An ancestry-based approach for detecting interactions.
Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
The Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.
Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA.
Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
Department of Genetics, Stanford University, Palo Alto, CA, USA.
Institute of Human Genetics, University of California San Francisco, San Francisco, CA, USA.
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
- Published Article
Wiley (John Wiley & Sons)
- Publication Date
Nov 08, 2017
We show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.
Report this publication
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
This record was last updated on 06/09/2018 and may not reflect the most current and accurate biomedical/scientific data available from NLM.
The corresponding record at NLM can be accessed at https://www.ncbi.nlm.nih.gov/pubmed/29114909