Journal
PLOS ONE
Volume 9, Issue 1, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0085728
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Funding
- National Science Council of Taiwan [NSC 102-2628-B-002-039-MY3, NSC 102-2314-B-002-001-MY2]
- National Taiwan University [NTU-CESRP-101R7622-8, NTU-CESRP-102R7622-8, NTU-CDP-102R7769]
- NIH [R01GM081488, R01HL092173, P01AR049084, P60AR048095, R01DA095025, R01GM073766]
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With the development of next-generation sequencing technology, there is a great demand for powerful statistical methods to detect rare variants (minor allele frequencies (MAFs), 1%) associated with diseases. Testing for each variant site individually is known to be underpowered, and therefore many methods have been proposed to test for the association of a group of variants with phenotypes, by pooling signals of the variants in a chromosomal region. However, this pooling strategy inevitably leads to the inclusion of a large proportion of neutral variants, which may compromise the power of association tests. To address this issue, we extend the sigma-MidP method (Cheung et al., 2012, Genet Epidemiol 36:675-685) and propose an approach (named 'adaptive combination of P-values for rare variant association testing', abbreviated as 'ADA') that adaptively combines per-site P-values with the weights based on MAFs. Before combining P-values, we first imposed a truncation threshold upon the per-site P-values, to guard against the noise caused by the inclusion of neutral variants. This ADA method is shown to outperform popular burden tests and non-burden tests under many scenarios. ADA is recommended for next-generation sequencing data analysis where many neutral variants may be included in a functional region.
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