Generating linkage disequilibrium patterns in data simulations using genomeSIMLA
EvoBIO'08 Proceedings of the 6th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
SNP-Schizo: a web tool for schizophrenia SNP sequence classification
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Supervised logistic principal component analysis for pathway based genome-wide association studies
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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Motivation: Reductions in genotyping costs have heightened interest in performing whole genome association scans and in the fine mapping of candidate regions. Improvements in study design and analytic techniques will require the simulation of datasets with realistic patterns of linkage disequilibrium and allele frequencies for typed SNPs. Methods: We describe a general approach to simulate genotyped datasets for standard case-control or affected child trio data, by resampling from existing phased datasets. The approach allows for considerable flexibility in disease models, potentially involving a large number of interacting loci. The method is most applicable for diseases caused by common variants that have not been under strong selection, a class specifically targeted by the International HapMap project. Results: Using the three population Phase I/II HapMap data as a testbed for our approach, we have implemented the approach in HAP-SAMPLE, a web-based simulation tool. Availability: The web-based tool is available at http://www.hapsample.org Contact:fwright@bios.unc.edu; fzou@bios.unc.edu;kirk@med.unc.edu