ReviewNature reviews. Genetics2015
Methods and models for unravelling human evolutionary history.
Review in Nature reviews. Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
64 citing papers in PubMed, 1 synthesis or guideline pooled it, 190 citations in OpenAlex.
- Population genetic considerations for using biobanks as international resources in the pandemic era and beyond.BMC genomics · 2021Pooled it
- Large-Scale Genomics Reveals Three-Source Ancestry and Layered Adaptation to High Altitude in Tibetan Chickens.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Assessing Ancient DNA Sampling Strategies for Natural Selection Inference in Humans Using Allele Frequency Time Series Data.Genome biology and evolution · 2026Article
- High-quality Population-specific Haplotype-resolved Reference Panel in the Genomic and Pangenomic Eras.Genomics, proteomics & bioinformatics · 2025Review
- Pastrami: a fast and efficient algorithm for fine-scale genetic ancestry inference.NAR genomics and bioinformatics · 2025Article
- Estimation of demography and mutation rates from one million haploid genomes.American journal of human genetics · 2025Article
- The DCIDE framework: systematic investigation of evolutionary hypotheses, exemplified with autism.Biological reviews of the Cambridge Philosophical Society · 2025Review
- clusIBD: Robust Detection of Identity-by-descent Segments Using Unphased Genetic Data from Poor-quality Samples.Genomics, proteomics & bioinformatics · 2025Article
- Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data.Heredity · 2025Article
- Article
- Overview of the Saccharomyces cerevisiae population structure through the lens of 3,034 genomes.G3 (Bethesda, Md.) · 2024Article
- Article
- Human genetic structure in Northwest France provides new insights into West European historical demography.Nature communications · 2024Article
- Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations.The American naturalist · 2023Review
- Haplotype-based inference of recent effective population size in modern and ancient DNA samples.Nature communications · 2023Article
- Rye: genetic ancestry inference at biobank scale.Nucleic acids research · 2023Article
- Population genomics unravels the Holocene history of bread wheat and its relatives.Nature plants · 2023Article
- Olfactory marker protein contains a leucine-rich domain in the Ω-loop important for nuclear export.Molecular brain · 2022Article
- Effects of genetic ancestry and socioeconomic deprivation on ethnic differences in serum creatinine.Gene · 2022Article
- A geometric relationship ofPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genomes of contemporary humans contain considerable information about the history of our species. Although the general contours of human evolutionary history have been defined with increasing resolution throughout the past several decades, the continuing deluge of massively large sequencing data sets presents new opportunities and challenges for understanding human evolutionary history. Here, we review the signatures that demographic history imparts on patterns of DNA sequence variation, statistical methods that have been developed to leverage information contained in genome-scale data sets and insights gleaned from these studies. We also discuss the importance of using exploratory analyses to assess data quality, the strengths and limitations of commonly used population genomics methods, and factors that confound population genomics inferences.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.