lodGWAS

lodGWAS implements parametric survival analysis within genome-wide association studies (GWAS) to incorporate limit of detection (LOD)-censored biomarker measurements into genetic association testing.

Key Features:

• Parametric survival analysis: Applies parametric survival models to treat observations below the LOD as censored data within GWAS.
• GWAS integration: Integrates censored-data handling directly into genome-wide association testing of biomarker traits.
• R implementation: Implemented in R to perform the statistical analyses and integrate with GWAS workflows.
• Biomarker support: Accommodates various biomarker assay data types that produce measurements constrained by a limit of detection.

Scientific Applications:

• Biomarker association studies: Enables genetic association analyses of biomarkers subject to LOD constraints without discarding censored observations.
• Oncology: Applicable to biomarker GWAS in cancer research where assay measurements may fall below detection limits.
• Pharmacogenomics: Supports association testing of drug-response biomarkers that are constrained by assay LODs.
• Personalized medicine: Facilitates discovery of genetic determinants of clinically relevant biomarkers that may be LOD-censored.

Methodology:

Integrates parametric survival analysis into the GWAS framework to statistically handle LOD-censored biomarker observations without discarding them.