Table 1.

Selected methods for multi-omics data integration.

Name	Category	Method	Example (cancer type)	Results of data integration	Data type	User-friendliness	Computational platform	References
Joint NMF	unsupervised	matrix factorization	ovarian cancer	cancer subtyping	Multi-data	difficult	Python	Zhang et al., 2011, 2012
iCluster+	unsupervised	matrix factorization	colorectal carcinoma	cancer subtyping	Multi-data	difficult	R	Mo et al., 2013
iClusterBayes	unsupervised	matrix factorization	glioblastoma, kidney cancer	cancer subtyping, disease drivers	Multi-data	difficult	R	Mo et al., 2018
moCluster	unsupervised	matrix factorization	colorectal carcinoma	cancer subtyping	Multi-data	difficult	R	Meng et al., 2016
JIVE	unsupervised	matrix factorization	glioblastoma	cancer subtyping	Multi-data	difficult	MATLAB	Lock et al., 2013
MOFA	unsupervised	PCA	chronic lymphocytic leukemia	novel disease drivers	Multi-data	difficult	R/Python	Argelaguet et al., 2018
rMKL-LPP	unsupervised	multiple kernel learning, similarity-based	glioblastoma	cancer subtyping	Multi-data	difficult	available on request	Speicher and Pfeifer, 2015
NetICS	unsupervised	network-based	multiple cancers	disease drivers	Multi-data	difficult	MATLAB	Dimitrakopoulos et al., 2018
BCC	unsupervised	Bayesian	breast cancer	cancer subtyping	EXP, MET, miRNA, proteomics	difficult	R	Lock and Dunson, 2013
MDI	unsupervised	Bayesian	glioblastoma	cancer subtyping	Multi-data	difficult	MATLAB	Kirk et al., 2012; Savage et al., 2013
PARADIGM	unsupervised	pathway networks, Bayesian	glioblastoma, ovarian cancer	cancer subtyping, therapeutic opportunities	Multi-data	difficult	Python	Vaske et al., 2010
iBAG	supervised	multi-step analysis	glioblastoma	potential biomarkers of survival	Multi-data	difficult	R	Jennings et al., 2013
SNF	unsupervised	network-based, similarity-based	glioblastoma	cancer subtyping	Multi-data	difficult	R/MATLAB	Wang et al., 2014
iOmicsPASS	supervised	network-based	breast cancer	cancer subtyping, disease drivers	Multi-data	difficult	R	Koh et al., 2019
NEMO	unsupervised	similarity-based clustering	acute myeloid leukemia	cancer subtyping	Multi-data	difficult	R	Rappoport and Shamir, 2019
PFA	unsupervised	fusion-based integration	clear cell carcinoma, lung squamous cell carcinoma, glioblastoma	cancer subtyping	Multi-data	difficult	MATLAB	Shi et al., 2017
CCA	unsupervised	correlation based	kidney renal clear cell carcinoma	mechanisms of carcinogenesis	CNV, methylation, gene expression	difficult	R	Lin et al., 2013; Zhou et al., 2015;El-Manzalawy et al., 2018