Sufficient direction factor model and its application to gene expression quantitative trait loci discovery.

ABSTRACT: Rapid improvement in technology has made it relatively cheap to collect genetic data, however statistical analysis of existing data is still much cheaper. Thus, secondary analysis of single-nucleotide polymorphism, SNP, data, i.e., reanalysing existing data in an effort to extract more information, is an attractive and cost-effective alternative to collecting new data. We study the relationship between gene expression and SNPs through a combination of factor analysis and dimension reduction estimation. To take advantage of the flexibility in traditional factor models where the latent factors are not required to be normal, we recommend using semiparametric sufficient dimension reduction methods in the joint estimation of the combined model. The resulting estimator is flexible and has superi

SUBMITTER: Jiang F 

PROVIDER: S-EPMC6508038 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature