<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/35429?offset=420 https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto Tue, 03 Jul 2018 05:05:55 -0500 https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto <![CDATA[NAViGaTOR: Network Analysis, Visualization and Graphing Toronto]]> Address of the bookmark: http://142.150.188.236/navigatorwp/

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties Mon, 28 Jan 2019 18:38:44 -0600 https://bioinformaticsonline.com/bookmarks/view/38819/upsetr-an-r-package-for-the-visualization-of-intersecting-sets-and-their-properties <![CDATA[UpSetR: An R Package for the Visualization of Intersecting Sets and their Properties]]> UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.

For further details about the original technique see the UpSet website. You can also check out the UpSetR shiny app. Here is the source code for the shiny wrapper.

A Python package called py-upset to create UpSet plots has been created by GitHub user ImSoErgodic.

Address of the bookmark: https://github.com/hms-dbmi/UpSetR/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx Sun, 31 May 2020 02:01:14 -0500 https://bioinformaticsonline.com/bookmarks/view/41736/synvisio-an-interactive-multiscale-synteny-visualization-tool-for-mcscanx <![CDATA[SynVisio: An Interactive Multiscale Synteny Visualization Tool for McScanX.]]> SynVisio lets you explore the results of McScanX a popular synteny and collinearity detection toolkit and generate publication ready images.

SynVisio requires two files to run:

  • The simplified gff file that was used as an input for a McScanX query.
  • The collinearity file generated as an output by McScanX for the same input query.
  • Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. 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.

Address of the bookmark: https://synvisio.github.io/#/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data Thu, 23 Nov 2017 09:55:57 -0600 https://bioinformaticsonline.com/bookmarks/view/34396/pore-an-r-package-for-the-visualization-and-analysis-of-nanopore-sequencing-data <![CDATA[poRe: an R package for the visualization and analysis of nanopore sequencing data]]> Motivation: The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.

Results: Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.

Availability and implementation: poRe is released as a package for R at http://sourceforge.net/projects/rpore/ . A tutorial and further information are available at https://sourceforge.net/p/rpore/wiki/Home/

Contact:mick.watson@roslin.ed.ac.uk

Address of the bookmark: https://academic.oup.com/bioinformatics/article/31/1/114/2365693

]]> Jit https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes Mon, 25 Jun 2018 17:22:24 -0500 https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes <![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]> chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.

https://cran.r-project.org/web/packages/chromoMap/index.html

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution Fri, 24 Aug 2018 09:50:01 -0500 https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution <![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]> Mulan: Multiple-sequence local alignment and visualization for studying function and evolution

Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs Thu, 23 Jan 2020 07:33:46 -0600 https://bioinformaticsonline.com/bookmarks/view/40594/gfaviz-flexible-and-interactive-visualization-of-gfa-sequence-graphs <![CDATA[GfaViz: flexible and interactive visualization of GFA sequence graphs]]> GFA (Graphical Fragment Assembly) is an emerging standard format for representing sequence graphs. Although it was originally conceived as a format for sequence assembly (hence the name), and this remains its core application, it is more general, and able to represent many different types of sequence graphs, including scaffolding graphs, alignment graphs, variant graphs and splicing graphs.

Address of the bookmark: https://github.com/ggonnella/gfaviz

]]> Jit https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes Tue, 09 May 2023 19:38:52 -0500 https://bioinformaticsonline.com/bookmarks/view/44318/proksee-in-depth-characterization-and-visualization-of-bacterial-genomes <![CDATA[Proksee: in-depth characterization and visualization of bacterial genomes]]> Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.

Address of the bookmark: https://proksee.ca/

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes Tue, 10 Sep 2024 04:54:55 -0500 https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes <![CDATA[NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes]]> NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes 

image

NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.

https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460

Address of the bookmark: https://github.com/hewm2008/NGenomeSyn

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/42313/crbhits-from-conditional-reciprocal-best-hits-to-codon-alignments-and-kaks-in-r Wed, 11 Nov 2020 23:06:03 -0600 https://bioinformaticsonline.com/bookmarks/view/42313/crbhits-from-conditional-reciprocal-best-hits-to-codon-alignments-and-kaks-in-r <![CDATA[CRBHits: From Conditional Reciprocal Best Hits to Codon Alignments and Ka/Ks in R]]> CRBHits is a coding sequence (CDS) analysis pipeline in R (R Core Team, 2019). It reimplements the Conditional Reciprocal Best Hit (CRBH) algorithm crb-blast and covers all necessary steps from sequence similarity searches, codon alignments to Ka/Ks calculations and synteny. The new R package targets ecology, population and evolutionary biologists working in the field of comparative genomics.

Address of the bookmark: https://gitlab.gwdg.de/mpievolbio-it/crbhits

]]> Shruti Paniwala