A semi-parametric Bayesian approach for detection of gene expression heterosis with RNA-seq data.

ABSTRACT: Heterosis refers to the superior performance of a hybrid offspring over its two inbred parents. Although heterosis has been widely observed in agriculture, its molecular mechanism is not well studied. Recent advances in high-throughput genomic technologies such as RNA sequencing (RNA-seq) facilitate the investigation of heterosis at the gene expression level. However, it is challenging to identify genes exhibiting heterosis using RNA-seq data because high-dimension of hypotheses tests are conducted with limited sample size. Furthermore, detecting heterosis genes requires testing composite null hypotheses involving multiple mean expression levels instead of testing simple null hypotheses as in differential expression analysis. In this manuscript, we formulate a statistical model with parame

SUBMITTER: Bi R 

PROVIDER: S-EPMC9754042 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature