Fault-tolerant pedigree reconstruction from pairwise kinship relations

Area of Science:

• Ancient DNA Analysis
• Computational Biology
• Population Genetics

Background:

• Manual reconstruction of ancient pedigrees is labor-intensive and limited by DNA data quality.
• Existing computational methods are not optimized for the challenges of ancient DNA.

Purpose of the Study:

• To introduce repare, an automated software for reconstructing pedigrees from ancient genomes.
• To provide a flexible and accurate tool for analyzing ancient kinship and population structures.

Main Methods:

• Developed an open-source software, repare, that reconstructs pedigrees from inferred pairwise kinship relations.
• Employs iterative incorporation of kinship data, pruning, and sampling to manage complexity.
• Optionally integrates supporting data like haplogroups and age-at-death estimates.

Main Results:

• Successfully reconstructed simulated pedigrees with varying error rates and missing data.
• Reconstructed several previously manually-derived pedigrees, identifying a potential alternative topology for one.
• Demonstrated repare's power and flexibility, especially with user-inferred constraints.

Conclusions:

• Repare offers a significant advancement in automated ancient pedigree reconstruction.
• The software enhances the analysis of ancient genomes for historical and genetic insights.
• Repare is available as an open-source tool to the research community.