Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes

By Jerome Kelleher, A. Etheridge, G. McVean. bioRxiv, 2015

638 citations recorded by the source corpus.

A central challenge in the analysis of genetic variation is to provide realistic genome simulation across millions of samples. Present day coalescent simulations do not scale well, or use approximations that fail to capture important long-range linkage properties. Analysing the results of simulations also presents a substantial challenge, as current methods to store genealogies consume a great deal of space, are slow to parse and do not take advantage of shared structure in correlated trees. We solve these problems by introducing sparse trees and coalescence records as the key units of genealogical analysis. Using these tools, exact simulation of the coalescent with recombination for chromosome-sized regions over hundreds of thousands of samples is possible, and substantially faster than present-day approximate methods. We can also analyse the results orders of magnitude more quickly than with existing methods.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/225b33b7a54278ce1c62d8d3fd11cd5ddce1c704

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Citations in the corpus

Efficient ancestry and mutation simulation with msprime 1.0 (2021, methodology): “In human-like parameter regimes and for large sample sizes, msprime ’s implementation of the exact coalescent with recombination comprehensively outperforms all other simulators, including those based on SMC approximations (Kelleher et al. 2016).”
Adaptive Sampling Strategies to Construct Equitable Training Datasets (2022, methodology): “might be applied in this setting, we use a simulation framework developed by domain experts [17, 38] to first generate a synthetic population of people with different ancestries, and then train PRS models under various sampling strategies.”
Spatial Population Genetics: It's About Time (2019, positive): “, 2019) and msprime (Kelleher et al., 2016b).”
Dsuite - fast D-statistics and related admixture evidence from VCF files (2020, methodology): “…set of 73 species of Lake Malawi cichlid fishes published in Malinsky et al. (2018); (b) a small simulation data set comprising 20 species and 20 Mb of sequence generated using the msprime (Kelleher et al., 2016) software; (c) a large simulation data set with 100 Mb of sequence and 100 species.”
pixy: Unbiased estimation of nucleotide diversity and divergence in the presence of missing data (2020, methodology): “To provide ground-truthed datasets for evaluating the performance of pixy , we simulated sequence data using the coalescent simulator msprime (Kelleher et al. 2016).”