OmeSim: a genetics-based nonlinear simulator for in-between-ome and phenotype (original) (raw)

2024, bioRxiv (Cold Spring Harbor Laboratory)

Motivation: Deciphering genetic basis of complex traits via genotype-phenotype association studies is a long-standing theme in genetics. The availability of molecular omics data (such as transcriptome) has enabled researchers to utilize "in-between-omes" in association studies, for instance transcriptome-wide association study. Although many statistical tests and machine learning models integrating omics in genetic mapping are emerging, there is no standard way to simulate phenotype by genotype with the role of in-between-omes incorporated. Moreover, the involvement of in-between-omes usually bring substantial nonlinear architecture (e.g., coexpression network), that may be non-trivial to simulate. As such, rigorous power estimations, a critical step to test novel models, may not be conducted fairly. Results: To address the gap between emerging methods development and the unavailability of adequate simulators, we developed OmeSim, a phenotype simulator incorporating genetics, an in-between-ome (e.g., transcriptome), and their complex relationships including nonlinear architectures. OmeSim outputs detailed causality graphs together with original data, correlations, and associations structures between phenotypic traits and omes terms as comprehensive gold-standard datasets for the verifications of novel tools integrating an inbetween-ome in genotype-phenotype association studies. We expect OmeSim to enable rigorous benchmarking for the future multi-omics integrations.

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