Advanced search
1 file | 71.93 KB

CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data

Steven Maenhout (UGent) , Bernard De Baets (UGent) and Geert Haesaert (UGent)
(2009) BIOINFORMATICS. 25(20). p.2753-2754
Author
Organization
Abstract
Motivation: Phenotypic data collected in breeding programs and marker-trait association studies are often analyzed by means of linear mixed models. In these models, the covariance between the genetic background effects of all genotypes under study is modeled by means of pairwise coefficients of coancestry. Several marker-based coancestry estimation procedures allow to estimate this covariance matrix, but generally introduce a certain amount of bias when the examined genotypes are part of a breeding program. CoCoa implements the most commonly used marker-based coancestry estimation procedures and as such, allows to select the best fitting covariance structure for the phenotypic data at hand. This better model fit translates into an increased power and improved type I error control in association studies and an improved accuracy in phenotypic prediction studies. The presented software package also provides an implementation of the new Weighted Alikeness in State (WAIS) estimator for use in hybrid breeding programs. Besides several matrix manipulation tools, CoCoa implements two different bending heuristics, in case the inverse of an ill-conditioned coancestry matrix estimate is needed.
Keywords
MAIZE

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 71.93 KB

Citation

Please use this url to cite or link to this publication:

Chicago
Maenhout, Steven, Bernard De Baets, and Geert Haesaert. 2009. “CoCoa: a Software Tool for Estimating the Coefficient of Coancestry from Multilocus Genotype Data.” Bioinformatics 25 (20): 2753–2754.
APA
Maenhout, S., De Baets, B., & Haesaert, G. (2009). CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data. BIOINFORMATICS, 25(20), 2753–2754.
Vancouver
1.
Maenhout S, De Baets B, Haesaert G. CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data. BIOINFORMATICS. 2009;25(20):2753–4.
MLA
Maenhout, Steven, Bernard De Baets, and Geert Haesaert. “CoCoa: a Software Tool for Estimating the Coefficient of Coancestry from Multilocus Genotype Data.” BIOINFORMATICS 25.20 (2009): 2753–2754. Print.
@article{783880,
  abstract     = {Motivation: Phenotypic data collected in breeding programs and marker-trait association studies are often analyzed by means of linear mixed models. In these models, the covariance between the genetic background effects of all genotypes under study is modeled by means of pairwise coefficients of coancestry. Several marker-based coancestry estimation procedures allow to estimate this covariance matrix, but generally introduce a certain amount of bias when the examined genotypes are part of a breeding program. CoCoa implements the most commonly used marker-based coancestry estimation procedures and as such, allows to select the best fitting covariance structure for the phenotypic data at hand. This better model fit translates into an increased power and improved type I error control in association studies and an improved accuracy in phenotypic prediction studies. The presented software package also provides an implementation of the new Weighted Alikeness in State (WAIS) estimator for use in hybrid breeding programs. Besides several matrix manipulation tools, CoCoa implements two different bending heuristics, in case the inverse of an ill-conditioned coancestry matrix estimate is needed.},
  author       = {Maenhout, Steven and De Baets, Bernard and Haesaert, Geert},
  issn         = {1367-4803},
  journal      = {BIOINFORMATICS},
  keyword      = {MAIZE},
  language     = {eng},
  number       = {20},
  pages        = {2753--2754},
  title        = {CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data},
  url          = {http://dx.doi.org/10.1093/bioinformatics/btp499},
  volume       = {25},
  year         = {2009},
}

Altmetric
View in Altmetric
Web of Science
Times cited: