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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42160?offset=180</link>
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	<description><![CDATA[]]></description>
	
	<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/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</guid>
	<pubDate>Tue, 16 Mar 2021 05:41:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42963/davi-deep-learning-based-tool-for-alignment-and-single-nucleotide-variant-identification</link>
	<title><![CDATA[DAVI: Deep learning-based tool for alignment and single nucleotide variant identification]]></title>
	<description><![CDATA[<p>DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species</p>
<p>https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf</p><p>Address of the bookmark: <a href="https://github.com/gguptaiitd/NEAT" rel="nofollow">https://github.com/gguptaiitd/NEAT</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33693/circleator</guid>
	<pubDate>Sun, 25 Jun 2017 18:04:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33693/circleator</link>
	<title><![CDATA[Circleator]]></title>
	<description><![CDATA[<p>The Charm City Circleator--or Circleator for short--is a Perl-based visualization tool developed at the&nbsp;<a href="http://igs.umaryland.edu/">Institute for Genome Sciences</a>&nbsp;in the University of Maryland's School of Medicine. Circleator produces circular plots of genome-associated data, like this one:</p>
<p><a href="https://camo.githubusercontent.com/0b414f050a7dcb672386932ee0cd83e5f42d2271/687474703a2f2f6a6f6e617468616e63726162747265652e6769746875622e696f2f436972636c6561746f722f696d616765732f43503030323732352d322d3432302e706e673f7261773d74727565" target="_blank"><img src="https://camo.githubusercontent.com/0b414f050a7dcb672386932ee0cd83e5f42d2271/687474703a2f2f6a6f6e617468616e63726162747265652e6769746875622e696f2f436972636c6561746f722f696d616765732f43503030323732352d322d3432302e706e673f7261773d74727565" alt="Sample Circleator image" title="Sample Circleator Image" style="border: 0px;"></a></p>
<p>Common uses of the tool include:</p>
<ul>
<li>Displaying the sequence and/or genes in a&nbsp;<a href="http://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;flat file.</li>
<li>Highlighting differences and/or similarities in gene content between related organisms.</li>
<li>Comparing SNPs and indels between closely-related strains or serovars.</li>
<li>Comparing gene expression values across multiple samples or timepoints.</li>
<li>Visualizing coverage plots of RNA-Seq read alignments.</li>
</ul>
<h3><a href="https://github.com/jonathancrabtree/Circleator#key-features"></a>Key Features</h3>
<p>Circleator...</p>
<ul>
<li>Builds on&nbsp;<a href="http://www.bioperl.org/">BioPerl</a>&nbsp;and the input file formats that it supports, including:
<ul>
<li><a href="http://www.ncbi.nlm.nih.gov/genbank/">GenBank</a>&nbsp;flat files, GFF, FASTA</li>
</ul>
</li>
<li>Accepts a number of other commonly-used datatypes and file formats:
<ul>
<li><a href="http://bsr.igs.umaryland.edu/">BSR</a>&nbsp;and&nbsp;<a href="http://tandem.bu.edu/trf/trf.html">TRF</a>&nbsp;output,&nbsp;<a href="http://samtools.sourceforge.net/">SAM/BAM</a>&nbsp;files,&nbsp;<a href="http://vcftools.sourceforge.net/">VCF</a>-encoded SNPs, tab-delimited files</li>
</ul>
</li>
<li>Outputs publication-ready figures in the&nbsp;<a href="http://www.w3.org/Graphics/SVG/">SVG</a>&nbsp;(Scalable Vector Graphics) format.</li>
<li>Requires only a single configuration file whose layout mirrors that of the figure itself.
<ul>
<li>Predefined configuration files and "track" types are supplied for common datasets.</li>
<li>Advanced features allow limited analyses to be performed as a figure is drawn.</li>
</ul>
</li>
<li>Includes an extensive set of regression tests.</li>
<li>Offers a prototype web-based GUI (under the "Ringmaster" project.)</li>
</ul>
<p>https://github.com/jonathancrabtree/Circleator</p><p>Address of the bookmark: <a href="https://github.com/jonathancrabtree/Circleator" rel="nofollow">https://github.com/jonathancrabtree/Circleator</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</guid>
	<pubDate>Wed, 06 Dec 2017 09:45:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34543/acana-an-accurate-and-consistent-alignment-tool-for-dna-sequences</link>
	<title><![CDATA[ACANA: An accurate and consistent alignment tool for DNA sequences]]></title>
	<description><![CDATA[<p><span>ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.</span></p><p>Address of the bookmark: <a href="https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm" rel="nofollow">https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34734/smash-an-alignment-free-tool-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Thu, 21 Dec 2017 08:26:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34734/smash-an-alignment-free-tool-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[SMASH: An alignment-free tool to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p style="text-align: justify;"><span>SMASH is a completely alignment-free method to find and visualise rearrangements between pairs of DNA sequences</span>. The detection is based on&nbsp;<span>relative compression</span>, namely using a FCM, also known as Markov model, of high context order (typically 20). The method has been approached with a tool (also called SMASH). For visualization, SMASH outputs a SVG image, with an ideogram output architecture, where the patterns are represented with several HSV values (only value varies). The following image, illustrating the information maps between human and chimpanzee for the several chromosomes, depicts an example:</p>
<p><a href="https://github.com/pratas/smash/blob/master/imgs/HC.png" target="_blank"><img src="https://github.com/pratas/smash/raw/master/imgs/HC.png" alt="ScreenShot" style="border: 0px;"></a></p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/pratas/smash" rel="nofollow">https://github.com/pratas/smash</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/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</guid>
	<pubDate>Tue, 29 May 2018 07:33:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36812/porechop-tool-for-finding-and-removing-adapters-from-oxford-nanopore-reads</link>
	<title><![CDATA[Porechop:  tool for finding and removing adapters from Oxford Nanopore reads]]></title>
	<description><![CDATA[<p>Porechop is a tool for finding and removing adapters from <a href="https://nanoporetech.com/">Oxford Nanopore</a> reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.</p>
<p>Porechop also supports demultiplexing of Nanopore reads that were barcoded with the <a href="https://store.nanoporetech.com/native-barcoding-kit-1d.html">Native Barcoding Kit</a>, <a href="https://store.nanoporetech.com/pcr-barcoding-kit-96.html">PCR Barcoding Kit</a> or <a href="https://store.nanoporetech.com/rapid-barcoding-sequencing-kit.html">Rapid Barcoding Kit</a>.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Porechop" rel="nofollow">https://github.com/rrwick/Porechop</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</guid>
	<pubDate>Thu, 02 Aug 2018 07:39:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</link>
	<title><![CDATA[LSC :a long read error correction tool]]></title>
	<description><![CDATA[<h2>Getting Started</h2>
<p>These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.</p>
<ul>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_requirements.asp">LSC_requirements</a>&nbsp;for running LSC.</li>
<li><a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_download.asp">Download</a>&nbsp;and set-up the LSC package.</li>
<li>Follow the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_tutorial.asp">tutorial</a>&nbsp;to see how LSC works on some example data.</li>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_manual.asp">manual</a>&nbsp;if anything is unclear.</li>
<li>You're ready, Happy LSCing!</li>
</ul>
<h2>Latest publication</h2>
<p><span>Kin Fai Au, Jason Underwood, Lawrence Lee and Wing Hung Wong&nbsp;</span><br><strong>Improving PacBio Long Read Accuracy by Short Read Alignment&nbsp;</strong><span>[</span><a href="http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0046679">Manuscript</a><span>]&nbsp;</span><br><em>PLoS ONE</em><span>&nbsp;2012. 7(10): e46679. doi:10.1371/journal.pone.0046679</span></p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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