Bayesian model search and multilevel inference for SNP association studies

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally ``validated'' in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS322 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Long term outcomes in men screened for abdominal aortic aneurysm : prospective cohort study

PMID: 22563092 [PubMed - indexed for MEDLINE] PMCID: PMC3344734 Free PMC ArticlePeer reviewedPublisher PD

Mackerel egg investigations in the North Sea

This paper deals with the mackerel egg investigations in the North Sea in 1982 and 1983. The egg production is estimated by a computerized method. The confidence limits of the egg samples were estimated at 20-30%. The optimum future distribution of sampling effort in the area is calculated according to Neyman allocation. A comparison of the fecundity of mackerel from different areas measured by different methods is done. The size of the North Sea spawning stock is estimated based on the egg surveys and the fecundity studies

Comparing Test-Driven Development and Pair Programming to Improve the Learning of Programming Languages

This article explores student perceptions of the impact that test-driven development (TDD) and pair programming has on their ability to learn programming. In particular, we examine how test-driven development compares to pair programming in student’s perceptions. The basis of the study is a survey of students who have completed two programming courses that use the C# programming language and use both pair programming and test- driven development techniques to support learning of object-oriented programming. The results indicate that both pair programming and TDD are considered helpful by students but TDD is seen as the more valuable practice