timeOmics: an R package for longitudinal multi-omics data integration

Abstract

Motivation: Multi-omics data integration enables the global analysis of biological systems and discovery of new biological insights. Multi-omics experimental designs have been further extended with a longitudinal dimension to study dynamic relationships between molecules. However, methods that integrate longitudinal multi-omics data are still in their infancy.

Results: We introduce the R package timeOmics, a generic analytical framework for the integration of longitudinal multi-omics data. The framework includes pre-processing, modeling and clustering to identify molecular features strongly associated with time. We illustrate this framework in a case study to detect seasonal patterns of mRNA, metabolites, gut taxa and clinical variables in patients with diabetes mellitus from the integrative Human Microbiome Project.

Availabilityand implementation: timeOmics is available on Bioconductor and github.com/abodein/timeOmics.

Supplementary information: Supplementary data are available at Bioinformatics online.