IntLIM 2.0: identifying multi-omic relationships dependent on discrete or continuous phenotypic measurements

Tara Eicher, Kyle Spencer, Siddiqui Jalal, Raghu Machiraju, Ewy Mathe

Abstract:

Motivation: IntLIM uncovers phenotype-dependent linear associations between two types of analytes (e.g. genes
and metabolites) in a multi-omic dataset, which may reflect chemically or biologically relevant relationships.
Results: The new IntLIM R package includes newly added support for generalized data types, covariate correction,
continuous phenotypic measurements, model validation and unit testing. IntLIM analysis uncovered biologically
relevant gene–metabolite associations in two separate datasets, and the run time is improved over baseline R functions by multiple orders of magnitude.