From genome-wide associations to candidate causal variants by statistical fine-mapping.

Nature Reviews. Genetics
Daniel J SchaidNicholas B Larson

Abstract

Advancing from statistical associations of complex traits with genetic markers to understanding the functional genetic variants that influence traits is often a complex process. Fine-mapping can select and prioritize genetic variants for further study, yet the multitude of analytical strategies and study designs makes it challenging to choose an optimal approach. We review the strengths and weaknesses of different fine-mapping approaches, emphasizing the main factors that affect performance. Topics include interpreting results from genome-wide association studies (GWAS), the role of linkage disequilibrium, statistical fine-mapping approaches, trans-ethnic studies, genomic annotation and data integration, and other analysis and design issues.

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Methods Mentioned

BETA
genotyping

Software Mentioned

PAINTOR
LocusZoom
Haploview
METASOFT
PIP 45 BVS
HyperLasso
BIMBAM
CADD
CAVIAR
SNPTEST

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