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Microarrays 2013, 2(3), 265-283; doi:10.3390/microarrays2030265

Kernel-Based Aggregation of Marker-Level Genetic Association Tests Involving Copy-Number Variation

1
Department of Statistics, University of Kentucky, 311 MDS, 725 Rose Street, Lexington, KY 40536, USA
2
Department of Biostatistics, University of Iowa, N336 CPHB, 105 River Street, Iowa City, IA 52242, USA
*
Author to whom correspondence should be addressed.
Received: 2 August 2013 / Revised: 29 August 2013 / Accepted: 30 August 2013 / Published: 4 September 2013
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Abstract

Genetic association tests involving copy-number variants (CNVs) are complicated by the fact that CNVs span multiple markers at which measurements are taken. The power of an association test at a single marker is typically low, and it is desirable to pool information across the markers spanned by the CNV. However, CNV boundaries are not known in advance, and the best way to proceed with this pooling is unclear. In this article, we propose a kernel-based method for aggregation of marker-level tests and explore several aspects of its implementation. In addition, we explore some of the theoretical aspects of marker-level test aggregation, proposing a permutation-based approach that preserves the family-wise error rate of the testing procedure, while demonstrating that several simpler alternatives fail to do so. The empirical power of the approach is studied in a number of simulations constructed from real data involving a pharmacogenomic study of gemcitabine and compares favorably with several competing approaches. View Full-Text
Keywords: CNV association study; multiple testing; family-wise error rate; kernel methods CNV association study; multiple testing; family-wise error rate; kernel methods
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Li, Y.; Breheny, P. Kernel-Based Aggregation of Marker-Level Genetic Association Tests Involving Copy-Number Variation. Microarrays 2013, 2, 265-283.

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