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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35395?offset=180</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28199/genome-workbench-2107</guid>
	<pubDate>Fri, 01 Jul 2016 12:09:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28199/genome-workbench-2107</link>
	<title><![CDATA[Genome Workbench 2.10.7]]></title>
	<description><![CDATA[<p>Genome Workbench 2.10.7 is here! New features include added support for local custom BLAST databases and improvements to Tree View.</p><p>For the full list of features, improvements and fixes, see the release notes:<a href="https://ncbi.nlm.nih.gov/tools/gbench/releasenotes" target="_blank">https://ncbi.nlm.nih.gov/tools/gbench/releasenotes</a></p><p>New Features</p><ul>
<li>BLAST Tool: added support for local custom BLAST databases</li>
<li>Graphical Sequence View: added log scaling option for graph tracks</li>
<li>Generic Table View:&nbsp;<a href="https://www.ncbi.nlm.nih.gov/tools/gbench/tutorial17">new tutorial</a>&nbsp;added</li>
</ul><p>Bug Fixes and Improvements</p><ul>
<li>Project Tree View: Genomic Collections/Assemblies now show accessions, not just names</li>
<li>Tree View: layout updated to better accommodate nodes of different sizes</li>
<li>Table Import Dialog (MacOS): fixed issue with table visibility</li>
<li>Fixed bug where different molecules IDs in GenBank could resolve to the same sequence</li>
<li>Graphical Sequence View: fixed issue where sequence track was not shown for some sequences</li>
<li>Graphical Sequence View: fixed protein coloration methods</li>
<li>Graphical Sequence View: improved rendering of Markers to better indicate boundaries and produce higher quality PDF images</li>
<li>Create Gene Model tool: fixed scenario when gene model tool failed with local sequences</li>
<li>Search View: ORF Finder &ndash; fixed incorrect protein lengths</li>
<li>Fixed bug with not opening project file (.gbp) on a click</li>
<li>Fixed issues in GVF import</li>
<li>Fixed BLAST Search tool against NCBI databases not working</li>
<li>Fixed tblastn (protein BLAST) not working in standalone mode</li>
<li>Fixed GTF export failure</li>
</ul>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</guid>
	<pubDate>Fri, 21 Oct 2016 04:54:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</link>
	<title><![CDATA[Ribbon !!]]></title>
	<description><![CDATA[<p><span>Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.</span></p>
<p>Script at&nbsp;https://github.com/MariaNattestad/ribbon</p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</guid>
	<pubDate>Wed, 05 Jul 2017 04:11:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33820/circular-visualization-in-r</link>
	<title><![CDATA[Circular Visualization in R]]></title>
	<description><![CDATA[<p>This is the documentation of the&nbsp;<a href="https://cran.r-project.org/package=circlize"><span>circlize</span></a>&nbsp;package. Examples in the book are generated under version 0.4.1.</p>
<p>If you use&nbsp;<span>circlize</span>&nbsp;in your publications, I would be appreciated if you can cite:</p>
<p>Gu, Z. (2014) circlize implements and enhances circular visualization in R. Bioinformatics. DOI:&nbsp;<a href="https://doi.org/10.1093/bioinformatics/btu393">10.1093/bioinformatics/btu393</a></p><p>Address of the bookmark: <a href="http://zuguang.de/circlize_book/book/" rel="nofollow">http://zuguang.de/circlize_book/book/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</guid>
	<pubDate>Fri, 06 Apr 2018 12:07:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36109/sankeynetwork-with-networkd3</link>
	<title><![CDATA[sankeyNetwork with networkD3]]></title>
	<description><![CDATA[<p><span>You can also create&nbsp;</span><a href="http://en.wikipedia.org/wiki/Sankey_diagram">Sankey diagrams</a><span>&nbsp;with&nbsp;</span><code>sankeyNetwork</code><span>. Here is an example using downloaded JSON data:</span></p>
<p><span>https://en.wikipedia.org/wiki/Sankey_diagram</span></p><p>Address of the bookmark: <a href="https://christophergandrud.github.io/networkD3/#sankey" rel="nofollow">https://christophergandrud.github.io/networkD3/#sankey</a></p>]]></description>
	<dc:creator>Jit</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/38745/osprey-network-visualization-system</guid>
	<pubDate>Sun, 20 Jan 2019 05:34:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38745/osprey-network-visualization-system</link>
	<title><![CDATA[Osprey: Network Visualization System]]></title>
	<description><![CDATA[<p>Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from&nbsp;<a href="http://geneontology.org/" title="GENE ONTOLOGY CONSORTIUM">Gene Ontology (GO)</a>&nbsp;annotated interaction data maintained by the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>.</p>
<p>Osprey is developed by the&nbsp;<a href="http://www.tyerslab.com/">TyersLab</a>&nbsp;and is a part of the&nbsp;<a href="https://thebiogrid.org/" title="The BioGRID">BioGRID</a>&nbsp;family of software. It utilizes both&nbsp;<a href="https://www.mysql.com/" title="MySQL Database">MySQL</a>&nbsp;and&nbsp;<a href="http://openjdk.java.net/" title="OpenJDK">Java</a>&nbsp;to operate and is compatible with&nbsp;<a href="https://www.microsoft.com/en-us/windows/" title="Microsoft Windows">Windows</a>,&nbsp;<a href="http://www.ubuntu.com/">Linux</a>, and&nbsp;<a href="http://www.apple.com/" title="Apple">Apple</a>&nbsp;operating systems.</p>
<p>These works were published in&nbsp;<strong>Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22</strong>&nbsp;<a href="http://genomebiology.com/2003/4/3/R22" title="Genome Biology">[Genome Biology]</a>&nbsp;<a href="http://genomebiology.com/content/pdf/gb-2003-4-3-r22.pdf" title="Osprey PDF">[PDF]</a>&nbsp;<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;list_uids=12620107&amp;dopt=Abstract" title="Pubmed">[PubMed]</a>&nbsp;and supported by the&nbsp;<a href="http://www.nih.gov/" title="NIH">National Institutes of Health</a>,&nbsp;<a href="http://www.cihr-irsc.gc.ca/" title="CIHR">Canadian Institutes of Health Research</a>, and&nbsp;<a href="http://www.genomecanada.ca/en/" title="Genome Canada">Genome Canada</a>.</p><p>Address of the bookmark: <a href="https://osprey.thebiogrid.org/" rel="nofollow">https://osprey.thebiogrid.org/</a></p>]]></description>
	<dc:creator>BioJoker</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/blog/view/45273/a-subway-map-for-the-genome</guid>
	<pubDate>Fri, 04 Sep 2026 04:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</link>
	<title><![CDATA[A Subway Map for the Genome]]></title>
	<description><![CDATA[<p>Maya was looking at a genome graph on her computer. There were nodes, branches, and paths going in every direction.</p><p>&ldquo;It&rsquo;s like a subway map,&rdquo; she said, &ldquo;but for DNA.&rdquo;</p><p>That idea is exactly what Sequence Tube Map brings to life.</p><p>Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.</p><p>This makes complex genome graphs much easier to explore.</p><p>Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.</p><p>What once looked like a tangled network now looked like a journey.</p><p>Sequence Tube Map turns the complexity of graph genomes into a visual story&mdash;making it easier for scientists to see how DNA can take different routes.</p><p>Read more at&nbsp; https://github.com/vgteam/sequencetubemap&nbsp;</p><p>and</p><p>https://academic.oup.com/bioinformatics/article/35/24/5318/5542397</p><p>Demo at&nbsp;https://vgteam.github.io/sequenceTubeMap/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</guid>
	<pubDate>Mon, 04 Dec 2017 10:09:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies</link>
	<title><![CDATA[Bandage: interactive visualization of de novo genome assemblies]]></title>
	<description><![CDATA[<p>Bandage (a Bioinformatics Application for Navigating&nbsp;<em>De&nbsp;novo</em>&nbsp;Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing&nbsp;<em>de novo</em>&nbsp;assemblies that are not possible through investigation of contigs alone.</p>
<p><strong>Availability and implementation:</strong>&nbsp;Source code and binaries are freely available at&nbsp;<a href="https://github.com/rrwick/Bandage" target="pmc_ext">https://github.com/rrwick/Bandage</a>. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at&nbsp;<a href="http://rrwick.github.io/Bandage" target="pmc_ext">http://rrwick.github.io/Bandage</a>.</p><p>Address of the bookmark: <a href="http://rrwick.github.io/Bandage/" rel="nofollow">http://rrwick.github.io/Bandage/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</guid>
	<pubDate>Thu, 28 Dec 2017 09:00:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34920/xmatchview-smith-waterman-alignment-visualization</link>
	<title><![CDATA[xmatchview: smith-waterman alignment visualization]]></title>
	<description><![CDATA[<p><span>xmatchview and xmatchview-conifer are imaging tools for comparing the synteny between DNA sequences. It allows users to align 2 DNA sequences in fasta format using cross_match and displays the alignment in a variety of image formats. xmatchview and xmatchview-conifer are written in python and run on linux and windows. They serve as visual tools for analyzing cross_match alignments. Cross_match (Green, P. (1994)&nbsp;</span><a href="http://www.phrap.org/">http://www.phrap.org</a><span>) uses an implementation of the Smith-Waterman algorithm for comparing DNA sequences that is sensitive.</span></p>
<p><span>http://www.bcgsc.ca/platform/bioinfo/software/xmatchview</span></p><p>Address of the bookmark: <a href="https://github.com/warrenlr/xmatchview" rel="nofollow">https://github.com/warrenlr/xmatchview</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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