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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44616?offset=220</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</guid>
	<pubDate>Sun, 31 May 2020 02:01:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx</link>
	<title><![CDATA[SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.]]></title>
	<description><![CDATA[<p>SynVisio lets you explore the results of&nbsp;<a href="http://chibba.pgml.uga.edu/mcscan2/">McScanX</a>&nbsp;a popular synteny and collinearity detection toolkit and generate publication ready images.</p>
<p>SynVisio requires two files to run:</p>
<ul>
<li>The&nbsp;<strong>simplified gff file</strong>&nbsp;that was used as an input for a McScanX query.</li>
<li>The&nbsp;<strong>collinearity file</strong>&nbsp;generated as an output by McScanX for the same input query.</li>
<li>Optional&nbsp;<strong>track file</strong>&nbsp;in bedgraph format to annotate the generated charts.</li>
</ul>
<p>SynVisio offers different types of visualizations such as&nbsp;<strong>Linear Parallel plots</strong>,&nbsp;<strong>Hive plots</strong>,&nbsp;<strong>Stacked Parallel Plots&nbsp;</strong>and&nbsp;<strong>Dot plots</strong>. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.</p><p>Address of the bookmark: <a href="https://synvisio.github.io/#/" rel="nofollow">https://synvisio.github.io/#/</a></p>]]></description>
	<dc:creator>Jit</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/30002/excavator2tool</guid>
	<pubDate>Wed, 30 Nov 2016 04:09:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</link>
	<title><![CDATA[EXCAVATOR2tool]]></title>
	<description><![CDATA[<p><span>EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.</span><br><span>EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it&rsquo;s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavator2tool/" rel="nofollow">https://sourceforge.net/projects/excavator2tool/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</guid>
	<pubDate>Mon, 07 Aug 2017 18:49:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34141/rami-a-tool-for-identification-and-characterization-of-phylogenetic-clusters-in-microbial-communities</link>
	<title><![CDATA[RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities]]></title>
	<description><![CDATA[<p>RAMI, which clusters related nodes in a phylogenetic tree based on the patristic distance. RAMI also produces indices of cluster properties and other indices used in population and community studies on-the-fly.</p>
<p><strong>Availability:</strong>&nbsp;RAMI is licensed under GNU GPL and can be run or downloaded from&nbsp;<a href="http://www.acgt.se/online.html" target="">http://www.acgt.se/online.html</a>.</p><p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051" rel="nofollow">https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</guid>
	<pubDate>Sun, 10 Dec 2017 17:03:48 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34594/synima-synteny-imaging-tool</link>
	<title><![CDATA[Synima: Synteny Imaging tool]]></title>
	<description><![CDATA[<p><span>Synteny Imaging tool (Synima) written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima &ndash; and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from&nbsp;</span><span><a href="https://github.com/rhysf/Synima"><span>https://github.com/rhysf/Synima</span></a></span><span>&nbsp;under the MIT License.</span></p><p>Address of the bookmark: <a href="https://github.com/rhysf/Synima" rel="nofollow">https://github.com/rhysf/Synima</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</guid>
	<pubDate>Mon, 04 Jun 2018 05:26:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</link>
	<title><![CDATA[EAGLER: a scaffolding tool for long reads.]]></title>
	<description><![CDATA[<p>EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.</p>
<p>The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:</p>
<ul>
<li>Mac OS X 10.11.1</li>
<li>Mac OS X 10.10.3</li>
<li>Ubuntu 14.04 LTS</li>
</ul>

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf<p>Address of the bookmark: <a href="https://github.com/mculinovic/EAGLER" rel="nofollow">https://github.com/mculinovic/EAGLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</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>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</guid>
	<pubDate>Wed, 22 Aug 2018 11:05:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37576/lrcstats-a-tool-for-evaluating-long-reads-correction-methods</link>
	<title><![CDATA[LRCstats: a tool for evaluating long reads correction methods]]></title>
	<description><![CDATA[<p><span>LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.</span></p><p>Address of the bookmark: <a href="https://github.com/cchauve/lrcstats" rel="nofollow">https://github.com/cchauve/lrcstats</a></p>]]></description>
	<dc:creator>Aaryan Lokwani</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</guid>
	<pubDate>Thu, 04 Oct 2018 16:39:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37837/clipcrop-a-tool-for-detecting-structural-variations-with-single-base-resolution-using-soft-clipping-information</link>
	<title><![CDATA[ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information]]></title>
	<description><![CDATA[<p>This is a tool for detecting structural variations using soft-clipping information From&nbsp;<a href="http://samtools.sourceforge.net/SAM1.pdf">SAM</a>&nbsp;files.</p>
<p>https://github.com/shinout/clipcrop</p><p>Address of the bookmark: <a href="https://github.com/shinout/clipcrop" rel="nofollow">https://github.com/shinout/clipcrop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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