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| 1. |  | SREEDASYAM, A.; PLOTT, C.; HOSSAIN, M. S.; LOVELL, J. T.; GRIMWOOD, J.; JENKINS, J. W.; DAUM, C.; BARRY, K.; CARLSON, J.; SHU, S.; PHILLIPS, J.; AMIREBRAHIMI, M.; ZANE, M.; WANG, M.; GOODSTEIN, D.; HAAS, F. B.; HISS, M.; PERROUD, P.-F.; JAWDY, S. S.; YANG, Y.; HU, R.; JOHNSON, J.; KROPAT, J.; GALLAHER, S. D.; LIPZEN, A.; SHAKIROV, E. V.; WENG, X.; TORRES-JEREZ, I.; WEERS, B.; CONDE, D.; PAPPAS, M. de C. R.; LIU, L.; MUCHLINSKI, A.; JIANG, H.; SHYU, C.; HUANG, P.; SEBASTIAN, J.; LAIBEN, C.; MEDLIN, A.; CAREY, S.; CARRELL, A. A.; CHEN, J.-G.; PERALES, M.; SWAMINATHAN, K.; ALLONA, I.; GRATTAPAGLIA, D.; COOPER, E. A.; THOLL, D.; VOGEL, V. P.; WESTON, D. J.; YANG, X.; BRUTNELL, T. P.; KELLOGG, E. A.; BAXTER, I.; UDVARDI, M.; TANG, Y.; MOCKLER, T. C.; JUENGER, T. E.; MULLET, J.; RENSING, S. A.; TUSKAN, G. A.; MERCHANT, S. S.; STACEY, G.; SCHMUTZ, J. JGI Plant Gene Atlas: an updateable transcriptome resource to improve functional gene descriptions across the plant kingdom. Nucleic Acids Research, v. 51, n. 16, p. 8383-8401, 2023. Na publicação: Marilia R. Pappas.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Gado de Leite. |
|
Data corrente: |
20/12/2012 |
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Data da última atualização: |
09/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 4 |
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Autoria: |
SILVA, M. V. G. B.; VAN TASSELL, C. P.; SONSTEGARD, T. S.; COBUCI, J. A.; GASBARRE, L. C. |
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Afiliação: |
MARCOS VINICIUS GUALBERTO B SILVA, CNPGL; CURTIS P. VAN TASSELL; TAD S. SONSTEGARD; JAIME ARAUJO COBUCI, UFRGS; LOUIS C. GASBARRE. |
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Título: |
Box-cox transformation and random regression models for fecal egg count data. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Frontiers in Genetics, v. 2, article 112, 2012. |
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DOI: |
https://doi.org/10.3389/fgene.2011.00112 |
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Idioma: |
Inglês |
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Conteúdo: |
Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated. |
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Palavras-Chave: |
Bovine; Box-cox transformation; Genetic parameters; REML. |
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Thesaurus NAL: |
fecal egg count. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02199naa a2200241 a 4500
001 1943307
005 2024-02-09
008 2012 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3389/fgene.2011.00112$2DOI
100 1 $aSILVA, M. V. G. B.
245 $aBox-cox transformation and random regression models for fecal egg count data.$h[electronic resource]
260 $c2012
520 $aAccurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.
650 $afecal egg count
653 $aBovine
653 $aBox-cox transformation
653 $aGenetic parameters
653 $aREML
700 1 $aVAN TASSELL, C. P.
700 1 $aSONSTEGARD, T. S.
700 1 $aCOBUCI, J. A.
700 1 $aGASBARRE, L. C.
773 $tFrontiers in Genetics$gv. 2, article 112, 2012.
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