ArticleGenome biology and evolution2026
A Recipe for a Good π. How to Properly Estimate Population Genetics Summary Statistics and Why we Should Systematically Report Them.
Article in Genome biology and evolution, 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
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.
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.
Who cites it
2 citing papers in PubMed.
- What has population genomics told us about the dynamics of selection and plant adaptation?Molecular biology and evolution · 2026Review
- Diversity at the HYP1 locus in potato cyst nematodes does not result from developmentally-programmed somatic mutations.PloS one · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Many long-standing questions in population genomics can now be addressed through comparative analyses and by leveraging the vast amount of genomic data being generated. In the context of questioning the utility of producing such a large amount of genomic data, whether for ecological or economic reasons, we argue that data publication should be standardized to ensure long-term reusability. Based on a literature review and key examples, we emphasize that despite the growing volume of available data, the lack of methodological documentation and the absence of metadata make most published polymorphism datasets incomparable, preventing the calculation of meaningful statistics and the application of FAIR (Findable, Accessible, Interoperable, Reusable) principles. We stress that the Variant Calling Format (VCF) as it is used and published today is insufficient, as it does not report the number of monomorphic sites, which are required to compute basic statistics such as pairwise nucleotide diversity (π) or Watterson's θ. We further propose guidelines and best practices to provide sufficient information to allow the proper calculation of these statistics while accounting for sources of bias and misestimation frequently observed in the literature. Finally, we underscore the need for the systematic reporting of standardized statistics, coupled with transparent documentation of data processing steps, to ensure the reproducibility and comparability of population genomic research.
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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.