<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/40964? https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library Wed, 09 Jan 2019 11:00:32 -0600 https://bioinformaticsonline.com/bookmarks/view/38646/visnetwork-an-r-package-for-network-visualization-using-visjs-javascript-library <![CDATA[visNetwork: an R package for network visualization, using vis.js javascript library]]>

visNetwork is an R package for network visualization, using vis.js javascript library (http://visjs.org/). All remarks and bugs are welcome on github : https://github.com/datastorm-open/visNetwork.

Features

Based on htmlwidgets, so :

  • compatible with shiny, R Markdown documents, and RStudio viewer

The package proposes all the features available in vis.js API, and even more with special features for R :

  • easy to use
  • custom shapes, styles, colors, sizes, …
  • works smooth on any modern browser for up to a few thousand nodes and edges
  • interactivity controls (highlight, collapsed nodes, selection, zoom, physics, movement of nodes, tooltip, events, …)
  • visualize rpart tree

Address of the bookmark: https://datastorm-open.github.io/visNetwork/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis Wed, 12 Feb 2020 12:40:54 -0600 https://bioinformaticsonline.com/bookmarks/view/41006/netgo-r-shiny-package-for-network-integrated-pathway-enrichment-analysis <![CDATA[netGO: R-Shiny package for network-integrated pathway enrichment analysis]]> netGO is an R/Shiny package for network-integrated pathway enrichment analysis.
netGO provides user-interactive visualization of enrichment analysis results and related networks.

Currently, netGO supports analysis for four species (Human, Mouse, Arabidopsis thaliana,and Yeast)
These data are available from netGO-Data repository.

https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635

Address of the bookmark: https://github.com/unistbig/netGO

]]> 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/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/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements Thu, 14 Dec 2023 12:33:19 -0600 https://bioinformaticsonline.com/bookmarks/view/44414/reconplot-an-r-package-for-the-visualization-and-interpretation-of-genomic-rearrangements <![CDATA[ReConPlot: an R package for the visualization and interpretation of genomic rearrangements]]> ReConPlot (REarrangement and COpy Number PLOT), an R package that provides functionalities for the joint visualization of SCNAs and SVs across one or multiple chromosomes. ReConPlot is based on the popular ggplot2 package, thus allowing customization of plots and the generation of publication-quality figures with minimal effort.

Address of the bookmark: https://academic.oup.com/bioinformatics/article/39/12/btad719/7460198?login=false

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes Fri, 12 Apr 2019 05:30:41 -0500 https://bioinformaticsonline.com/bookmarks/view/39244/chromomap-an-r-package-for-interactive-visualization-and-annotation-of-chromosomes <![CDATA[chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes]]> Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism 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. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. 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.

Address of the bookmark: https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots Fri, 20 May 2016 11:01:13 -0500 https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots <![CDATA[RCircos: an R package for Circos 2D track plots]]> RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.

More at https://bitbucket.org/henryhzhang/rcircos/src

Address of the bookmark: https://bitbucket.org/henryhzhang/rcircos/src

]]> Jit 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/news/view/21241/pacman Mon, 16 Feb 2015 12:15:17 -0600 https://bioinformaticsonline.com/news/view/21241/pacman <![CDATA[Pacman]]> The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.

Function names in the pacman package follow the format of p_xxx where ‘xxx’ is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn’t available locally it will install it for you.

Installation

To download the development version of pacman:

Download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the devtools package to install the development version:

## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")

Note: Windows users need Rtools and devtools to install this way.

More at https://github.com/trinker/pacman

 

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler Thu, 16 Jun 2016 18:57:03 -0500 https://bioinformaticsonline.com/bookmarks/view/27850/clusterprofiler <![CDATA[clusterProfiler]]> statistical analysis and visulization of functional profiles for genes and gene clusters

Bioconductor version: Release (3.3)

This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.

Author: Guangchuang Yu <guangchuangyu at gmail.com> with contributions from Li-Gen Wang and Giovanni Dall'Olio.

Maintainer: Guangchuang Yu <guangchuangyu at gmail.com>

Citation (from within R, enter citation("clusterProfiler")):

Yu G, Wang L, Han Y and He Q (2012). “clusterProfiler: an R package for comparing biological themes among gene clusters.” OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.
Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("clusterProfiler")

https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

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