
MA

MAP


BVS: EB prior +int

0.84±0.12

1.00±0.16

BVS: flat prior +int

0.86±0.11

1.26±0.17

BVS: ‘incorrect’ prior +int

0.93±0.15

1.22±0.17

BVS: MRF prior +int

0.86±0.11

1.24±0.17

Lasso +int

0.73±0.10

Li&Li

0.96±0.21

Baseline linear

1.00±0.14

 Predictions using leaveoneoutcrossvalidation (see text for details). Results shown are mean absolute predictive errors ± SEM for the following methods: Bayesian variable selection (BVS) with biologically informative pathwaybased prior with source and strength parameters set by empirical Bayes, BVS with flat prior, BVS with ‘incorrect’ prior (contradicting empirical Bayes; see text for details), BVS with a Markov random field (MRF) prior, Lasso regression, penalisedlikelihood approach proposed by Li and Li[21], and a baseline linear regression without interaction terms including all 11 predictors. ‘+int’ denotes linear model with interaction terms. For BVS, predictions made using the posterior predictive distribution with exact model averaging (‘MA’) and using the maximum a posteriori model (‘MAP’).