ArticleeLife2017
Minimal-assumption inference from population-genomic data.
Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Isolation by distance in populations with power-law dispersal.G3 (Bethesda, Md.) · 2023Article
- Article
- Inference of Historical Population-Size Changes with Allele-Frequency Data.G3 (Bethesda, Md.) · 2020Article
- A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data.Ecology and evolution · 2020Review
- Article
- Coalescence times for three genes provide sufficient information to distinguish population structure from population size changes.Journal of mathematical biology · 2019Article
- Article
- ABLE: blockwise site frequency spectra for inferring complex population histories and recombination.Genome biology · 2018Article
- Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories.G3 (Bethesda, Md.) · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of coalescence or recombination, allowing it to analyze arbitrarily large samples without phasing while making no assumptions about ancestral structure, linked selection, or gene conversion. Using simulated data, we show that the performance of MAGIC is comparable to that of PSMC' even on single diploid samples generated with standard coalescent and recombination models. Applying MAGIC to a sample of human genomes reveals evidence of non-demographic factors driving coalescence.
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Registered trials
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