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Table 1 Models and factors that discriminate the tissue of origins via joint and separate analysis

From: Multilevel omic data integration in cancer cell lines: advanced annotation and emergent properties

Methods    Joint   Separate   
Data    mRNA & Prot & miRNA   mRNA Prot miRNA
Best Model    M8   M8 M10 M9
  ME   F1 (0.98, 3×10−13)   F1 (0.98, 3×10−13) F4 (0.93, 7×10−9) F1 (0.98, 3×10−13)
  CO   F2 (0.97, 8×10−11)   F2 (1, 7×9−15) F8 (0.92, 1×10−5) F2 (0.95, 2×10−9)
  LE   F3 (1.0, 9×10−15)   F3 (1, 9×10−15) F1 (0.98, 1×10−12) F3 (1.0, 9×10−15)
Tissue & Factor RE   F4 (0.98, 7×10−13)   F4 (0.97, 7×10−13) F10 (0.93, 1×10−7) F7 (0.93, 3×10−7)
  OV   F5 (0.9, 2×10−3)   F5 (0.92, 1×10−5) F3 (0.9, 3×10−3) F9 (0.92, 8×10−5)
  LC   F7 (0.95, 8×10−10)   F7 (0.92, 8×10−7) F2 (0.93, 3×10−8) NA
  CNS   F8 (0.97, 5×10−10)   F8 (0.93, 2×10−5) F7 (0.95, 5×10−8) F8 (0.95, 1×10−3)
  1. The first 3 rows in the table describe a hierarchy of information about the factor analyzed to extract information relevant for the tissue of origins listed in column 1. Namely: the type of analysis, that is joint or separate. Within the separate analysis 3 options are possible i.e. analysis of mRNA only, or miRNA only or proteins only. Finally, the factor analysis model (M) chosen to describe the tissue is noted in row 3, the number indicates the number of factors obtained from the analysis. Finally each cell in the matrix indicate which factor among the ones available in the model better describe each tissue type. In each cell, accuracy (acc.) and p-value related to the ability of the Factor to predict the tissue are reported.