Comparative study on gene set and pathway topology-based enrichment methods

BMC Bioinformatics

Table 1 Summary of seven enrichment methods evaluated in this study

Test/Method name	Pathway representation	ORA/ FCS	R-function/ package version	Database support	Null hypothesis
Wilcoxon rank sum	GS	FCS	wilcox.test	Any input	Competitive
Kolmogorov-Smirnov	GS	FCS	ks.test	Any input	Competitive
Fisher’s exact	GS	ORA	fisher.test	Any input	Competitive
SPIA	PT-based	ORA-like	2.12.0.	KEGG	Competitive
CePa ORA	PT-based	ORA-like	0.5.	KEGG, Reactome, NCI-Nature, BioCarta	Competitive
CePa GSA	PT-based	FCS-like	0.5.	KEGG, Reactome, NCI-Nature, BioCarta	Self-contained
PathNet	PT-based	unclass.	1.3.0.	KEGG	Competitive

Methods were classified according to the representation of a pathway into the gene set (GS) enrichment and the pathway topology-based (PT-based) methods. Second column stratifies the methods into over-representation analysis (ORA) and functional class scoring (FCS). However, for PT-based methods this classification is not always explicit, therefore we used ‘-like’ suffix and ‘unclass.’ for an unclassified method. Third column shows the utilized R-functions for GS methods and versions of R-packages of PT-based methods. Next column summarizes the pathways databases which are provided within the R-packages. According to the null hypothesis most of the methods are competitive, only the GSA variant of the CePa method is self-contained

ISSN: 1471-2105