ArticlePLoS genetics2020
Learning the properties of adaptive regions with functional data analysis.
Article in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 27 citations in OpenAlex.
- Soft Selective Sweeps Predominate in the Yellow Fever Mosquito Aedes aegypti.Molecular biology and evolution · 2026Article
- Detecting Positive Selection by Modeling Structure Within Images of Genetic Variation.Genome biology and evolution · 2026Article
- Identifying Adaptive Footprints in the Presence of Demographic Uncertainty.Genome biology and evolution · 2026Article
- Signatures of soft selective sweeps predominate in the yellow fever mosquitobioRxiv : the preprint server for biology · 2025Article
- Article
- Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning.Molecular biology and evolution · 2025Article
- Efficient detection and characterization of targets of natural selection using transfer learning.bioRxiv : the preprint server for biology · 2025Article
- Digital Image Processing to Detect Adaptive Evolution.Molecular biology and evolution · 2024Article
- Population Genomic Scans for Natural Selection and Demography.Annual review of genetics · 2024Review
- Tree Sequences as a General-Purpose Tool for Population Genetic Inference.Molecular biology and evolution · 2024Article
- Tree sequences as a general-purpose tool for population genetic inference.bioRxiv : the preprint server for biology · 2024Article
- Assessing the Presence of Recent Adaptation in the Human Genome With Mixture Density Regression.Genome biology and evolution · 2023Article
- Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data.Molecular biology and evolution · 2023Article
- Uncovering Footprints of Natural Selection Through Spectral Analysis of Genomic Summary Statistics.Molecular biology and evolution · 2023Article
- Genome-wide scans for selective sweeps using convolutional neural networks.Bioinformatics (Oxford, England) · 2023Article
- Versatile Detection of Diverse Selective Sweeps with Flex-Sweep.Molecular biology and evolution · 2023Article
- A spatially aware likelihood test to detect sweeps from haplotype distributions.PLoS genetics · 2022Article
- Learning Retention Mechanisms and Evolutionary Parameters of Duplicate Genes from Their Expression Data.Molecular biology and evolution · 2021Article
- Review
- A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data.Molecular biology and evolution · 2020Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.
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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.