TY - JOUR
T1 - From genome-wide associations to candidate causal variants by statistical fine-mapping
AU - Schaid, Daniel J.
AU - Chen, Wenan
AU - Larson, Nicholas B.
N1 - Publisher Copyright:
© 2018 Macmillan Publishers Ltd., part of Springer Nature.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - 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.
AB - 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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U2 - 10.1038/s41576-018-0016-z
DO - 10.1038/s41576-018-0016-z
M3 - Review article
C2 - 29844615
AN - SCOPUS:85047832663
SN - 1471-0056
VL - 19
SP - 491
EP - 504
JO - Nature Reviews Genetics
JF - Nature Reviews Genetics
IS - 8
ER -