GMRP

GMRP performs Mendelian randomization analyses using genetic variants as instrumental variables to infer causal effects of exposures (e.g., biomarkers or risk factors) on disease outcomes, analyze multiple single nucleotide polymorphisms (SNPs), construct path analyses, and account for confounding.

Key Features:

• Mendelian Randomization Analysis: Implements Mendelian randomization using genetic variants as instrumental variables to estimate causal effects between exposures and outcomes.
• Multiple SNP Analysis: Handles analysis of multiple single nucleotide polymorphisms (SNPs) concurrently to assess their collective impact on traits or diseases.
• Confounding Variable Exclusion: Applies MR principles to reduce confounding and potential reverse causation in observational genetic association data.
• Path Analysis Construction: Facilitates path analysis to construct pathways linking genetic variants to disease outcomes.
• Bioconductor Interoperability: Operates within the Bioconductor ecosystem and the R programming environment for interoperability with other genomic analysis packages.

Scientific Applications:

• Epidemiological Research: Enables causal inference between genetic markers and diseases in epidemiological studies.
• Genetic Epidemiology: Supports analysis of the genetic architecture of complex traits by elucidating gene-disease associations.
• Public Health Interventions: Identifies causal risk factors that can inform public health prevention strategies.

Methodology:

Uses genetic variants as instrumental variables to perform Mendelian randomization, supports analysis of multiple SNPs and path analysis, and is grounded in statistical genetics principles.