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Bayesian Analysis of Isochores.

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Bayesian Analysis of Isochores. / Fearnhead, Paul; Vasilieou, Despina.
In: Journal of the American Statistical Association, Vol. 485, 01.03.2009, p. 132-141.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Fearnhead, P & Vasilieou, D 2009, 'Bayesian Analysis of Isochores.', Journal of the American Statistical Association, vol. 485, pp. 132-141. https://doi.org/10.1198/jasa.2009.0009

APA

Fearnhead, P., & Vasilieou, D. (2009). Bayesian Analysis of Isochores. Journal of the American Statistical Association, 485, 132-141. https://doi.org/10.1198/jasa.2009.0009

Vancouver

Fearnhead P, Vasilieou D. Bayesian Analysis of Isochores. Journal of the American Statistical Association. 2009 Mar 1;485:132-141. doi: 10.1198/jasa.2009.0009

Author

Fearnhead, Paul ; Vasilieou, Despina. / Bayesian Analysis of Isochores. In: Journal of the American Statistical Association. 2009 ; Vol. 485. pp. 132-141.

Bibtex

@article{360b4a99cb5a4e16910e9571e27f93fd,
title = "Bayesian Analysis of Isochores.",
abstract = "Statistical identification of isochore structure, the variation in large-scale GC composition (proportion of DNA bases that are G or C as opposed to A or T), of mammalian genomes is a necessary requirement for understanding both the evolution of base composition and the many genomic features such as mutation and recombination rates, which covary with base composition. We have developed a Bayesian method for isochore analysis that we demonstrate to be more accurate than the commonly used binary segmentation approach implemented within the program IsoFinder. The method accounts for both fine-scale and large-scale structure. We adapt direct simulation methods to allow for iid samples from the posterior distribution of our model, and provide an accurate approximation to this that can analyze data from a chromosome in a matter of seconds. We apply our method to human chromosome 1. The resulting estimate of how GC content varies across this region is shown to be a better predictor of local recombination rates than IsoFinder, and we are able to detect regions consistent with the classic definition of isochores that cover 85% of the chromosome. We also show a measure of relative GC content to be particularly predictive of local recombination rates.",
author = "Paul Fearnhead and Despina Vasilieou",
year = "2009",
month = mar,
day = "1",
doi = "10.1198/jasa.2009.0009",
language = "English",
volume = "485",
pages = "132--141",
journal = "Journal of the American Statistical Association",
issn = "1537-274X",
publisher = "Taylor and Francis Ltd.",

}

RIS

TY - JOUR

T1 - Bayesian Analysis of Isochores.

AU - Fearnhead, Paul

AU - Vasilieou, Despina

PY - 2009/3/1

Y1 - 2009/3/1

N2 - Statistical identification of isochore structure, the variation in large-scale GC composition (proportion of DNA bases that are G or C as opposed to A or T), of mammalian genomes is a necessary requirement for understanding both the evolution of base composition and the many genomic features such as mutation and recombination rates, which covary with base composition. We have developed a Bayesian method for isochore analysis that we demonstrate to be more accurate than the commonly used binary segmentation approach implemented within the program IsoFinder. The method accounts for both fine-scale and large-scale structure. We adapt direct simulation methods to allow for iid samples from the posterior distribution of our model, and provide an accurate approximation to this that can analyze data from a chromosome in a matter of seconds. We apply our method to human chromosome 1. The resulting estimate of how GC content varies across this region is shown to be a better predictor of local recombination rates than IsoFinder, and we are able to detect regions consistent with the classic definition of isochores that cover 85% of the chromosome. We also show a measure of relative GC content to be particularly predictive of local recombination rates.

AB - Statistical identification of isochore structure, the variation in large-scale GC composition (proportion of DNA bases that are G or C as opposed to A or T), of mammalian genomes is a necessary requirement for understanding both the evolution of base composition and the many genomic features such as mutation and recombination rates, which covary with base composition. We have developed a Bayesian method for isochore analysis that we demonstrate to be more accurate than the commonly used binary segmentation approach implemented within the program IsoFinder. The method accounts for both fine-scale and large-scale structure. We adapt direct simulation methods to allow for iid samples from the posterior distribution of our model, and provide an accurate approximation to this that can analyze data from a chromosome in a matter of seconds. We apply our method to human chromosome 1. The resulting estimate of how GC content varies across this region is shown to be a better predictor of local recombination rates than IsoFinder, and we are able to detect regions consistent with the classic definition of isochores that cover 85% of the chromosome. We also show a measure of relative GC content to be particularly predictive of local recombination rates.

U2 - 10.1198/jasa.2009.0009

DO - 10.1198/jasa.2009.0009

M3 - Journal article

VL - 485

SP - 132

EP - 141

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

SN - 1537-274X

ER -