Evaluation and comparison of multi-omics data integration methods for cancer subtyping
Fig 3
Clustering-based performance of Dataset group #1 Nine-cancer Datasets.
We use “iCB”, “LRA”, “moC”, “CIM”, “MNMF”, and “SGAN” to represent iClusterBayes, LRAcluster, moCluster, CIMLR, MultiNMF, and Subtype-GAN respectively. (A) Silhouette coefficient based on the suggested k of methods. We set k-max as 8 and let each method suggest the best k. Each of the 11 data points in a box represents a silhouette coefficient of the subtyping results based on the method suggested k obtained by the corresponding method using one of the 11 possible combinations of data types. (B) Silhouette coefficient based on all the possible k. Each of the 11 data points in a box represents the average silhouette coefficient of the subtyping results from k = 2 to 8 obtained by the corresponding method using one of the 11 possible combinations of data types.