Durbadal Ghosh, Ph.D. candidate Biostatistics, Florida State University, Tallahassee

Genotype-phenotype associations provide crucial insights for disciplines such as biology, agriculture, and medicine. This project introduces BigRiverQTL.jl, a comprehensive Julia package designed to streamline quantitative trait locus (QTL) analysis. It features three main components: preprocessing, genome scans, and visualization. The preprocessing functions convert genomic data into an efficient format, calculate kinship matrices, and prepare data for analysis. For genome scans, BigRiverQTL.jl utilizes BulkLMM.jl for univariate scans and integrates the FlxQTL.jl module for multivariate and longitudinal trait analyses. Additionally, BigRiverQTL includes visualization tools that facilitate the examination of both QTL and eQTL scans. Overall, BigRiverQTL.jl represents a significant computational advancement in high-throughput QTL analysis, making sophisticated statistical tools accessible within the Julia programming environment.