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Fine-mapping genetic associations.

Accepted version
Peer-reviewed

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Article

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Abstract

Whilst thousands of genetic variants have been associated with human traits, identifying the subset of those variants that are causal requires a further 'fine-mapping' step. We review the basic fine-mapping approach, which is computationally fast and requires only summary data, but depends on an assumption of a single causal variant per associated region which is recognized as biologically unrealistic. We discuss different ways that the approach has been built upon to accommodate multiple causal variants in a region and to incorporate additional layers of functional annotation data. We further review methods for simultaneous fine-mapping of multiple datasets, either exploiting different linkage disequilibrium (LD) structures across ancestries or borrowing information between distinct but related traits. Finally, we look to the future and the opportunities that will be offered by increasingly accurate maps of causal variants for a multitude of human traits.

Description

Keywords

Chromosome Mapping, Disease, Genetic Markers, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci

Journal Title

Hum Mol Genet

Conference Name

Journal ISSN

0964-6906
1460-2083

Volume Title

29

Publisher

Oxford University Press (OUP)

Rights

All rights reserved
Sponsorship
Wellcome Trust (107881/Z/15/Z)
Medical Research Council (MR/R021368/1)
Engineering and Physical Sciences Research Council (EP/R511870/1)
Medical Research Council (MC_UU_00002/4)