OTTERS

OTTERS performs transcriptome-wide association studies (TWAS) using summary-level expression quantitative trait loci (eQTL) reference data to estimate eQTL weights and conduct omnibus tests across genes and transcripts to identify associations between genetic variants and gene expression.

Key Features:

• Summary-level eQTL integration: Leverages summary-level eQTL reference data to enable TWAS without requiring individual-level expression measurements.
• eQTL weight estimation via PRS methods: Adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level datasets.
• Omnibus TWAS testing: Conducts omnibus tests that simultaneously evaluate multiple genes or transcripts for association with genetic variation.
• Compatibility with large-scale association data: Integrates summary-level genetic association data to capitalize on increased reference sample sizes.
• Evaluation in silico and empirical: Performance has been assessed through simulation studies and real-world application scenarios.

Scientific Applications:

• Transcriptome-wide association studies (TWAS): Identifying gene- or transcript-level associations with complex trait–linked genetic variation using summary eQTL references.
• eQTL weight recovery: Estimating genetic effect sizes on gene expression (eQTL weights) from summary statistics when individual-level expression data are unavailable.
• Genetic regulation discovery: Mapping genetic contributions to gene expression variability and associated phenotypic traits.
• Large-cohort integrative analyses: Applying TWAS frameworks to large-scale GWAS summary statistics by leveraging summary eQTL reference datasets.

Methodology:

Adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and applies those weights in omnibus TWAS tests using summary-level genetic association data.