An efficient concordant integrative analysis of multiple large-scale two-sample expression data sets.

ABSTRACT:

Motivation

We have proposed a mixture model based approach to the concordant integrative analysis of multiple large-scale two-sample expression datasets. Since the mixture model is based on the transformed differential expression test P-values (z-scores), it is generally applicable to the expression data generated by either microarray or RNA-seq platforms. The mixture model is simple with three normal distribution components for each dataset to represent down-regulation, up-regulation and no differential expression. However, when the number of datasets increases, the model parameter space increases exponentially due to the component combination from different datasets.

Results

In this study, motivated by the well-known generalized estimating equations (GEEs) for longitudinal

SUBMITTER: Lai Y 

PROVIDER: S-EPMC5860313 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature