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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35565?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</guid>
	<pubDate>Fri, 06 Apr 2018 12:10:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36111/d3networktools-for-creating-d3-javascript-network-tree-dendrogram-and-sankey-graphs-from-r</link>
	<title><![CDATA[d3Network:Tools for creating D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.]]></title>
	<description><![CDATA[<p><a href="http://bost.ocks.org/mike/">Mike Bostock</a><span>&rsquo;s&nbsp;</span><a href="http://d3js.org/">D3.js</a><span>&nbsp;is great for creating&nbsp;</span><a href="http://bl.ocks.org/mbostock/4062045">interactive network graphs</a><span>&nbsp;with JavaScript. The&nbsp;</span><a href="https://github.com/christophergandrud/d3Network">d3Network</a><span>&nbsp;package makes it easy to create these network graphs from&nbsp;</span><a href="http://www.r-project.org/">R</a><span>. The main idea is that you should able to take an R data frame with information about the relationships between members of a network and create full network graphs with one command.</span></p><p>Address of the bookmark: <a href="http://christophergandrud.github.io/d3Network/" rel="nofollow">http://christophergandrud.github.io/d3Network/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40463/%E2%80%98dockr%E2%80%99-the-r-container</guid>
	<pubDate>Mon, 23 Dec 2019 09:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40463/%E2%80%98dockr%E2%80%99-the-r-container</link>
	<title><![CDATA[‘dockr’: the R container]]></title>
	<description><![CDATA[<p><code>dockr</code> 0.8.6 is now available on CRAN. <code>dockr</code> is a minimal toolkit to build a lightweight Docker container image for your R package, in which the package itself is available. The Docker image seeks to mirror your R session as close as possible with respect to R specific dependencies. Both dependencies on CRAN R packages as well as local non-CRAN R packages will be included in the Docker container image.</p>
<p>If you want to know, how Docker works, and why you should consider using Docker, please take a look at the <a href="https://www.docker.com/why-docker" target="_blank">Docker website</a>.</p><p>Address of the bookmark: <a href="https://www.docker.com/why-docker" rel="nofollow">https://www.docker.com/why-docker</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33592/circular-plots-in-r</guid>
	<pubDate>Mon, 19 Jun 2017 06:20:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33592/circular-plots-in-r</link>
	<title><![CDATA[Circular plots in R]]></title>
	<description><![CDATA[<div>
<p><strong>Circular plots</strong>&nbsp;are useful to represent complicated informations. They are used in 2 specific cases: when you have long axis and numerous categories, and when you want to show relationships between elements. The&nbsp;<a href="http://circos.ca/images/samples/" target="_blank">circos gallery</a>&nbsp;displays several examples of circular plots, what gives a nice overview of the possibilities. Circos is the most famous</p>
</div>
<div>
<p>tool to create circular plots. Thanks to&nbsp;<a href="https://www.linkedin.com/in/zuguanggu" target="_blank">Zuguang Gu</a>, the&nbsp;<a href="https://cran.r-project.org/web/packages/circlize/vignettes/circlize.pdf" target="_blank">Circlize library</a>&nbsp;makes the circos functions available in R! It implements low-level graphic functions for adding common graphics in a circular layout. This page aims to learn you how to use the library, so I strongly advise to read the graphics in the proposed order!</p>
<p><img src="http://www.r-graph-gallery.com/wp-content/uploads/2016/03/122_Circlize_package.png" width="480" height="480" alt="image" style="border: 0px;"></p>
</div>
<p>http://www.r-graph-gallery.com/portfolio/circular-plot/</p><p>Address of the bookmark: <a href="http://www.r-graph-gallery.com/portfolio/circular-plot/" rel="nofollow">http://www.r-graph-gallery.com/portfolio/circular-plot/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</guid>
	<pubDate>Wed, 27 Mar 2024 11:16:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool</link>
	<title><![CDATA[CGView.js is a Circular Genome Viewing tool]]></title>
	<description><![CDATA[<p>CGView.js is a&nbsp;<span>C</span>ircular&nbsp;<span>G</span>enome&nbsp;<span>View</span>ing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program&nbsp;<a href="https://paulstothard.github.io/cgview/">CGView</a>.</p>
<div>
<p>CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.</p>
<a href="https://proksee.ca/"></a></div>
<h1 id="features">Features</h1>
<ul>
<li>
<p>Circular and linear views of genomes</p>
</li>
<li>
<p>Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs</p>
</li>
<li>
<p>Smooth zooming down to the sequence level</p>
</li>
<li>
<p>Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)</p>
</li>
<li>
<p>Save high resolution PNG maps up to 8000x8000px</p>
</li>
<li>
<p>Fully documented API for interacting with CGView.js maps</p>
</li>
</ul><p>Address of the bookmark: <a href="https://js.cgview.ca/" rel="nofollow">https://js.cgview.ca/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</guid>
	<pubDate>Fri, 14 Jun 2024 14:42:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44571/panacus-a-counting-tool-for-pangenome-graphs</link>
	<title><![CDATA[Panacus : A Counting Tool for Pangenome Graphs]]></title>
	<description><![CDATA[<p dir="auto"><code>panacus</code>&nbsp;is a tool for calculating statistics for&nbsp;<a href="https://github.com/GFA-spec/GFA-spec/blob/master/GFA1.md">GFA</a>&nbsp;files. It supports GFA files with&nbsp;<code>P</code>&nbsp;and&nbsp;<code>W</code>&nbsp;lines, but requires that the graph is&nbsp;<code>blunt</code>, i.e., nodes do not overlap and consequently, each link (<code>L</code>) points from the end of one segment (<code>S</code>) to the start of another.</p>
<p dir="auto"><code>panacus</code>&nbsp;supports the following calculations:</p>
<ul dir="auto">
<li>coverage histogram</li>
<li>pangenome growth statistics</li>
<li>path-/group-resolved coverage table</li>
</ul><p>Address of the bookmark: <a href="https://github.com/marschall-lab/panacus" rel="nofollow">https://github.com/marschall-lab/panacus</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</guid>
	<pubDate>Thu, 23 Jan 2020 07:33:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs</link>
	<title><![CDATA[GfaViz: flexible and interactive visualization of GFA sequence graphs]]></title>
	<description><![CDATA[<p><span>GFA (Graphical Fragment Assembly) is an emerging standard format for representing sequence graphs. Although it was originally conceived as a format for sequence assembly (hence the name), and this remains its core application, it is more general, and able to represent many different types of sequence graphs, including scaffolding graphs, alignment graphs, variant graphs and splicing graphs.</span></p><p>Address of the bookmark: <a href="https://github.com/ggonnella/gfaviz" rel="nofollow">https://github.com/ggonnella/gfaviz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing</guid>
	<pubDate>Mon, 23 Apr 2018 05:49:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing</link>
	<title><![CDATA[DendroPy: a Python library for phylogenetic computing]]></title>
	<description><![CDATA[<p>DendroPy is a Python library for phylogenetic computing. It provides classes and functions for the simulation, processing, and manipulation of phylogenetic trees and character matrices, and supports the reading and writing of phylogenetic data in a range of formats, such as NEXUS, NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing some useful phylogenetic operations, such as data conversion and tree posterior distribution summarization, are also distributed and installed as part of the libary. DendroPy can thus function as a stand-alone library for phylogenetics, a component of more complex multi-library phyloinformatic pipelines, or as a scripting &ldquo;glue&rdquo; that assembles and drives such pipelines.</p>
<p>The primary home page for DendroPy, with detailed tutorials and documentation, is at:</p>
<blockquote><div><a href="http://dendropy.org/">http://dendropy.org/</a></div></blockquote>
<p>DendroPy is also hosted in the official Python repository:</p>
<blockquote><div><a href="http://packages.python.org/DendroPy/">http://packages.python.org/DendroPy/</a></div></blockquote>
<div id="requirements-and-installation">
<h2>Requirements and Installation</h2>
<p>DendroPy 4.x runs under Python 3 (all versions &gt; 3.1) and Python 2 (Python 2.7 only).</p>
<p>You can install DendroPy by running:</p>
<pre>&nbsp;</pre>
<p>More information is available here:</p>
<blockquote><div><a href="http://dendropy.org/downloading.html">http://dendropy.org/downloading.html</a></div></blockquote>
</div>
<div id="documentation">
<h2>Documentation</h2>
<p>Full documentation is available here:</p>
<blockquote><div><a href="http://dendropy.org/">http://dendropy.org/</a></div></blockquote>
<p>This includes:</p>
<blockquote>
<ul>
<li><a href="http://dendropy.org/primer/index.html">A comprehensive &ldquo;getting started&rdquo; primer</a>&nbsp;.</li>
<li><a href="http://dendropy.org/library/index.html">API documentation</a>&nbsp;.</li>
<li><a href="http://dendropy.org/schemas/index.html">Descriptions of data formats supported for reading/writing</a>&nbsp;.</li>
</ul>
</blockquote>
<p>and more.</p>
</div><p>Address of the bookmark: <a href="https://pypi.org/project/DendroPy/" rel="nofollow">https://pypi.org/project/DendroPy/</a></p>]]></description>
	<dc:creator>Seema Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</guid>
	<pubDate>Wed, 09 Jan 2019 11:00:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library</link>
	<title><![CDATA[visNetwork: an R package for network visualization, using vis.js javascript library]]></title>
	<description><![CDATA[<div id="introduction">
<p><strong>visNetwork</strong>&nbsp;is an R package for network visualization, using&nbsp;<strong>vis.js</strong>&nbsp;javascript library (<a href="http://visjs.org/">http://visjs.org/</a>). All remarks and bugs are welcome on github :&nbsp;<a href="https://github.com/datastorm-open/visNetwork">https://github.com/datastorm-open/visNetwork</a>.</p>
</div>
<div id="features">
<h2>Features</h2>
<p>Based on&nbsp;<a href="http://www.htmlwidgets.org/">htmlwidgets</a>, so :</p>
<ul>
<li>compatible with&nbsp;<a href="http://shiny.rstudio.com/">shiny</a>, R Markdown documents, and RStudio viewer</li>
</ul>
<p>The package proposes all the features available in&nbsp;<strong>vis.js</strong>&nbsp;API, and even more with special features for R :</p>
<ul>
<li>easy to use</li>
<li>custom shapes, styles, colors, sizes, &hellip;</li>
<li>works smooth on any modern browser for up to a few thousand nodes and edges</li>
<li>interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, &hellip;)</li>
<li>visualize&nbsp;<code>rpart</code>&nbsp;tree</li>
<li></li>
</ul>
</div><p>Address of the bookmark: <a href="https://datastorm-open.github.io/visNetwork/" rel="nofollow">https://datastorm-open.github.io/visNetwork/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</guid>
	<pubDate>Thu, 24 Jun 2021 05:43:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43101/luigi-a-python-package-that-helps-you-build-complex-pipelines-of-batch-jobs</link>
	<title><![CDATA[Luigi: a Python package that helps you build complex pipelines of batch jobs.]]></title>
	<description><![CDATA[<p>Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more.</p>
<p>Run <code>pip install luigi</code> to install the latest stable version from <a href="https://pypi.python.org/pypi/luigi">PyPI</a>. <a href="https://luigi.readthedocs.io/en/stable/">Documentation for the latest release</a> is hosted on readthedocs.</p>
<p>Run <code>pip install luigi[toml]</code> to install Luigi with <a href="https://luigi.readthedocs.io/en/stable/configuration.html">TOML-based configs</a> support.</p><p>Address of the bookmark: <a href="https://github.com/spotify/luigi" rel="nofollow">https://github.com/spotify/luigi</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33791/slactree-svg-large-annotated-circular-tree-drawing</guid>
	<pubDate>Mon, 03 Jul 2017 08:02:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33791/slactree-svg-large-annotated-circular-tree-drawing</link>
	<title><![CDATA[slacTree: SVG Large Annotated Circular Tree drawing]]></title>
	<description><![CDATA[<p>A simple, extensible, Perl script for producing figures of large phylogenetic trees.</p>
<ul>
<li>While there are many other tree drawing programs, slacTree was originally written in 2009 to fill a need for producing publication quality figures of circular trees with more than 1000 taxa with custom annotations</li>
<li>Because it is a single Perl script with very few dependencies, it is easy to run, and easy to further customize</li>
<li>SVG is used because it is a scalable format allowing for very small representations of entire trees or highly magnified regions with unlimited resolution</li>
<li>Circular and radial trees are more compact than linear representations</li>
<li></li>
</ul>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/mccrowjp/slacTree" rel="nofollow">https://github.com/mccrowjp/slacTree</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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