Utilizing Graph Theory to Select the Largest Set of Unrelated Individuals for Genetic Analysis
Version of Record online: 19 SEP 2012
© 2012 WILEY PERIODICALS, INC.
Volume 37, Issue 2, pages 136–141, February 2013
How to Cite
Staples, J., Nickerson, D. A. and Below, J. E. (2013), Utilizing Graph Theory to Select the Largest Set of Unrelated Individuals for Genetic Analysis. Genet. Epidemiol., 37: 136–141. doi: 10.1002/gepi.21684
- Issue online: 10 JAN 2013
- Version of Record online: 19 SEP 2012
- Manuscript Accepted: 17 AUG 2012
- Manuscript Revised: 10 AUG 2012
- Manuscript Received: 8 JUN 2012
- NHGRI. Grant Number: T32 HG00035
- NHLBI. Grant Number: HL102926
- NHGRI. Grant Number: HG006493
Disclaimer: Supplementary materials have been peer-reviewed but not copyedited.
Table S1. Comparison of PRIMUS and other methods on publicly available datasets. Table contains the total number of samples (including related individuals) for each cohort and the sizes of the unrelated sets produced by each method. The HapMap 3 cohort is also separated by population. IBD estimates were generated in PLINK and a pair of individuals was determined to be related if the coefficient of relatedness > = 0.1. In datasets with limited relatedness like the HapMap, all the approaches work well
Figure S1. Heatmaps comparing PRIMUS and three other methods on simulated data.
Figure S2. Heatmaps comparing PRIMUS and three other methods on simulation data when using the binary weighting functions.
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