SMC++

SMC++ estimates historical population size changes and population split times from whole-genome sequence data to infer past demographic events without requiring phased genomes.

Key Features:

• Genealogical inference with recombination: Leverages genealogical processes with recombination to infer demographic history from sequence data.
• Unphased data compatibility: Performs inference on unphased whole-genome sequence data, avoiding phasing switch errors.
• Scalability: Handles substantially larger sample sizes to increase resolution in recent historical periods.
• Joint inference of sizes and splits: Jointly infers population size histories and split times among diverged populations.
• Spline regularization: Employs a spline regularization scheme that reduces estimation error in demographic reconstructions.

Scientific Applications:

• Human population genomics: Applied to sequence data from over a thousand human genomes spanning Africa and Eurasia to infer human demographic history.
• Drosophila population genomics: Applied to hundreds of Drosophila melanogaster genomes from an African population.
• Avian population genomics: Applied to tens of zebra finch and long-tailed finch genomes from Australian populations.
• Cross-species demographic inference: Demonstrated versatility across diverse species' genomic datasets for reconstructing population history.

Methodology:

Performs inference using genealogical processes incorporating recombination on whole-genome sequences, operates on unphased data, jointly estimates population size histories and split times, and applies spline regularization to reduce estimation error while scaling to large sample sizes.