Table 1.
Comparison of the effectiveness of BMSS, SSS and MC3. The 3 rightmost columns show which regressions have been identified by each algorithm
Model | Log-posterior | BMSS | SSS | MC3 |
SFRS17A, GEM, RGS3, SDHC, W26659, ATP6V1F | − 42.33 | Yes | Yes | No |
SFRS17A, TOMM40, RGS3, PJA2, W26659, ATP6V1F | − 42.78 | Yes | No | No |
SFRS17A, RGS3, W26659, ATP6V1F, WSB1, CD19 | − 43.03 | Yes | No | No |
SFRS17A, DPY19L4, RGS3, W26659, ATP6V1F, WSB1 | − 43.17 | Yes | No | Yes |
SFRS17A, RGS3, W26659, ATP6V1F, WSB1, UBE2A | − 43.27 | Yes | Yes | No |
SFRS17A, RGS3, PJA2, W26659, ATP6V1F, XPO1 | − 43.31 | Yes | Yes | Yes |
SFRS17A, RGS3, HSPE1, W26659, ATP6V1F, WSB1 | − 43.34 | Yes | Yes | No |
SFRS17A, GEM, RGS3, W26659, ATP6V1F, RAD21 | − 43.49 | Yes | Yes | Yes |
SFRS17A, GEM, ARF6, KEAP1, W26659, ATP6V1F | − 43.57 | Yes | Yes | No |
SFRS17A, GEM, RGS3, ARF6, W26659, ATP6V1F | − 43.62 | Yes | Yes | No |
SFRS17A, GEM, RGS3, W26659, ATP6V1F, XPO1 | − 43.63 | Yes | Yes | Yes |