To install this package, start R and enter:

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

In most cases, you don't need to download the package archive at all.

SEPA

 

SEPA

Bioconductor version: Release (3.5)

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>

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

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 1.6.0
In Bioconductor since BioC 3.2 (R-3.2) (2 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.

Package Source SEPA_1.6.0.tar.gz
Windows Binary SEPA_1.6.0.zip
Mac OS X 10.11 (El Capitan) SEPA_1.6.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/SEPA/tree/release-3.5
Package Short Url http://bioconductor.org/packages/SEPA/
Package Downloads Report Download Stats

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