ESEA: ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis
Version 1.0

The package can identify the dysregulated canonical pathways by investigating the changes of biological relationships of pathways in the context of gene expression data. (1) The ESEA package constructs a background set of edges by extracting pathway structure (e.g. interaction, regulation, modification, and binding etc.) from the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther) and the edge sets of pathways for each of the above databases. (2) The ESEA package can can quantify the change of correlation between genes for each edge based on gene expression data with cases and controls. (3) The ESEA package uses the weighted Kolmogorov-Smirnov statistic to calculate an edge enrichment score (EES), which reflects the degree to which a given pathway is associated the specific phenotype. (4) The ESEA package can provide the visualization of the results.

Getting started

Package details

AuthorJunwei Han, Xinrui Shi, Chunquan Li
Bioconductor views Pathways Statistics edge enrichment analysis
Date of publication2015-01-22 15:58:44
MaintainerXinrui Shi <xinrui103@163.com>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("ESEA")

Try the ESEA package in your browser

Any scripts or data that you put into this service are public.

ESEA documentation built on May 30, 2017, 7:28 a.m.