Inference of mutation parameters and selective constraint in mammalian coding sequences by approximate Bayesian computation.

Abstract excerpt

We develop an inference method that uses approximate Bayesian computation (ABC) to simultaneously estimate mutational parameters and selective constraint on the basis of nucleotide divergence for protein-coding genes between pairs of species. Our simulations explicitly model CpG hypermutability and transition vs. transversion mutational biases along with negative and positive selection operating on synonymous and...

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