Evidence map›Paper›PMID 39611246›Full record

ArticleMolecular ecology resources2025

A Pipeline and Recommendations for Population and Individual Diagnostic SNP Selection in Non-Model Species.

Ellie E Armstrong, Chenyang Li, Michael G Campana, Tessa Ferrari, Joanna L Kelley, Dmitri A Petrov, Katherine A Solari, Jazlyn A Mooney

Abstract read
In one paragraph

Article in Molecular ecology resources, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ellie E ArmstrongSchool of Biological Sciences, Washington State University, Pullman, Washington, USA.ORCID https://orcid.org/0000-0001-7107-6318
Chenyang LiDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0009-0008-2093-9804
Michael G CampanaSmithsonian's National Zoo and Conservation Biology Institute, Washington, DC, USA.ORCID https://orcid.org/0000-0003-0461-6462
Tessa FerrariDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0009-0009-7692-4465
Joanna L KelleyDepartment of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, California, USA.ORCID https://orcid.org/0000-0002-7731-605X
Dmitri A PetrovDepartment of Biology, Stanford University, Stanford, California, USA.ORCID https://orcid.org/0000-0002-3664-9130
Katherine A SolariDepartment of Biology, Stanford University, Stanford, California, USA.ORCID https://orcid.org/0000-0001-7029-6554
Jazlyn A MooneyDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-2369-0855

Funding

Genomics of rapid adaptation in the lab and in the wildR35GM118165 · NIGMS · STANFORD UNIVERSITY · PI Dmitri Petrov · 2016 to 2026
$8.3M
NIGMS NIH HHS R35 GM118165
6 · The paper itself

Abstract

Despite substantial reductions in the cost of sequencing over the last decade, genetic panels remain relevant due to their cost-effectiveness and flexibility across a variety of sample types. In particular, single nucleotide polymorphism (SNP) panels are increasingly favoured for conservation applications. SNP panels are often used because of their adaptability, effectiveness with low-quality samples, and cost-efficiency for population monitoring and forensics. However, the selection of diagnostic SNPs for population assignment and individual identification can be challenging. The consequences of poor SNP selection are under-powered panels, inaccurate results, and monetary loss. Here, we develop a novel and user-friendly SNP selection pipeline (mPCRselect) that can be used to select SNPs for population assignment and/or individual identification. mPCRselect allows any researcher, who has sufficient SNP-level data, to design a successful and cost-effective SNP panel for a diploid species of conservation concern.

Indexed as

Computational BiologyGenetics, PopulationGenotyping TechniquesPolymorphism, Single Nucleotideconservation geneticsindividual IDmarker selectionpopulation assignmentSNP panel

Identifiers

PMID39611246
PMCPMC11887608

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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.