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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44182?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40937/shinycircos-an-rshiny-application-for-interactive-creation-of-circos-plot</guid>
	<pubDate>Fri, 07 Feb 2020 03:26:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40937/shinycircos-an-rshiny-application-for-interactive-creation-of-circos-plot</link>
	<title><![CDATA[shinyCircos: an R/Shiny application for interactive creation of Circos plot]]></title>
	<description><![CDATA[<p><span>shinyCircos, a graphical user interface for interactive creation of Circos plot. shinyCircos can be easily installed either on computers for personal use or on local or public servers to provide online use to the community. Furthermore, various types of Circos plots could be easily generated and decorated with simple mouse-click.</span></p>
<p>Tutorial&nbsp;<a href="http://shinycircos.ncpgr.cn/shinyCircos_Help_Manual.pdf">http://shinycircos.ncpgr.cn/shinyCircos_Help_Manual.pdf</a></p>
<p>Github&nbsp;<a href="https://github.com/venyao/shinyCircos">https://github.com/venyao/shinyCircos</a></p><p>Address of the bookmark: <a href="http://150.109.59.144:3838/shinyCircos/" rel="nofollow">http://150.109.59.144:3838/shinyCircos/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</guid>
	<pubDate>Thu, 17 Feb 2022 05:37:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools</link>
	<title><![CDATA[Comparative genomics visualisation tools !]]></title>
	<description><![CDATA[<p>Comparative genomics visualisation tools !</p><p>Address of the bookmark: <a href="https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative" rel="nofollow">https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&amp;selected=%23BRIG&amp;tag=Comparative</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</guid>
	<pubDate>Wed, 07 Mar 2018 18:11:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35896/phylographer-graph-visualization-tool</link>
	<title><![CDATA[PhyloGrapher - Graph Visualization Tool]]></title>
	<description><![CDATA[<p><strong>PhyloGrapher</strong><span>&nbsp;is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use&nbsp;</span><strong>PhyloGrapher</strong><span>&nbsp;to visualize any type of relations between elements.&nbsp;</span></p>
<p><span>https://www.youtube.com/watch?v=WgufqYMHCvM</span></p><p>Address of the bookmark: <a href="http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html" rel="nofollow">http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44445/ppanggolin-depicting-microbial-species-diversity-via-a-partitioned-pangenome-graph-of-linked-neighbors</guid>
	<pubDate>Thu, 01 Feb 2024 00:24:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44445/ppanggolin-depicting-microbial-species-diversity-via-a-partitioned-pangenome-graph-of-linked-neighbors</link>
	<title><![CDATA[PPanGGOLiN: Depicting microbial species diversity via a Partitioned PanGenome Graph Of Linked Neighbors]]></title>
	<description><![CDATA[<p dir="auto"><span>PPanGGOLiN</span>&nbsp;(<a href="https://doi.org/10.1371/journal.pcbi.1007732">Gautreau et al. 2020</a>) is a software suite used to create and manipulate prokaryotic pangenomes from a set of either genomic DNA sequences or provided genome annotations. It is designed to scale up to tens of thousands of genomes. It has the specificity to partition the pangenome using a statistical approach rather than using fixed thresholds which gives it the ability to work with low-quality data such as&nbsp;<em>Metagenomic Assembled Genomes (MAGs)</em>&nbsp;or&nbsp;<em>Single-cell Amplified Genomes (SAGs)</em>&nbsp;thus taking advantage of large scale environmental studies and letting users study the pangenome of uncultivable species.</p>
<p dir="auto">A complete documentation is available&nbsp;<a href="https://ppanggolin.readthedocs.io/">here</a>.</p>
<p dir="auto" style="text-align: center;"><a href="https://github.com/labgem/PPanGGOLiN/blob/master/docs/_static/logo.png" target="_blank"><img src="https://github.com/labgem/PPanGGOLiN/raw/master/docs/_static/logo.png" alt="logo" style="border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/labgem/PPanGGOLiN" rel="nofollow">https://github.com/labgem/PPanGGOLiN</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</guid>
	<pubDate>Wed, 14 Nov 2018 04:50:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38212/megahit-an-ultra-fast-single-node-solution-for-large-and-complex-metagenomics-assembly-via-succinct-de-bruijn-graph</link>
	<title><![CDATA[MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph]]></title>
	<description><![CDATA[<p><span>MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct&nbsp;</span><em>de Bruijn</em><span>&nbsp;graph (SdBG) to achieve low memory assembly. MEGAHIT can&nbsp;</span><span>optionally</span><span>&nbsp;utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. MEGAHIT v1.0 or greater also supports IBM Power PC and has been tested on IBM POWER8.</span></p>
<p><span>https://academic.oup.com/bioinformatics/article/31/10/1674/177884</span></p><p>Address of the bookmark: <a href="https://github.com/voutcn/megahit" rel="nofollow">https://github.com/voutcn/megahit</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</guid>
	<pubDate>Fri, 05 Feb 2021 21:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42806/graphunzip-phases-an-assembly-graph-using-hi-c-data-andor-long-reads</link>
	<title><![CDATA[GraphUnzip: Phases an assembly graph using Hi-C data and/or long reads.]]></title>
	<description><![CDATA[<p>GraphUnzip, a fast, memory-efficient and accurate tool to unzip assembly graphs into their constituent haplotypes using long reads and/or Hi-C data. As GraphUnzip only connects sequences in the assembly graph that already had a potential link based on overlaps, it yields high-quality gap-less supercontigs. To demonstrate the efficiency of GraphUnzip, we tested it on a simulated diploid Escherichia coli genome, and on two real datasets for the genomes of the rotifer Adineta vaga and the potato Solanum tuberosum. In all cases, GraphUnzip yielded highly continuous phased assemblies.</p>
<p>https://www.biorxiv.org/content/biorxiv/early/2021/02/01/2021.01.29.428779.full.pdf</p><p>Address of the bookmark: <a href="https://github.com/nadegeguiglielmoni/GraphUnzip" rel="nofollow">https://github.com/nadegeguiglielmoni/GraphUnzip</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</guid>
	<pubDate>Thu, 28 Aug 2025 02:56:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44887/alfapang-alignment-free-algorithm-for-pangenome-graph-construction</link>
	<title><![CDATA[AlfaPang: alignment free algorithm for pangenome graph construction]]></title>
	<description><![CDATA[<p><span>AlfaPang constructs variation graphs, leveraging its alignment-free and reference-free approach, based solely on intrinsic sequence properties. This design allows AlfaPang's runtime and memory usage to scale linearly with the size of input sequences, enabling it to handle significantly larger genome sets compared to other methods.</span></p><p>Address of the bookmark: <a href="https://github.com/AdamCicherski/AlfaPang" rel="nofollow">https://github.com/AdamCicherski/AlfaPang</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</guid>
	<pubDate>Tue, 10 May 2016 08:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27261/segemehl</link>
	<title><![CDATA[segemehl]]></title>
	<description><![CDATA[<p><span>segemehl is a software to map short sequencer reads to reference genomes. Unlike other methods, segemehl is able to detect not only mismatches but also insertions and deletions. Furthermore, segemehl is not limited to a specific read length and is able to map&nbsp;primer- or polyadenylation contaminated reads correctly.&nbsp; segemehl implements a matching strategy based on enhanced suffix arrays (ESA).&nbsp;</span></p>
<p><span>More at&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/</span></p>
<p><span>Manual&nbsp;http://www.bioinf.uni-leipzig.de/Software/segemehl/segemehl_manual_0_1_7.pdf</span></p><p>Address of the bookmark: <a href="http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html" rel="nofollow">http://hoffmann.bioinf.uni-leipzig.de/LIFE/segemehl.html</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33586/genetic-mapper-svg-genetic-map-drawer</guid>
	<pubDate>Sun, 18 Jun 2017 14:11:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33586/genetic-mapper-svg-genetic-map-drawer</link>
	<title><![CDATA[Genetic-mapper: SVG Genetic Map Drawer]]></title>
	<description><![CDATA[<p><span>Genetic-mapper is a perl script able to draw publication-ready vectorial genetic maps.</span></p>
<p>Perl script for creating a publication-ready vectorial genetic/linkage map in Scalable Vector Graphics (SVG) format. The resulting file can either be submitted for publication and edited with any vectorial drawing software like&nbsp;<a href="https://inkscape.org/">Inkscape</a>&nbsp;and&nbsp;<a href="http://www.adobe.com/uk/products/illustrator.html">Abobe Illustrator(R)</a>.</p>
<p>The input file must be a text file with at least the marker name (ID), linkage group (LG) and the position (POS) separeted by tabulations. Additionally a logarithm of odds (LOD score) can be provided. Any extra parameter will be ignored.</p>
<pre><code>map.tsv

ID&lt;tab&gt;LG&lt;tab&gt;POS&lt;tab&gt;LOD
13519  12     0       0.250840894
2718   12     1.0     0.250840893
11040  12     1.6     0.252843341
...</code></pre>
<p>https://github.com/pseudogene/genetic-mapper</p><p>Address of the bookmark: <a href="https://github.com/pseudogene/genetic-mapper" rel="nofollow">https://github.com/pseudogene/genetic-mapper</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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