Analysis and Optimal Design for Association Studies Using Next-Generation Sequencing With Case-Control Pools
Article first published online: 12 SEP 2012
© 2012 Wiley Periodicals, Inc.
Volume 36, Issue 8, pages 870–881, December 2012
How to Cite
Liang, W. E., Thomas, D. C. and Conti, D. V. (2012), Analysis and Optimal Design for Association Studies Using Next-Generation Sequencing With Case-Control Pools. Genet. Epidemiol., 36: 870–881. doi: 10.1002/gepi.21681
- Issue published online: 14 NOV 2012
- Article first published online: 12 SEP 2012
- Manuscript Accepted: 7 AUG 2012
- Manuscript Revised: 3 AUG 2012
- Manuscript Received: 8 MAR 2012
- National Institutes of Health (NIH). Grant Numbers: R01CA140561, P50HG002790
- NIH/National Institute of Environmental Health Sciences (NIEHS). Grant Number: R01ES019876
- NIEHS. Grant Number: P30ES007048
- National Heart, Lung, and Blood Institute (NHLBI). Grant Number: R01HL087680
- NIH/National Cancer Institute (NCI). Grant Number: R01CA143237
- National Institute of Mental Health. Grant Number: R01MH084678
Disclaimer: Supplementary materials have been peer-reviewed but not copyedited.
Supplemental Figure 1. The discovery probability of a novel variant (VAF = 0.01) using pooling designs, with a fixed sequencing cost. The sequencing cost is the same as that of sequencing 200 individuals with 4× coverage, which provides a maximum discovery probability possible at 0.866.
Supplement Figure 2. Comparison in variant detection probability of optimal pooling designs with various cost function, vs. individual designs, over a range of variant allele frequencies. The cost function is the same as in Figure 7.
Supplemental Text 1. The WinBUGS code for the hierarchical model on the pooled NGS data.
Supplemental Table 1. Top 5 optimal pooling designs for a study interested in a variant with VAF = 0.03 and OR = 2, with a specified cost function and fixed constraints on sequencing cost and sample size
Supplemental Table 2. Comparison in variant detection probability of optimal pooling designs with various cost function, vs. individual designs, over a range of variant allele frequencies. The cost function is the same as in Figure 7.
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