The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
OptM: estimating the optimal number of migration edges on population trees using Treemix
Open accessAbstract
The software Treemix has become extensively used to estimate the number of migration events, or edges (m), on population trees from genome-wide allele frequency data. However, the appropriate number of edges to include remains unclear. Here, I show that an optimal value of m can be inferred from the second-order rate of change in likelihood (Δm) across incremental values of m. Repurposed from its original use to estimate the number of population clusters in the software Structure (ΔK), I show using simulated populations that Δm performs equally as well as current recommendations for Treemix. A demonstration of an empirical dataset from domestic dogs indicates that this method may be preferable in large, complex population histories and can prioritize migration events for subsequent investigation. The method has been implemented in a freely available R package called “OptM” and as a web application (https://rfitak.shinyapps.io/OptM/) to interface directly with the output files of Treemix.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Inference of Population Structure Using Multilocus Genotype Data
Pritchard, J. K., Stephens, M., & Donnelly, P. (2000) · Genetics · doi:10.1093/genetics/155.2.945 · Cited by 33,908
Detecting the number of clusters of individuals using the software structure: a simulation study
EVANNO, G., REGNAUT, S., & GOUDET, J. (2005) · Molecular Ecology · doi:10.1111/j.1365-294x.2005.02553.x · Cited by 21,895
The variant call format and VCFtools
Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr330 · Cited by 16,200
Inference of population splits and mixtures from genome-wide allele frequency data
Pickrell, J. K., & Pritchard, J. K. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002967 · Cited by 2,731
Genome sequencing and population genomics in non-model organisms
Ellegren, H. (2014) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2013.09.008 · Cited by 759
An overview of STRUCTURE: applications, parameter settings, and supporting software
Porras-Hurtado, L., Ruiz, Y., Santos, C., Phillips, C., Carracedo, Á., & Lareu, M. V. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00098 · Cited by 609
Janes, J. K., Miller, J. M., Dupuis, J. R., Malenfant, R. M., Gorrell, J. C., Cullingham, C. I., & Andrew, R. L. (2017) · Molecular Ecology · doi:10.1111/mec.14187 · Cited by 606
Worldwide Patterns of Ancestry, Divergence, and Admixture in Domesticated Cattle
Decker, J. E., McKay, S. D., Rolf, M. M., Kim, J., Molina Alcalá, A., Sonstegard, T. S., Hanotte, O., Götherström, A., Seabury, C. M., Praharani, L., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004254 · Cited by 521
Parker, H. G., Dreger, D. L., Rimbault, M., Davis, B. W., Mullen, A. B., Carpintero-Ramirez, G., & Ostrander, E. A. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.03.079 · Cited by 435
Cited by
Re-evaluating Homoploid Reticulate Evolution in Helianthus Sunflowers
Owens, G. L., Huang, K., Todesco, M., & Rieseberg, L. H. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad013 · Cited by 39
Metadata
- Authors
- Fitak, R. R.
- Venue
- Biology Methods and Protocols
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-01-01
- Volume
- 6
- Issue
- 1
- Pages
- bpab017-bpab017
- ISSN
- 2396-8923 (ISSN-L)
- OpenAlex
- W3199637732
- Cited by
- 396
- References
- 23
- FWCI
- 26.94
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: OptM: estimating the optimal number of migration edges on population trees using Treemix. https://app.cochat.ai/papers/10.1093/biomethods/bpab017
- The paper
- Fitak, R. R. (2021). OptM: estimating the optimal number of migration edges on population trees using Treemix. Biology Methods and Protocols. https://doi.org/10.1093/biomethods/bpab017
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
