densvis

DOI: 10.18129/B9.bioc.densvis    

Density-Preserving Data Visualization via Non-Linear Dimensionality Reduction

Bioconductor version: Release (3.12)

Implements the density-preserving modification to t-SNE and UMAP described by Narayan et al. (2020) . The non-linear dimensionality reduction techniques t-SNE and UMAP enable users to summarise complex high-dimensional sequencing data such as single cell RNAseq using lower dimensional representations. These lower dimensional representations enable the visualisation of discrete transcriptional states, as well as continuous trajectory (for example, in early development). However, these methods focus on the local neighbourhood structure of the data. In some cases, this results in misleading visualisations, where the density of cells in the low-dimensional embedding does not represent the transcriptional heterogeneity of data in the original high-dimensional space. den-SNE and densMAP aim to enable more accurate visual interpretation of high-dimensional datasets by producing lower-dimensional embeddings that accurately represent the heterogeneity of the original high-dimensional space, enabling the identification of homogeneous and heterogeneous cell states. This accuracy is accomplished by including in the optimisation process a term which considers the local density of points in the original high-dimensional space. This can help to create visualisations that are more representative of heterogeneity in the original high-dimensional space.

Author: Alan O'Callaghan [aut, cre], Ashwinn Narayan [aut], Hyunghoon Cho [aut]

Maintainer: Alan O'Callaghan <alan.ocallaghan at outlook.com>

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

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("densvis")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("densvis")

 

HTML R Script Introduction to densvis
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews DimensionReduction, Sequencing, SingleCell, Software, Visualization
Version 1.00.4
In Bioconductor since BioC 3.12 (R-4.0) (< 6 months)
License MIT + file LICENSE
Depends
Imports Rcpp, basilisk, assertthat, reticulate
LinkingTo Rcpp
Suggests knitr, rmarkdown, BiocStyle, ggplot2, Rtsne, uwot, testthat
SystemRequirements
Enhances
URL
BugReports https://github.com/Alanocallaghan/densvis/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package densvis_1.00.4.tar.gz
Windows Binary densvis_1.00.4.zip (32- & 64-bit)
macOS 10.13 (High Sierra) densvis_1.00.4.tgz
Source Repository git clone https://git.bioconductor.org/packages/densvis
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/densvis
Package Short Url https://bioconductor.org/packages/densvis/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.12 Source Archive

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: