Design and statistical analysis of pooled next generation sequencing for rare variants

Tao Wang, Chang Yun Lin, Yuanhao Zhang, Ruofeng Wen, Kenny Ye

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Next generation sequencing (NGS) is a revolutionary technology for biomedical research. One highly cost-efficient application of NGS is to detect disease association based on pooled DNA samples. However, several key issues need to be addressed for pooled NGS. One of them is the high sequencing error rate and its high variability across genomic positions and experiment runs, which, if not well considered in the experimental design and analysis, could lead to either inflated false positive rates or loss in statistical power. Another important issue is how to test association of a group of rare variants. To address the first issue, we proposed a new blocked pooling design in which multiple pools of DNA samples from cases and controls are sequenced together on same NGS functional units. To address the second issue, we proposed a testing procedure that does not require individual genotypes but by taking advantage of multiple DNA pools. Through a simulation study, we demonstrated that our approach provides a good control of the type I error rate, and yields satisfactory power compared to the test-based on individual genotypes. Our results also provide guidelines for designing an efficient pooled.

Original languageEnglish (US)
Article number524724
JournalJournal of Probability and Statistics
DOIs
StatePublished - 2012

ASJC Scopus subject areas

  • Statistics and Probability

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