The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
G eneland: a computer package for landscape genetics
Abstract
Geneland is a computer package that allows to make use of georeferenced individual multilocus genotypes for the inference of the number of populations and of the spatial location of genetic discontinuities between those populations. Main assumptions of the method are: (i) the number of populations is unknown and all values are considered a priori equally likely, (ii) populations are spread over areas given by a union of some polygons of unknown location in the spatial domain, (iii) Hardy–Weinberg equilibrium is assumed within each population and (iv) allele frequencies in each population are unknown and treated as random variable either following the so‐called Dirichlet model or Falush model. Different algorithms implemented in Geneland to perform inferences are first briefly presented. Then major running steps and outputs (i.e. histogram of number of populations and map of posterior probabilities of population membership) are illustrated from the analysis of a simulated data set, which was also produced by Geneland.
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
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
R: A Language for Data Analysis and Graphics
Ihaka, R., & Gentleman, R. (1996) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1996.10474713 · Cited by 11,220
Falush, D., Stephens, M., & Pritchard, J. K. (2003) · Genetics · doi:10.1093/genetics/164.4.1567 · Cited by 7,959
Markov Chain Monte Carlo in Practice
(1995) · Chapman & Hall/CRC eBooks · doi:10.1201/b14835 · Cited by 7,757
ROGERS, S. M., & BERNATCHEZ, L. (2005) · Molecular Ecology · doi:10.1111/j.1365-294x.2004.02396.x · Cited by 5,088
Landscape genetics: combining landscape ecology and population genetics
Manel, S., Schwartz, M. K., Luikart, G., & Taberlet, P. (2003) · Trends in Ecology & Evolution · doi:10.1016/s0169-5347(03)00008-9 · Cited by 1,859
(2000) · CrossRef Listing of Deleted DOIs · doi:10.1007/978-1-4899-4485-6 · Cited by 1,151
Why environmental scientists are becoming Bayesians
Clark, J. S. (2005) · Ecology Letters · doi:10.1111/j.1461-0248.2004.00702.x · Cited by 862
A Spatial Statistical Model for Landscape Genetics
Guillot, G., Estoup, A., Mortier, F., & Cosson, J. F. (2005) · Genetics · doi:10.1534/genetics.104.033803 · Cited by 692
Self-citation
Cited by
How to fail at species delimitation
Carstens, B. C., Pelletier, T. A., Reid, N. M., & Satler, J. D. (2013) · Molecular Ecology · doi:10.1111/mec.12413 · Cited by 1,248
Harnessing genomics for delineating conservation units
Funk, W. C., McKay, J. K., Hohenlohe, P. A., & Allendorf, F. W. (2012) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2012.05.012 · Cited by 1,117
Puechmaille, S. J. (2016) · Molecular Ecology Resources · doi:10.1111/1755-0998.12512 · Cited by 1,010
Putting the ‘landscape’ in landscape genetics
Storfer, A., Murphy, M. A., Evans, J. S., Goldberg, C. S., Robinson, S., Spear, S. F., Dezzani, R., Delmelle, E., Vierling, L., & Waits, L. P. (2007) · Heredity · doi:10.1038/sj.hdy.6800917 · Cited by 938
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Corander, J., Marttinen, P., Sirén, J., & Tang, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-539 · Cited by 874
Metadata
- Authors
- GUILLOT, G., MORTIER, F., & ESTOUP, A.
- Venue
- Molecular Ecology Notes
- Publisher
- Wiley
- Published
- 2005-06-09
- Volume
- 5
- Issue
- 3
- Pages
- 712-715
- ISSN
- 1471-8278 (ISSN-L)
- 1471-8286
- OpenAlex
- W2011521696
- Cited by
- 1,118
- References
- 11
- FWCI
- 10.92
- Type
- journal article
- Language
- en
- Open access
- closed
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: G eneland: a computer package for landscape genetics. https://app.cochat.ai/papers/10.1111/j.1471-8286.2005.01031.x
- The paper
- GUILLOT, G., MORTIER, F., & ESTOUP, A. (2005). G eneland: a computer package for landscape genetics. Molecular Ecology Notes. https://doi.org/10.1111/j.1471-8286.2005.01031.x
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.