AnchorFCI: harnessing genetic anchors for enhanced causal discovery of cardiometabolic disease pathways.

ABSTRACT:

Introduction

Cardiometabolic diseases, a major global health concern, stem from complex interactions of lifestyle, genetics, and biochemical markers. While extensive research has revealed strong associations between various risk factors and these diseases, latent confounding and limited causal discovery methods hinder understanding of their causal relationships, essential for mechanistic insights and developing effective prevention and intervention strategies.

Methods

We introduce anchorFCI, a novel adaptation of the conservative Really Fast Causal Inference (RFCI) algorithm, designed to enhance robustness and discovery power in causal learning by strategically selecting and integrating reliable anchor variables from a set of variables known not to be caused by the variables

SUBMITTER: Ribeiro AH 

PROVIDER: S-EPMC11663939 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature