Disease risk prediction with rare and common variants.

Journal Article (Journal Article)

A number of studies have been conducted to investigate the predictive value of common genetic variants for complex diseases. To date, these studies have generally shown that common variants have no appreciable added predictive value over classical risk factors. New sequencing technology has enhanced the ability to identify rare variants that may have larger functional effects than common variants. One would expect rare variants to improve the discrimination power for disease risk by permitting more detailed quantification of genetic risk. Using the Genetic Analysis Workshop 17 simulated data sets for unrelated individuals, we evaluate the predictive value of rare variants by comparing prediction models built using the support vector machine algorithm with or without rare variants. Empirical results suggest that rare variants have appreciable effects on disease risk prediction.

Full Text

Duke Authors

Cited Authors

  • Wu, C; Walsh, KM; Dewan, AT; Hoh, J; Wang, Z

Published Date

  • November 29, 2011

Published In

Volume / Issue

  • 5 Suppl 9 /

Start / End Page

  • S61 -

PubMed ID

  • 22373337

Pubmed Central ID

  • PMC3287900

Electronic International Standard Serial Number (EISSN)

  • 1753-6561

Digital Object Identifier (DOI)

  • 10.1186/1753-6561-5-S9-S61


  • eng

Conference Location

  • England