Finite mixtures of matrix variate Poisson-log normal distributions for three-way count data.

ABSTRACT:

Motivation

Three-way data structures, characterized by three entities, the units, the variables and the occasions, are frequent in biological studies. In RNA sequencing, three-way data structures are obtained when high-throughput transcriptome sequencing data are collected for n genes across p conditions at r occasions. Matrix variate distributions offer a natural way to model three-way data and mixtures of matrix variate distributions can be used to cluster three-way data. Clustering of gene expression data is carried out as means of discovering gene co-expression networks.

Results

In this work, a mixture of matrix variate Poisson-log normal distributions is proposed for clustering read counts from RNA sequencing. By considering the matrix variate structure, full informatio

SUBMITTER: Silva A 

PROVIDER: S-EPMC10159656 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature