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TrajectoryGeometry

This Package Discovers Directionality in Time and Pseudo-times Series of Gene Expression Patterns

Bioconductor version: 3.23 · Package version: 1.20.0

Given a time series or pseudo-times series of gene expression data, we might wish to know: Do the changes in gene expression in these data exhibit directionality? Are there turning points in this directionality. Do different subsets of the data move in different directions? This package uses spherical geometry to probe these sorts of questions. In particular, if we are looking at (say) the first n dimensions of the PCA of gene expression, directionality can be detected as the clustering of points on the (n-1)-dimensional sphere.

Installation

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

BiocManager::install("TrajectoryGeometry")

Details

MaintainerMichael Shapiro <michael.shapiro@crick.ac.uk>
AuthorMichael Shapiro [aut, cre] (ORCID: <https://orcid.org/0000-0002-2769-9320>)
LicenseMIT + file LICENSE
Downloads rank178
Source branchRELEASE_3_23
biocViewsBiologicalQuestion, GeneExpression, SingleCell, Software, StatisticalMethod

Documentation

Download

Dependencies

Depends: R (>= 4.1)

Imports: pracma, rgl, ggplot2, stats, methods

Suggests: dplyr, knitr, RColorBrewer, rmarkdown