Abstract
In family studies with multiple continuous phenotypes, heritability can be conveniently evaluated through the so-called principal-component of heredity (PCH, for short; Ott and Rabinowitz in Hum Hered 49:106-111, 1999). Estimation of the PCH, however, is notoriously difficult when entertaining a large collection of phenotypes which naturally arises in dealing with modern genomic data such as those from expression QTL studies. In this paper, we propose a regularized PCH method to specifically address such challenges. We show through both theoretical studies and data examples that the proposed method can accurately assess the heritability of a large collection of phenotypes.
Original language | English (US) |
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Pages (from-to) | 455-465 |
Number of pages | 11 |
Journal | Computational Statistics |
Volume | 29 |
Issue number | 3-4 |
DOIs | |
State | Published - Jun 2014 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Computational Mathematics
Keywords
- Expression quantitative trait loci
- Family study
- High dimensional data
- Linear discriminant analysis
- Principal components
- Sparsity