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

Authors:
Publisher website
Google Scholar
Abstract
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. 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. timeOmics is available on Bioconductor and github.com/abodein/timeOmics. Supplementary data are available at Bioinformatics online.
Funding Information
  • Research and Innovation chair L’Oréal in Digital Biology
  • National Health and Medical Research Council (NHMRC) Career Development Fellowship (GNT1159458)

This publication has 9 references indexed in Scilit: