This is the development version of SplineDV; for the stable release version, see SplineDV.
Differential Variability (DV) analysis for single-cell RNA sequencing data. (e.g. Identify Differentially Variable Genes across two experimental conditions)Bioconductor version: Development (3.22)
A spline based scRNA-seq method for identifying differentially variable (DV) genes across two experimental conditions. Spline-DV constructs a 3D spline from 3 key gene statistics: mean expression, coefficient of variance, and dropout rate. This is done for both conditions. The 3D spline provides the âexpectedâ behavior of genes in each condition. The distance of the observed mean, CV and dropout rate of each gene from the expected 3D spline is used to measure variability. As the final step, the spline-DV method compares the variabilities of each condition to identify differentially variable (DV) genes.
Author: Shreyan Gupta [aut, cre] ORCID: 0000-0002-1904-9862 , James Cai [aut] ORCID: 0000-0002-8081-6725
Maintainer: Shreyan Gupta <xenon8778 at tamu.edu>
Citation (from within R, entercitation("SplineDV")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("SplineDV")
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("SplineDV")Follow Installation instructions to use this package in your R session.
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