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

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.

Availability and implementation

IntLIM is available as an R package with a detailed vignette (https://github.com/ncats/IntLIM) and as an R Shiny app (see Supplementary Figs S1-S6) (htt

SUBMITTER: Eicher T 

PROVIDER: S-EPMC10010601 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature