CEA: CEA

In wulingyun/CopTea: Combinatorial OPTimization based Enrichment Analysis

Description

A novel combination-based method for gene set functional enrichment analysis.

Usage

CEA(resultmap, active_gene, d = 0, times = 1, trace = TRUE)

Arguments

resultmap	The annotation matrix of enrichment analysis. Rows are genes and columns are categories.
active_gene	The input character active gene list.
d	A stochastic tolerance paramter to add randomness to CEA algorithm.
times	The repeated time of CEA algorithm. Positive integer variable.
trace	Logical variable indicated whether tracing information on the solving progress is produced.

Details

This function performs the CEA algorithm to perform the enrichment analysis. CEA is based on a multi-objective optimization problem, and the adapted IMPROVED GREEDY algorithm was used to approximatively solve the problem.

Value

This function will return a list with the following components:

p.values	The sorted Fisher's exact test p-values of the identified category sets.
coverage	The related coverage of the corresponding category set.
category	The identified category set corresponding to the sorted p-values.
annotation	The pre-processed original annotation matrix.

References

Duanchen Sun, Yinliang Liu, Xiang-Sun Zhang, Ling-Yun Wu. CEA: Combination-based gene set functional enrichment analysis. Scientific Reports, 8:13085, 2018.

wulingyun/CopTea documentation built on Dec. 4, 2019, 2:59 p.m.