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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39200?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</guid>
	<pubDate>Sat, 20 Mar 2021 00:28:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42974/list-of-bioinformatics-packages-for-ngs-analysis</link>
	<title><![CDATA[List of bioinformatics packages for NGS analysis !]]></title>
	<description><![CDATA[<p>Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.</p><ul>
<li><a href="https://github.com/Bioconductor">Bioconductor</a>&nbsp;&ndash; A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [&nbsp;<a href="https://link.springer.com/article/10.1186/gb-2004-5-10-r80">paper-2004</a>&nbsp;|&nbsp;<a href="https://www.bioconductor.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/biopython/biopython">Biopython</a>&nbsp;&ndash; Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the&nbsp;<a href="http://open-bio.org/">Open Bioinformatics Foundation</a>. Contains the very useful&nbsp;<a href="https://biopython.org/DIST/docs/api/Bio.Entrez-module.html">Entrez</a>&nbsp;package for API access to the NCBI databases. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/19304878">paper-2009</a>&nbsp;|&nbsp;<a href="https://biopython.org/">web</a>&nbsp;]</li>
<li><a href="https://github.com/bioconda">Bioconda</a>&nbsp;&ndash; A channel for the&nbsp;<a href="http://conda.pydata.org/docs/intro.html">conda package manager</a>&nbsp;specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with&nbsp;<code>conda install</code>) bioinformatics packages. [&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29967506">paper-2018</a>&nbsp;|&nbsp;<a href="https://bioconda.github.io/">web</a>&nbsp;]</li>
<li><a href="https://github.com/BioJulia">BioJulia</a>&nbsp;&ndash; Bioinformatics and computational biology infastructure for the Julia programming language. [&nbsp;<a href="https://biojulia.net/">web</a>&nbsp;]</li>
<li><a href="https://github.com/rust-bio/rust-bio">Rust-Bio</a>&nbsp;&ndash; Rust implementations of algorithms and data structures useful for bioinformatics. [&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/early/2015/10/06/bioinformatics.btv573.short?rss=1">paper-2016</a>&nbsp;]</li>
<li><a href="https://github.com/seqan/seqan3">SeqAn</a>&nbsp;&ndash; The modern C++ library for sequence analysis.</li>
</ul>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Tue, 25 Dec 2018 21:20:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38535/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.<p>Address of the bookmark: <a href="https://github.com/wdecoster/nanopack" rel="nofollow">https://github.com/wdecoster/nanopack</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38634/eyechrom-visualizing-chromosome-count-data-from-plants</guid>
	<pubDate>Tue, 08 Jan 2019 10:20:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38634/eyechrom-visualizing-chromosome-count-data-from-plants</link>
	<title><![CDATA[EyeChrom: Visualizing Chromosome Count Data From Plants]]></title>
	<description><![CDATA[<p><span>It's goal is to show chromosmal data per genus. Select the genus, and the plot will show the records found for it in the Chromosome Counts Database. note: Report an issue via Gihub: github.com/roszenil/CCDBcurator and github.com/RodrigoRivero/EyeChrom</span></p>
<p>https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.1207</p><p>Address of the bookmark: <a href="http://eyechrom.com:3838/EyeChrom/" rel="nofollow">http://eyechrom.com:3838/EyeChrom/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40525/heatmaply-popular-graphical-method-for-visualizing-high-dimensional-data</guid>
	<pubDate>Sat, 11 Jan 2020 07:34:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40525/heatmaply-popular-graphical-method-for-visualizing-high-dimensional-data</link>
	<title><![CDATA[heatmaply: popular graphical method for visualizing high-dimensional data]]></title>
	<description><![CDATA[<p>This work is based on ggplot2 and plotly.js engine. It produces similar heatmaps as d3heatmap, with the advantage of speed (plotly.js is able to handle larger size matrix), and the ability to zoom from the dendrogram.</p>
<p>heatmaply also provides an interface based around the&nbsp;<a href="https://cran.r-project.org/package=plotly">plotly R package</a>. This interface can be used by choosing&nbsp;<code>plot_method = "plotly"</code>&nbsp;instead of the default&nbsp;<code>plot_method = "ggplot"</code>. This interface can provide smaller objects and faster rendering to disk in many cases and provides otherwise almost identical features.</p>
<p>Documentation for this package is also available as a&nbsp;<a href="https://cran.r-project.org/package=pkgdown">pkgdown</a>&nbsp;site:&nbsp;<a href="http://talgalili.github.io/heatmaply/">http://talgalili.github.io/heatmaply/</a></p><p>Address of the bookmark: <a href="http://talgalili.github.io/heatmaply/articles/heatmaply.html" rel="nofollow">http://talgalili.github.io/heatmaply/articles/heatmaply.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</guid>
	<pubDate>Tue, 02 May 2023 00:48:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44313/orthovenn3-an-integrated-platform-for-exploring-and-visualizing-orthologous-data-across-genomes</link>
	<title><![CDATA[OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes]]></title>
	<description><![CDATA[<p><span>OrthoVenn3 is a powerful tool for comparative genomics analysis, used as a web server for full genome comparisons, annotation, and evolutionary analysis of orthologous clusters across multiple species. It has already been used by thousands of users from over 60 countries.</span></p><p>Address of the bookmark: <a href="https://orthovenn3.bioinfotoolkits.net/" rel="nofollow">https://orthovenn3.bioinfotoolkits.net/</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</guid>
	<pubDate>Mon, 25 Jun 2018 17:22:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]></title>
	<description><![CDATA[
<p>chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>

<p>https://cran.r-project.org/web/packages/chromoMap/index.html</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</guid>
	<pubDate>Thu, 23 Nov 2017 09:55:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data</link>
	<title><![CDATA[poRe: an R package for the visualization and analysis of nanopore sequencing data]]></title>
	<description><![CDATA[<p><strong>Motivation:</strong>&nbsp;The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.</p>
<p><strong>Results:</strong>&nbsp;Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.</p>
<p><strong>Availability and implementation:</strong>&nbsp;poRe is released as a package for R at&nbsp;<a href="http://sourceforge.net/projects/rpore/" target="">http://sourceforge.net/projects/rpore/</a>&nbsp;. A tutorial and further information are available at&nbsp;<a href="https://sourceforge.net/p/rpore/wiki/Home/" target="">https://sourceforge.net/p/rpore/wiki/Home/</a></p>
<p><strong>Contact:</strong><a href="mailto:mick.watson@roslin.ed.ac.uk" target="">mick.watson@roslin.ed.ac.uk</a></p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/1/114/2365693" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/1/114/2365693</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</guid>
	<pubDate>Fri, 10 Aug 2018 18:41:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37527/nanopack-visualizing-and-processing-long-read-sequencing-data</link>
	<title><![CDATA[NanoPack: visualizing and processing long-read sequencing data]]></title>
	<description><![CDATA[<p>The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at&nbsp;<a href="https://github.com/wdecoster/nanopack" target="">https://github.com/wdecoster/nanopack</a>, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at&nbsp;<a href="http://nanoplot.bioinf.be/" target="">http://nanoplot.bioinf.be</a>&nbsp;and command line tools.</p>
<p>&nbsp;https://academic.oup.com/bioinformatics/article/34/15/2666/4934939</p><p>Address of the bookmark: <a href="https://github.com/wdecoster/nanoQC" rel="nofollow">https://github.com/wdecoster/nanoQC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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