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Inference of population structure using multilocus genotype data: dominant markers and null alleles
Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1974779/ https://www.ncbi.nlm.nih.gov/pubmed/18784791 http://dx.doi.org/10.1111/j.1471-8286.2007.01758.x |
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author | FALUSH, DANIEL STEPHENS, MATTHEW PRITCHARD, JONATHAN K |
author_facet | FALUSH, DANIEL STEPHENS, MATTHEW PRITCHARD, JONATHAN K |
author_sort | FALUSH, DANIEL |
collection | PubMed |
description | Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html. |
format | Text |
id | pubmed-1974779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-19747792007-09-18 Inference of population structure using multilocus genotype data: dominant markers and null alleles FALUSH, DANIEL STEPHENS, MATTHEW PRITCHARD, JONATHAN K Mol Ecol Notes Technical Articles Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html. Blackwell Publishing Ltd 2007-07-01 /pmc/articles/PMC1974779/ /pubmed/18784791 http://dx.doi.org/10.1111/j.1471-8286.2007.01758.x Text en © 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd https://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation. |
spellingShingle | Technical Articles FALUSH, DANIEL STEPHENS, MATTHEW PRITCHARD, JONATHAN K Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title | Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title_full | Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title_fullStr | Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title_full_unstemmed | Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title_short | Inference of population structure using multilocus genotype data: dominant markers and null alleles |
title_sort | inference of population structure using multilocus genotype data: dominant markers and null alleles |
topic | Technical Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1974779/ https://www.ncbi.nlm.nih.gov/pubmed/18784791 http://dx.doi.org/10.1111/j.1471-8286.2007.01758.x |
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