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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39903?offset=150</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</guid>
	<pubDate>Fri, 17 Feb 2017 09:06:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31018/j-circos</link>
	<title><![CDATA[J-Circos]]></title>
	<description><![CDATA[<p>Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.</p><p>Address of the bookmark: <a href="http://www.australianprostatecentre.org/research/software/jcircos" rel="nofollow">http://www.australianprostatecentre.org/research/software/jcircos</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</guid>
	<pubDate>Fri, 03 Mar 2017 08:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</link>
	<title><![CDATA[MyCC: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes]]></title>
	<description><![CDATA[<p><span>MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments.</span></p>
<p><span>More at&nbsp;http://www.nature.com/articles/srep24175</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/sb2nhri/files/MyCC/" rel="nofollow">https://sourceforge.net/projects/sb2nhri/files/MyCC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</guid>
	<pubDate>Mon, 06 Mar 2017 04:03:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</link>
	<title><![CDATA[MaxBin: software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm.]]></title>
	<description><![CDATA[<p><span>MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page.</span><br><br><span>Users can use MEGAN or similar software on MaxBin bins to find the taxonomy of each bin after the binning process is finished.</span></p>
<p>https://academic.oup.com/bioinformatics/article/32/4/605/1744462/MaxBin-2-0-an-automated-binning-algorithm-to<br><br><span>The most recent version of MaxBin is 2.2, which supports the analysis of coassemblies of multiple samples. It is available at this JBEI downloads sites as well as&nbsp;</span><a href="https://sourceforge.net/projects/maxbin/" target="_blank">MaxBin</a><span>&nbsp;and&nbsp;</span><a href="https://sourceforge.net/projects/maxbin2/" target="_blank">MaxBin 2.0</a><span>&nbsp;sourceforge sites.</span></p><p>Address of the bookmark: <a href="http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html" rel="nofollow">http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</guid>
	<pubDate>Tue, 07 Mar 2017 08:59:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</link>
	<title><![CDATA[GroopM: Metagenomic binning toolset]]></title>
	<description><![CDATA[<p>GroopM is a metagenomic binning toolset. It leverages spatio-temoral<br>dynamics (differential coverage) to accurately (and almost automatically)<br>extract population genomes from multi-sample metagenomic datasets.</p>
<p>GroopM is largely parameter-free. Use: groopm -h for more info.</p>
<p>For installation and usage instructions see : http://ecogenomics.github.io/GroopM/</p><p>Address of the bookmark: <a href="https://github.com/ecogenomics/GroopM" rel="nofollow">https://github.com/ecogenomics/GroopM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32481/sspace</guid>
	<pubDate>Fri, 05 May 2017 05:42:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32481/sspace</link>
	<title><![CDATA[SSPACE]]></title>
	<description><![CDATA[<p>SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" rel="nofollow">https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</guid>
	<pubDate>Thu, 29 Jun 2017 11:54:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33720/deschrambler</link>
	<title><![CDATA[DESCHRAMBLER]]></title>
	<description><![CDATA[<p>DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools</p>
<p>You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/</p><p>Address of the bookmark: <a href="https://github.com/jkimlab/DESCHRAMBLER" rel="nofollow">https://github.com/jkimlab/DESCHRAMBLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</guid>
	<pubDate>Wed, 14 Feb 2018 02:49:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder</link>
	<title><![CDATA[MeDuSa: a multi-draft based scaffolder]]></title>
	<description><![CDATA[<p><span>MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.&nbsp;</span></p><p>Address of the bookmark: <a href="https://github.com/combogenomics/medusa" rel="nofollow">https://github.com/combogenomics/medusa</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</guid>
	<pubDate>Wed, 21 Mar 2018 12:25:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization</link>
	<title><![CDATA[GMOL: An Interactive Tool for 3D Genome Structure Visualization]]></title>
	<description><![CDATA[<p><span>GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/srep20802" rel="nofollow">https://www.nature.com/articles/srep20802</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</guid>
	<pubDate>Wed, 20 Jun 2018 10:15:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36997/cgview-circular-genome-viewer</link>
	<title><![CDATA[CGView - Circular Genome Viewer]]></title>
	<description><![CDATA[CGView is a Java package for generating high quality, zoomable maps of circular genomes. Its primary purpose is to serve as a component of sequence annotation pipelines, as a means of generating visual output suitable for the web. Feature information and rendering options are supplied to the program using an XML file, a tab delimited file, or an NCBI ptt file. CGView converts the input into a graphical map (PNG, JPG, or Scalable Vector Graphics format), complete with labels, a title, legends, and footnotes. In addition to the default full view map, the program can generate a series of hyperlinked maps showing expanded views. The linked maps can be explored using any web browser, allowing rapid genome browsing, and facilitating data sharing. The feature labels in maps can be hyperlinked to external resources, allowing CGView maps to be integrated with existing web site content or databases. For examples of the various output types, see the CGView gallery.

http://wishart.biology.ualberta.ca/cgview/gallery.html

http://stothard.afns.ualberta.ca/downloads/CCT/index.html

https://www.gview.ca/wiki/GView/WebHome

https://server.gview.ca/

http://stothard.afns.ualberta.ca/cgview_server/

Paper https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbx081/4037458<p>Address of the bookmark: <a href="http://wishart.biology.ualberta.ca/cgview/" rel="nofollow">http://wishart.biology.ualberta.ca/cgview/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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