Abstract

Motivation: Pedigree errors frequently occur in livestock populations due to long-term manual record-keeping, which reduces the efficiency of breeding programs. Although several pedigree correction methods exist, their practical application is often limited by complicated procedures, high computational cost, and insufficient accuracy. Therefore, an effective and efficient solution for pedigree error correction is needed. Results: We developed a new algorithm and software, PEC, to accurately and efficiently correct pedigree errors. The method matches haplotype fragments between candidate parents and offspring using estimated linkage disequilibrium patterns and subsequently checks for Mendelian conflicts to adjust the pedigree. Using simulated pig datasets, we compared PEC against SeekParentF90 and AlphaAssign in terms of accuracy, memory usage, and computation time. PEC demonstrated superior performance across all metrics. Furthermore, application of single-step genomic best linear unbiased prediction (ssGBLUP) in a real pig population showed that PEC corrected pedigrees significantly improved the accuracy and unbiasedness of genomic evaluations, highlighting the importance of pedigree error correction. Availability: The PEC software is freely available at https://github.com/TXiang-lab/JPEC.