SEPA: SEPA

Given single-cell RNA-seq data and true experiment time of cells or pseudo-time cell ordering, SEPA provides convenient functions for users to assign genes into different gene expression patterns such as constant, monotone increasing and increasing then decreasing. SEPA then performs GO enrichment analysis to analysis the functional roles of genes with same or similar patterns.

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("SEPA")
AuthorZhicheng Ji, Hongkai Ji
Bioconductor views GO GUI GeneExpression Visualization
Date of publicationNone
MaintainerZhicheng Ji <zji4@jhu.edu>
LicenseGPL(>=2)
Version1.6.0

View on Bioconductor

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