Table 3.
Performance ranking of MOI methods across different test scenarios
| Test case | Top method | Runner-up | Notable performer |
|---|---|---|---|
| Sample size | SNF (5/10) | NEMO (2/10) | PP (2/10) |
| Feature selection | SNF (4/10) | NEMO (2/10) | PP, CC (2/10 each) |
| Balance | SNF, NEMO (3/10 each) | PP (2/10) | CC (1/10) |
| Noise tolerance | PP (3/10) | SNF, NEMO, CC (2/10 each) | - |
| Subtype combination | SNF (5/10) | NEMO (2/10) | MOFA, CC (1/10 each) |
| Omics (Subtype) | NEMO (4/10) | SNF, Spectrum (2/10 each) | CC, IntNMF (1/10 each) |
| Omics (Gender) | CC (4/9) | LRAcluster (2/9) | SNF, COCA, IntNMF (1/9 each) |
| Omics (Stage) | NEMO (5/10) | PP, CC (2/10 each) | COCA (1/10) |
| Omics (Age) | NEMO (3/10) | IntNMF, CC, LRAcluster (2/10 each) | Spectrum (1/10) |
A comparison of ten multi-omics integration methods across various test scenarios. Numbers in parentheses indicate the frequency of achieving the highest cluster score out of total cases (e.g., 5/10 means the method achieved the highest score in 5 out of 10 cancer types). Top method indicates the best performing method in each test scenario, followed by the second-best performer (Runner-up) and other methods showing notable performance (Notable Performer). Test cases include fundamental computational assessments (sample size, feature selection, balance, noise tolerance) and biological analyses (subtype and omics combinations with various clinical features). The gender analysis includes only 9 cases due to the exclusion of one cancer type with extreme gender imbalance