This means that we can compute the Bayes factor for assessing the evidence against the null model by using only the causal SNPs and that the marginal likelihood is proportional to this expression. CAVIARBF utilizes this result, although without a mathematical derivation explicitly shown in Chen et al. (2015). Note that the correlation submatrix RCC is not invertible if there is almost perfect collinearity among the SNPs in C. To handle this case, we have implemented an option in FINEMAP to set the posterior probability of a causal configuration to zero if it contains at least one SNP pair with absolute correlation greater or equal to some specified threshold.
