Manetti, M.; Hiet, S.; Rahmouni, M.; Spadoni, J.-L.; Dobiecki, A.; Lamanda, M.; Tison, M.; Labib, T.; Giuliani, C.; Le Clerc, S.; Zagury, J.-F.

MotivationHaplotype blocks in the genome are informative of evolutionary processes and they play a pivotal role in describing the genomic variability across human populations and susceptibility/resistance to diseases. Several software have been developed for haplotype blocks detection, but they do not distinguish between the impacts of major and minor SNP alleles. In this study, we present a powerful haploblock detection software, specifically designed for identifying haploblocks associated with SNP minor allele haploblocks (MiA-haploblocks). These haploblocks are particularly important as they can significantly influence phenotypic traits, offering a novel approach for studying genetic associations and complex traits.\n\nResultsHaploExplore operates on VCF files containing phased data, exhibiting rapid processing times and generating user-friendly outputs. Its results are convergent for populations starting from 100 individuals. A comparative analysis of HaploExplore against other haploblock detection software revealed its superiority in terms of either simplicity, or flexibility, or speed, with the unique capability to target minor alleles. HaploExplore will be very useful for evolutionary genomics and for GWAS analysis in human diseases, given that the effects of genetic associations may accumulate within a specific haploblock.