Dr Roderick D. Ball
Ensis Wood Quality (NZ Forest Research Institute)
We discuss statistical analysis and experimental design for association mapping with reference to case studies from Chapters 7 and 8 of the book “Association Mapping in Plants”, Springer 2007.
Case studies include:
We re-analyse previous results using Bayesian methods. Equivalent Bayes factors are derived from published results and posterior probabilities for putative associations assessed. Bayes factors are derived for the common association tests: the chi-squared, Fisher's exact test, and the TDT and S-TDT tests for discrete and continuous traits. Various methods are used including direct integration, MCMC, and the Savage-Dickey density ratio.
A common theme is the inadequacy of p-values as a measure of evidence for testing scientific hypotheses as noted by Berger and Berry (1998). Higher sample sizes are needed to obtain respectable Bayes factors, and even higher sample sizes are needed to obtain sufficiently high Bayes factors to overcome low prior probabilities for genomic associations.
Session 3b, Biometrics: 13:50 — 14:10, Room 445