A comparison of methods for inferring causal relationships between genotype and phenotype using additional biological measurements.

ABSTRACT: Genome wide association studies (GWAS) have been very successful over the last decade at identifying genetic variants associated with disease phenotypes. However, interpretation of the results obtained can be challenging. Incorporation of further relevant biological measurements (e.g. 'omics' data) measured in the same individuals for whom we have genotype and phenotype data may help us to learn more about the mechanism and pathways through which causal genetic variants affect disease. We review various methods for causal inference that can be used for assessing the relationships between genetic variables, other biological measures, and phenotypic outcome, and present a simulation study assessing the performance of the methods under different conditions. In general, the methods we consider

SUBMITTER: Ainsworth HF 

PROVIDER: S-EPMC5655748 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature