A comparison of genomic profiles of complex diseases under different models.

ABSTRACT:

Background

Various approaches are being used to predict individual risk to polygenic diseases from data provided by genome-wide association studies. As there are substantial differences between the diseases investigated, the data sets used and the way they are tested, it is difficult to assess which models are more suitable for this task.

Results

We compared different approaches for seven complex diseases provided by the Wellcome Trust Case Control Consortium (WTCCC) under a within-study validation approach. Risk models were inferred using a variety of learning machines and assumptions about the underlying genetic model, including a haplotype-based approach with different haplotype lengths and different thresholds in association levels to choose loci as part of the predictiv

SUBMITTER: Potenciano V 

PROVIDER: S-EPMC4717655 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature