MVP
A C++ toolkit for scalable GWAS, structure analysis and publication-ready genomic reporting.
MVP carries forward the core philosophy of rMVP while rebuilding the workflow in C++ for better portability, cleaner engineering and a more practical path from raw genotype input to association results, structure analysis and figures.
The features of MVP
A complete C++ workflow for genotype input, association modeling, population-aware analysis and publication-ready reporting.
By the aid of Memory-mapping and Mixed precision operation technology, MVP can access values from local disk directly, rather than loading all the genotype data into memory at one time, MVP requires less computational resources.
MVP provides comprehensive and high-quality visualization capabilities for genome-wide association studies (GWAS), enabling the rapid generation of key analytical plots, including phenotype distribution plots, SNP marker density maps, Manhattan plots, and quantile–quantile (Q–Q) plots. All visual outputs are optimized to achieve publication-ready quality.
MVP is accelerated by multiple threads computing, including High-performance math library (Intel MKL, Kunpeng[鲲鹏] KML, OpenBLAS, and Apple Accelerate) and OpenMP technic, making MVP super fast to handle big genomic data.