This is the released version of TrajectoryGeometry; for the devel version, see TrajectoryGeometry.
This Package Discovers Directionality in Time and Pseudo-times Series of Gene Expression PatternsBioconductor version: Release (3.21)
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.
Author: Michael Shapiro [aut, cre] ORCID: 0000-0002-2769-9320
Maintainer: Michael Shapiro <michael.shapiro at crick.ac.uk>
Citation (from within R, entercitation("TrajectoryGeometry")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("TrajectoryGeometry")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("TrajectoryGeometry")Follow Installation instructions to use this package in your R session.
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