High-resolution genetic mapping with pooled sequencing

BMC Bioinformatics

Proceedings

Matthew D Edwards¹  David K Gifford² 

[1] Computer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 02139, Cambridge, MA, USA;Computer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 02139, Cambridge, MA, USA;Whitehead Institute for Biomedical Research, 02142, Cambridge, MA, USA;Broad Institute of MIT and Harvard, 02142, Cambridge, MA, USA;

关键词: Read Count;    Sequencing Depth;    Hide State;    Dynamic Bayesian Network;    Causal Locus;   

DOI  :  10.1186/1471-2105-13-S6-S8

来源: Springer

【 摘 要 】

BackgroundModern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods.ResultsWe present MULTI POOL, a computational method for genetic mapping in model organism crosses that are analyzed by pooled genotyping. Unlike other methods for the analysis of pooled sequence data, we simultaneously consider information from all linked chromosomal markers when estimating the location of a causal variant. Our use of informative sequencing reads is formulated as a discrete dynamic Bayesian network, which we extend with a continuous approximation that allows for rapid inference without a dependence on the pool size. MULTI POOL generalizes to include biological replicates and case-only or case-control designs for binary and quantitative traits.ConclusionsOur increased information sharing and principled inclusion of relevant error sources improve resolution and accuracy when compared to existing methods, localizing associations to single genes in several cases. MULTI POOL is freely available at http://cgs.csail.mit.edu/multipool/.

【 授权许可】

CC BY   
© Edwards and Gifford; licensee BioMed Central Ltd. 2012