Evidence map›Paper›PMID 41279763›Full record

ArticlebioRxiv : the preprint server for biology2025

Selection scans and downstream analysis with selscan.

Amatur Rahman, T Quinn Smith, Zachary A Szpiech

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Amatur RahmanDepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USA.ORCID 0000-0002-9166-1220
T Quinn SmithDepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USA.ORCID 0009-0004-9955-4915
Zachary A SzpiechDepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USA.ORCID 0000-0001-6372-8224

Funding

Population Genetics Methods for Understanding Complex Trait EvolutionR35GM146926 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI Zachary Alfano Szpiech · 2022 to 2026
$1.8M
NIGMS NIH HHS R35 GM146926
6 · The paper itself

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 they are straightforward to compute, there lacks clear descriptions on how they relate to one another, how they should be used, and how their results should be interpreted. Here, we provide a comprehensive introduction to selection statistics as they are implemented in the widely used software, selscan. 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.

Identifiers

PMID41279763
PMCPMC12632508

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Registered trials

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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.