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| Registros recuperados : 10 | |
| 5. |  | LEGARRA, A.; CHRISTENSEN, O. F.; VITEZICA, Z. G.; AGUILAR, I.; MISZTAL, I. Across-breeds ancestral relationships and metafounders for genomic evaluation. Volume Genetic Improvement Programs: Selection using molecular information, 075. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.075. Acknowledgements: This project has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees for providing computing resources.| Biblioteca(s): INIA Las Brujas. |
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| 6. | | ANTONIOS, S.; RODRÍGUEZ-RAMILO, S.T.; AGUILAR, I.; ASTRUC, J.M.; LEGARRA, A.; VITEZICA, Z. G. Genomic and pedigree estimation of inbreeding depression for semen traits in the Basco-Béarnaise dairy sheep breed. Journal of Dairy Science, 2021, volume 104, number 3, pages 3221-3230. doi: https://doi.org/10.3168/jds.2020-18761 Article history: Receibed: April 21, 2020 / Accepted: October 5, 2020 /First Publication: 23 Decembrer 2020.
Corresponding author: zulma.viterica@inrae.fr| Biblioteca(s): INIA Treinta y Tres. |
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| 8. | | FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; CANTET, R. J. C. Quality control of genotypes using heritability estimates of gene content at the marker. Genetics, 2015, v. 199, p. 675-681. OPEN ACCESS. Manuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 9. | | FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; CANTET, R.J.C.; MISZTAL, I. Quality control of genotypes using heritability estimates of gene content. Volume Genetic Improvement Programs: Selection using molecular information (Posters), 471. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.471.| Biblioteca(s): INIA Las Brujas. |
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| 10. | | WANG, H.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A.; FERNANDO, R.L.; VITEZICA, Z.; OKIMOTO, R.; WING, T.; HAWKEN, R.; MUIR, W.M. Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens. Frontiers in Genetics, 2014, v.5, p.1-10. OPEN ACCESS. Article history: Received 03 March 2014 // Paper pending published 04 April 2014 // Accepted 25 April 2014 // Published online: 20 May 2014.| Biblioteca(s): INIA Las Brujas. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
26/11/2015 |
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Actualizado : |
18/06/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; CANTET, R. J. C. |
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Afiliación : |
NATALIA S. FORNERIS, Universidad de Buenos Aires (UBA)/ Facultad de Agronomía; INRA (Institut National de la Recherche Agronomique); ANDRÉS LEGARRA, INRA (Institut National de la Recherche Agronomique); Université de Toulouse; ZULMA G. VITEZICA, INRA (Institut National de la Recherche Agronomique); Université de Toulouse; SHOGO TSURUTA, Universidad de Georgia (UG); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACY MISZTAL, Universidad de Georgia (UG); RODOLFO J. C. CANTET, Universidad de Buenos Aires (UBA)/ Facultad de Agronomía; INRA (Institut National de la Recherche Agronomique). |
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Título : |
Quality control of genotypes using heritability estimates of gene content at the marker. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Genetics, 2015, v. 199, p. 675-681. OPEN ACCESS. |
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DOI : |
10.1534/genetics.114.173559 |
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Idioma : |
Inglés |
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Notas : |
Manuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015. |
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Contenido : |
ABSTRACT
Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.
Copyright © 2015 by the Genetics Society of America MenosABSTRACT
Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4... Presentar Todo |
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Palabras claves : |
GENE CONTENT; GENOMIC SELECTION; GENPRED; QUALITY CONTROL; REML; SHARED DATA RESOURCE; SNP. |
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Thesagro : |
MEJORAMIENTO GENETICO ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5302/1/Forneris-et-al-2015-Genetics.pdf
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Marc : |
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100 1 $aFORNERIS, N. S.
245 $aQuality control of genotypes using heritability estimates of gene content at the marker.$h[electronic resource]
260 $c2015
500 $aManuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015.
520 $aABSTRACT Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided. Copyright © 2015 by the Genetics Society of America
650 $aMEJORAMIENTO GENETICO ANIMAL
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653 $aGENOMIC SELECTION
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653 $aQUALITY CONTROL
653 $aREML
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700 1 $aLEGARRA, A.
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700 1 $aMISZTAL, I.
700 1 $aCANTET, R. J. C.
773 $tGenetics, 2015$gv. 199, p. 675-681. OPEN ACCESS.
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