The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Beyond Missing Heritability: Prediction of Complex Traits
Open accessAbstract
Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the "missing heritability" for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h(2) up to 0.83, R(2) up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R(2) values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (∼ 0.80), substantial room for improvement remains.
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Cites
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Polygenic prediction via Bayesian regression and continuous shrinkage priors
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Priors in whole-genome regression: the Bayesian alphabet returns
Gianola, D. (2013) · Genetics · doi:10.1534/genetics.113.151753 · Cited by 457
Relatedness in the post-genomic era: is it still useful?
Speed, D., & Balding, D. J. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3821 · Cited by 316
Kernel-based whole-genome prediction of complex traits: a review
Morota, G., & Gianola, D. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00363 · Cited by 162
Using Genetic Distance to Infer the Accuracy of Genomic Prediction
Scutari, M., Mackay, I., & Balding, D. (2016) · PLOS Genetics · doi:10.1371/journal.pgen.1006288 · Cited by 137
Metadata
- Authors
- Makowsky, R., Pajewski, N. M., Klimentidis, Y. C., Vazquez, A. I., Duarte, C. W., Allison, D. B., & de los Campos, G.
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-04-28
- Volume
- 7
- Issue
- 4
- Pages
- e1002051
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- OpenAlex
- W1992140675
- Cited by
- 254
- References
- 12
- FWCI
- 19.00
- Type
- journal article
- Language
- en
- Open access
- gold
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