ArticleHuman population genetics and genomics2026
Selection scans and downstream analysis with selscan.
Article in Human population genetics and genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
The trial behind it
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
2 citing papers in PubMed.
- Human Genetic Variation Associates With Infection by Derived Ugandan M. tuberculosis Lineage.The Journal of infectious diseases · 2026Article
- Genome Wide Structural Variants Provide Insights Into Population Structure and Genetic Divergence in Pacific White Shrimp (Evolutionary applications · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
statistics based on Extended Haplotype Homozygosity (EHH) are widely used for inferring positive selection in genomes as a result of their ease of use, computational efficiency, and interpretability. These various summary statistics can be applied to single populations or to pairs of populations, can be used with a genetic recombination map or without, and can be applied to phased or unphased data. Although these statistics are straightforward to compute, there lacks clear descriptions on how they relate to one another, how they should be used, and how their resulting outputs should be interpreted. Here, we provide a comprehensive introduction to selection statistics as they are implemented in the widely used software, selscan. In addition to this detailed guide, we implement enhanced normalization procedures and support for gene-based analyses, enabling users to translate selection signals captured by these statistics into gene-level interpretations using BED annotation files, facilitating biologically meaningful insights. We demonstrate the behavior of such statistics on simulated data and highlight best practices by performing an example downstream analysis on data from the 1000 Genomes Project using new features in selscan v3.0. We hope these guidelines will foster reproducibility in the evolutionary genomics community. Precompiled executables and source code for selscan v3.0 can be found at https://github.com/szpiech/selscan.
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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.