SEPA

DOI: 10.18129/B9.bioc.SEPA    

SEPA

Bioconductor version: Release (3.6)

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 jhu.edu>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("SEPA")

Documentation

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

browseVignettes("SEPA")

 

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

Details

biocViews	GO, GUI, GeneExpression, Software, Visualization
Version	1.8.0
In Bioconductor since	BioC 3.2 (R-3.2) (2.5 years)
License	GPL(>=2)
Depends	R (>= 2.10.0)
Imports	ggplot2, shiny, topGO, segmented, reshape2, org.Hs.eg.db, org.Mm.eg.db
LinkingTo
Suggests	knitr
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	SEPA_1.8.0.tar.gz
Windows Binary	SEPA_1.8.0.zip
Mac OS X 10.11 (El Capitan)	SEPA_1.8.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/SEPA
Package Short Url	http://bioconductor.org/packages/SEPA/
Package Downloads Report	Download Stats