dc.creatorCantet, R.J.C.
dc.creatorGarcía Baccino, C. A.
dc.creatorRogberg Muñoz, Andrés
dc.creatorForneris, N. S.
dc.creatorMunilla, S.
dc.date2017
dc.date2019-12-17T18:01:36Z
dc.date.accessioned2023-07-14T17:42:55Z
dc.date.available2023-07-14T17:42:55Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/87597
dc.identifierissn:0931-2668
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7428554
dc.descriptionGenome inheritance is by segments of DNA rather than by independent loci. We introduce the ancestral regression (AR) as a recursive system of simultaneous equations, with grandparental path coefficients as novel parameters. The information given by the pedigree in the AR is complementary with that provided by a dense set of genomic markers, such that the resulting linear function of grandparental BV is uncorrelated to the average of parental BV in the absence of inbreeding. AR is then connected to segmental inheritance by a causal multivariate Gaussian density for BV. The resulting covariance structure (Σ) is Markovian, meaning that conditional on the BV of parents and grandparents, the BV of the animal is independent of everything else. Thus, an algorithm is presented to invert the resulting covariance structure, with a computing effort that is linear in the number of animals as in the case of the inverse additive relationship matrix.
dc.descriptionInstituto de Genética Veterinaria
dc.formatapplication/pdf
dc.format224-231
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Veterinarias
dc.subjectbreeding value
dc.subjectcausal inference
dc.subjectGaussian Markov density
dc.subjectgenomic data
dc.subjectsegmental inheritance
dc.titleBeyond genomic selection: the animal model strikes back (one generation)!
dc.typeArticulo
dc.typeArticulo


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