MOSTWAS: Multi-Omic TWAS Models and Association Statistics

MOSTWAS models and summary statistics for transcriptome-wide association studies are contained in this dataset. The data includes models trained on TCGA breast cancer and ROS/MAP pre-frontal cortex multi-omic data, simulation results, and TWAS associations for breast cancer survival, Alzheimer's disease, and major depressive disorder. Arjun Bhattacharya from the University of North Carolina at Chapel Hill created this dataset to accompany the 2020 paper.

Use Cases

• Training or validating multi-omic TWAS models based on the provided MOSTWAS_Models.
• Analyzing simulation results for method performance based on the Simulation_Results_MOSTWAS.xlsx file.
• Investigating genetic associations for breast cancer survival based on iCOGs GWAS summary statistics.
• Studying genetic links to Alzheimer's disease risk based on IGAP GWAS summary statistics.
• Exploring genetic associations for major depressive disorder based on PGC and UK Biobank GWAX summary statistics.

Strengths

• Includes models trained on two distinct multi-omic datasets: TCGA breast cancer and ROS/MAP pre-frontal cortex.
• Provides association results for three complex traits: breast cancer survival, Alzheimer's disease, and major depressive disorder.
• Contains full simulation results as outlined in the accompanying 2020 paper.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of North Carolina at Chapel Hill

Collection Method

Models generated using Multi-Omic Strategies for Transcriptome-Wide Association Studies (MOSTWAS).