SPEARS: Standard Performance Evaluation of Ancestral Reconstruction through Simulation

Motivation Ancestral haplotype maps provide useful information about genomic variation and biological processes. Reconstructing the descendent haplotype structure of homologous chromosomes, particularly for large numbers of individuals, can help with characterizing the recombination landscape, elucidating genotype-to-phenotype relationships, improving genomic predictions and more. Inferring haplotype maps from sparse genotype data is an efficient approach to whole-genome haplotyping, but this is a non-trivial problem. A standardized approach is needed to validate whether haplotype reconstruction software, conceived population designs and existing data for a given population provides accurate haplotype information for further inference. Results We introduce SPEARS, a pipeline for whole simulation-based appraisal of genome-wide ancestral haplotype inference. The pipeline generates virtual genotypes (truth data) with real-world missing data structure. It then proceeds to mimic analysis in practice, capturing sources of error due to imputation and reconstruction of ancestral haplotypes. Standard metrics allow researchers to assess which features of haplotype structure or regions of the genome are sufficiently accurate for analysis and reporting. Haplotype maps for 1,000 outcross progeny from a multi-parent population of maize is used to demonstrate SPEARS. Availability https://github.com/maizeatlas/spears