DOI: 10.18129/B9.bioc.SEPA    

This is the development version of SEPA; for the stable release version, see SEPA.


Bioconductor version: Development (3.9)

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.

Author: Zhicheng Ji, Hongkai Ji

Maintainer: Zhicheng Ji <zji4 at>

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


To install this package, start R (version "3.6") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
BiocManager::install("SEPA", version = "3.9")

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


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



PDF R Script SEPA: Single-Cell Gene Expression Pattern Analysis
PDF   Reference Manual


biocViews GO, GUI, GeneExpression, Software, Visualization
Version 1.13.0
In Bioconductor since BioC 3.2 (R-3.2) (3.5 years)
License GPL(>=2)
Depends R (>= 2.10.0)
Imports ggplot2, shiny, topGO, segmented, reshape2,,
Suggests knitr
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 SEPA_1.13.0.tar.gz
Windows Binary
Mac OS X 10.11 (El Capitan) SEPA_1.13.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Package Short Url
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