finally, I find the underlying R code in a file created by <em>GrapheR</em>. For more details read also the <a href="http://cran.r-project.org/web/packages/GrapheR/index.html" target="_blank">package vignette</a>, which is available in <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_en.pdf" target="_blank">English</a>, <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_fr.pdf" target="_blank">French</a> and <a href="http://cran.r-project.org/web/packages/GrapheR/vignettes/manual_de.pdf" target="_blank">German</a>!</p>]]></description>
	<dc:creator>John Parker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</guid>
	<pubDate>Sat, 27 Dec 2014 06:50:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</link>
	<title><![CDATA[RStudio]]></title>
	<description><![CDATA[<p>RStudio IDE is a powerful and productive user interface for R. It&rsquo;s free and open source, and works great on Windows, Mac, and Linux.</p>
<p>The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.</p>
<p>More at http://www.rstudio.com/</p>
<p>http://www.rstudio.com/products/RStudio/</p><p>Address of the bookmark: <a href="http://www.rstudio.com/" rel="nofollow">http://www.rstudio.com/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21367/a-guide-for-complete-r-beginners-r-syntax</guid>
	<pubDate>Fri, 20 Feb 2015 23:41:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21367/a-guide-for-complete-r-beginners-r-syntax</link>
	<title><![CDATA[A guide for complete R beginners :- R Syntax]]></title>
	<description><![CDATA[<p>R is a functional based language, the inputs to a function, including options, are in brackets. Note that all dat and options are separated by a comma</p><ul>
<li>Function(data, options)</li>
</ul><p>Even quit is a function</p><ul>
<li>q()</li>
</ul><p>So is help</p><blockquote><p><strong>help(read.table)</strong></p></blockquote><p>Provides the help page for the FUNCTION &lsquo;read.table&rsquo;</p><blockquote><p><strong>help.search(&ldquo;t test&rdquo;)</strong></p></blockquote><p>Searches for help pages that might relate to the phrase &lsquo;t test&rsquo;</p><p><strong>NOTE</strong>: quotes are needed for search strings, they are not needed when referring to data objects or function names.</p><p>There is a short cut for help,</p><p>? shows the help page on a function name, same as <em>help(function)</em></p><blockquote><p><strong>?read.table</strong></p></blockquote><p>?? searches for help pages on functions, same as <em>help.search(&lsquo;phrase&rsquo;)</em></p><blockquote><p><strong>??&ldquo;t test&rdquo;</strong></p></blockquote><p>Information is usually returned from a function, by default this is printed to screen</p><blockquote><p><strong>read.table(&lsquo;data.tsv&rsquo;)</strong></p></blockquote><p>This can always be stored, we call what it is stored in an &lsquo;object&rsquo;</p><p><strong>mydata </strong></p><p>here <strong>mydata</strong> is an object of type <span style="text-decoration: underline;">dataframe</span></p><p><strong>Reminder:</strong></p><ul>
<li>Vector: a list of numbers, equivalent to a column in a table</li>
<li>Data Frame = a collection of vectors. Equivalent to a table</li>
</ul><p><strong>Hint</strong>:</p><ul>
<li>Up/Down arrow keys can be use to cycle through previous commands</li>
</ul>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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