yQTL Pipeline

yQTL Pipeline facilitates and automates large-scale quantitative trait loci (QTL) discovery and downstream visualization through a structured computational workflow.

Key Features:

• Flexible Input Support: The pipeline supports calculation or direct input of pre-defined genome-wide principal components, genetic relationship matrix, and user-specified covariates.
• Statistical Model Selection: Genome-wide association tests use either a linear mixed-effect model or a linear model depending on whether familial relatedness exists among subjects.
• Workflow Parallelization: Nextflow parallelizes analysis steps to optimize run-time and ensure results reproducibility.
• Result Visualization: An R Shiny App generates Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds.

Scientific Applications:

• Metabolomics QTL (mQTL) Analysis: The pipeline was applied to analyze metabolomics profiles of blood serum from New England Centenarians Study (NECS) participants, analyzing 9.1M SNPs and 1,052 metabolites across 194 participants.
• Multi-metabolite Association Discovery: Using a p-value cutoff of 5e-8, analysis revealed 14,983 mQTLs cumulatively associated with 312 metabolites, including multiple mQTLs shared across multiple metabolites.

Methodology:

The pipeline performs genome-wide association tests using either a linear mixed-effect model or a linear model, with optional inclusion of genome-wide principal components, genetic relationship matrix, and user-specified covariates prior to association testing. Analysis steps are parallelized using Nextflow.