|
|
Registro completo
|
Biblioteca (s) : |
INIA Salto Grande; INIA Tacuarembó. |
Fecha : |
15/07/2015 |
Actualizado : |
24/10/2019 |
Tipo de producción científica : |
Revista INIA |
Autor : |
INIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA) |
Título : |
Revista INIA Uruguay. (No.2, Marzo 2005). |
Fecha de publicación : |
2005 |
Fuente / Imprenta : |
Montevideo (Uruguay) : INIA, 2005. |
Páginas : |
48 p. |
Serie : |
(Revista INIA; 02) |
ISSN : |
1510-9011 |
Idioma : |
Español |
Thesagro : |
ARROZ; BIOTECNOLOGIA; BOVINOS DE CARNE; C0NTROL DE ENFERMEDADES; CAMBIO CLIMATICO; CIENCIA; CITRUS; CLIMA; CLIMATOLOGIA; COMUNICACION; CULTIVOS DE GRANO; CULTIVOS DE SECANO; ENTOMOLOGIA; ESPECIES FORRAJERAS; EUCALYPTUS; EXPLOTACION AGRICOLA FAMILIAR; FITOPATOLOGIA; FORESTALES; FORRAJES; FRUTALES; FRUTICULTURA; GANADO BOVINO; GRANOS; GRAS; HORTALIZAS; HORTICULTURA; INIA; INNOVACION; INVESTIGACIÓN; LECHERÍA; LEGUMINOSAS FORRAJERAS; MANEJO DE CULTIVOS; MEJORAMIENTO ANIMAL; METEOROLOGIA; MICROBIOLOGIA; OVINOS; PASTURAS; PRODUCCIÓN ANIMAL; PRODUCCION DE LANA; PRODUCCION DE LECHE; PRODUCCION LECHERA; REVISTA INIA 2005; SEMILLAS; SOJA; SUELOS; SUINOS; SUSTENTABILIDAD AMBIENTAL; TECNOLOGÍA; TRANSFERENCIA DE TECNOLOGIA; VARIEDADES; VITICULTURA. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13596/1/Revista-INIA-02.pdf
http://www.ainfo.inia.uy/digital/bitstream/item/4811/1/Revista-INIA-02.pdf
|
Marc : |
LEADER 01901nam a2200745 a 4500 001 1053065 005 2019-10-24 008 2005 bl uuuu u00u1 u #d 022 $a1510-9011 100 1 $aINIA (INSTITUTO NACIONAL DE INVESTIGACIÓN AGROPECUARIA) 245 $aRevista INIA Uruguay. (No.2, Marzo 2005). 260 $aMontevideo (Uruguay) : INIA$c2005 300 $a48 p. 490 $a(Revista INIA; 02) 650 $aARROZ 650 $aBIOTECNOLOGIA 650 $aBOVINOS DE CARNE 650 $aC0NTROL DE ENFERMEDADES 650 $aCAMBIO CLIMATICO 650 $aCIENCIA 650 $aCITRUS 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aCOMUNICACION 650 $aCULTIVOS DE GRANO 650 $aCULTIVOS DE SECANO 650 $aENTOMOLOGIA 650 $aESPECIES FORRAJERAS 650 $aEUCALYPTUS 650 $aEXPLOTACION AGRICOLA FAMILIAR 650 $aFITOPATOLOGIA 650 $aFORESTALES 650 $aFORRAJES 650 $aFRUTALES 650 $aFRUTICULTURA 650 $aGANADO BOVINO 650 $aGRANOS 650 $aGRAS 650 $aHORTALIZAS 650 $aHORTICULTURA 650 $aINIA 650 $aINNOVACION 650 $aINVESTIGACIÓN 650 $aLECHERÍA 650 $aLEGUMINOSAS FORRAJERAS 650 $aMANEJO DE CULTIVOS 650 $aMEJORAMIENTO ANIMAL 650 $aMETEOROLOGIA 650 $aMICROBIOLOGIA 650 $aOVINOS 650 $aPASTURAS 650 $aPRODUCCIÓN ANIMAL 650 $aPRODUCCION DE LANA 650 $aPRODUCCION DE LECHE 650 $aPRODUCCION LECHERA 650 $aREVISTA INIA 2005 650 $aSEMILLAS 650 $aSOJA 650 $aSUELOS 650 $aSUINOS 650 $aSUSTENTABILIDAD AMBIENTAL 650 $aTECNOLOGÍA 650 $aTRANSFERENCIA DE TECNOLOGIA 650 $aVARIEDADES 650 $aVITICULTURA
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA Salto Grande (SG) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
Registro completo
|
Biblioteca (s) : |
INIA La Estanzuela. |
Fecha actual : |
21/02/2014 |
Actualizado : |
05/12/2018 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 1 |
Autor : |
BRANDARIZ , S.; GONZÁLEZ RAYMÚNDEZ, A.; LADO, B.; MALOSETTI, M.; FRANCO GARCIA, A.; QUINCKE, M.; VON ZITZEWITZ, J.; CASTRO, M.; MATUS,I.; DEL POZO, A.; CASTRO, A.J.; GUTIÉRREZ, L. |
Afiliación : |
SOFÍA P. BRANDARIZ, Universidad de la República (UdelaR); Facultad de Agronomía, Uruguay.; AGUSTÍN GONZÁLEZ REYMÚNDEZ; BETTINA LADO; MARCOS MALOSETTI; ANTONIO AUGUSTO FRANCO GARCIA; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JARISLAV RAMON VON ZITZEWITZ VON SALVIATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IVÁN MATUS; ALEJANDRO DEL POZO; ARIEL J. CASTRO; LUCÍA GUTIÉRREZ. |
Título : |
Ascertainment bias from imputation methods evaluation in wheat. |
Fecha de publicación : |
2016 |
Fuente / Imprenta : |
BMC Genomics, 2016, v. 17, p.773. |
DOI : |
10.1186/s12864-016-3120-5 |
Idioma : |
Inglés |
Notas : |
OPEN ACCESS. Article history: Received 2016 Feb 24 // Accepted 2016 Sep 23. |
Contenido : |
Abstract
BACKGROUND:
Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel.
RESULTS:
In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available.
CONCLUSIONS:
Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel. MenosAbstract
BACKGROUND:
Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel.
RESULTS:
In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between ... Presentar Todo |
Palabras claves : |
FALSE POSITIVE; FALSO POSITIVO; GBS; GWAS; POWER; QTLs. |
Thesagro : |
MEJORAMIENTO DE TRIGO. |
Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12122/1/s12864-016-3120-5.pdf
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-3120-5
|
Marc : |
LEADER 02972nam a2200349 a 4500 001 1047336 005 2018-12-05 008 2016 bl uuuu u0uu1 u #d 024 7 $a10.1186/s12864-016-3120-5$2DOI 100 1 $aBRANDARIZ , S. 245 $aAscertainment bias from imputation methods evaluation in wheat.$h[electronic resource] 260 $aBMC Genomics, 2016, v. 17, p.773.$c2016 500 $aOPEN ACCESS. Article history: Received 2016 Feb 24 // Accepted 2016 Sep 23. 520 $aAbstract BACKGROUND: Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel. RESULTS: In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available. CONCLUSIONS: Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel. 650 $aMEJORAMIENTO DE TRIGO 653 $aFALSE POSITIVE 653 $aFALSO POSITIVO 653 $aGBS 653 $aGWAS 653 $aPOWER 653 $aQTLs 700 1 $aGONZÁLEZ RAYMÚNDEZ, A. 700 1 $aLADO, B. 700 1 $aMALOSETTI, M. 700 1 $aFRANCO GARCIA, A. 700 1 $aQUINCKE, M. 700 1 $aVON ZITZEWITZ, J. 700 1 $aCASTRO, M. 700 1 $aMATUS,I. 700 1 $aDEL POZO, A. 700 1 $aCASTRO, A.J. 700 1 $aGUTIÉRREZ, L.
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA La Estanzuela (LE) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
Expresión de búsqueda válido. Check! |
|
|