Fig. 1
From: Sparse multiple co-Inertia analysis with application to integrative analysis of multi -Omics data
From the top to bottom, each row shows the results from mCIA, smCIA, and ssmCIA method respectively. From left to right, each column represents the sample space in \(\mathbb {R}^{n}\), the gene space of the Affymetrix dataset in \(\mathbb {R}^{491}\), the gene space of the Agilent dataset in \(\mathbb {R}^{488}\), and the gene space of the proteomics dataset in \(\mathbb {R}^{94}\). For three panels in the first column, the estimates of the first loading vectors are used. Each different colors represent different cell lines, breast (BR), melanoma (ME), colon (CO), ovarian (OV), renal (RE), lung (LC), central nervous system (CNS, glioblastoma), prostate (PR) cancers and leukemia (LE). For the remaining plots, the estimates of the first two loading vectors are used. Also, colored and labeled points in the plots are top 20 genes that are most distant from the origin, which are more significant compared to other genes. Complete lists of top 20 genes for each panel can be found in the supplementary materials