Aristotle: stratified causal discovery for omics data.

ABSTRACT:

Background

There has been a simultaneous increase in demand and accessibility across genomics, transcriptomics, proteomics and metabolomics data, known as omics data. This has encouraged widespread application of omics data in life sciences, from personalized medicine to the discovery of underlying pathophysiology of diseases. Causal analysis of omics data may provide important insight into the underlying biological mechanisms. Existing causal analysis methods yield promising results when identifying potential general causes of an observed outcome based on omics data. However, they may fail to discover the causes specific to a particular stratum of individuals and missing from others.

Methods

To fill this gap, we introduce the problem of stratified causal discovery and propo

SUBMITTER: Mansouri M 

PROVIDER: S-EPMC8760642 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature