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Calculates per-block haplotype diversity metrics: richness (n_haplotypes), expected heterozygosity (He, Nei 1973 sample-size corrected), Shannon entropy, effective number of alleles (1/\(\sum p_i^2\)), dominant haplotype frequency, and a sweep flag (TRUE when freq_dominant \(\geq\) 0.90). These metrics directly correspond to those used to characterise block diversity and identify selection signatures in Difabachew et al. (2023) and Tong et al. (2024). Phased data contributes two gamete observations per individual, doubling the effective sample size.

Usage

compute_haplotype_diversity(haplotypes, missing_string = ".")

Arguments

haplotypes

Named list from extract_haplotypes.

missing_string

Missing data marker. Default ".".

Value

Data frame with one row per block: block_id, CHR, start_bp, end_bp, n_snps, n_ind, n_haplotypes, He (corrected), Shannon, n_eff_alleles, freq_dominant, sweep_flag, phased.

References

Nei M (1973). Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences 70(12):3321-3323. doi:10.1073/pnas.70.12.3321

Difabachew YF et al. (2023). Genomic prediction with haplotype blocks in wheat. Frontiers in Plant Science 14:1168547. doi:10.3389/fpls.2023.1168547

Tong J et al. (2024). Stacking beneficial haplotypes from the Vavilov wheat collection to accelerate breeding for multiple disease resistance. Theoretical and Applied Genetics 137:274. doi:10.1007/s00122-024-04784-w