Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1159390
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorOLIVEIRA, G. F.
dc.contributor.authorNASCIMENTO, A. C. C.
dc.contributor.authorAZEVEDO, C. F.
dc.contributor.authorCELERI, M. de O.
dc.contributor.authorBARROSO, L. M. A.
dc.contributor.authorSANT’ANNA, I. de C.
dc.contributor.authorVIANA, J. M. S.
dc.contributor.authorRESENDE, M. D. V. de
dc.contributor.authorNASCIMENTO, M.
dc.date.accessioned2023-12-08T19:32:09Z-
dc.date.available2023-12-08T19:32:09Z-
dc.date.created2023-12-08
dc.date.issued2023
dc.identifier.citationScientific Reports, v. 13, Article 9585, 2023.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1159390-
dc.descriptionThe aim of this study was to evaluate the performance of Quantile Regression (QR) in Genome-Wide Association Studies (GWAS) regarding the ability to detect QTLs (Quantitative Trait Locus) associated with phenotypic traits of interest, considering different population sizes. For this, simulated data was used, with traits of different levels of heritability (0.30 and 0.50), and controlled by 3 and 100 QTLs. Populations of 1,000 to 200 individuals were defined, with a random reduction of 100 individuals for each population. The power of detection of QTLs and the false positive rate were obtained by means of QR considering three different quantiles (0.10, 0.50 and 0.90) and also by means of the General Linear Model (GLM). In general, it was observed that the QR models showed greater power of detection of QTLs in all scenarios evaluated and a relatively low false positive rate in scenarios with a greater number of individuals. The models with the highest detection power of true QTLs at the extreme quantils (0.10 and 0.90) were the ones with the highest detection power of true QTLs. In contrast, the analysis based on the GLM detected few (scenarios with larger population size) or no QTLs in the evaluated scenarios. In the scenarios with low heritability, QR obtained a high detection power. Thus, it was verified that the use of QR in GWAS is effective, allowing the detection of QTLs associated with traits of interest even in scenarios with few genotyped and phenotyped individuals.
dc.language.isopor
dc.rightsopenAccess
dc.titlePopulation size in QTL detection using quantile regression in genome‑wide association studies.
dc.typeArtigo de periódico
dc.subject.nalthesaurusRegression analysis
dc.subject.nalthesaurusPhenotypic variation
dc.subject.nalthesaurusGenome-wide association study
dc.format.extent210 p.
riaa.ainfo.id1159390
riaa.ainfo.lastupdate2023-12-08
dc.identifier.doihttps://doi.org/10.1038/s41598-023-36730-z
dc.contributor.institutionGABRIELA FRANÇA OLIVEIRA, UNIVERSIDADE FEDERAL DE VIÇOSA
dc.contributor.institutionANA CAROLINA CAMPANA NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSApt_BR
dc.contributor.institutionCAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSApt_BR
dc.contributor.institutionMAURÍCIO DE OLIVEIRA CELERI, UNIVERSIDADE FEDERAL DE VIÇOSApt_BR
dc.contributor.institutionLAÍS MAYARA AZEVEDO BARROSO, INSTITUTO FEDERAL DE EDUCAÇÃO, CIÊNCIA E TECNOLOGIA DE MATO GROSSOpt_BR
dc.contributor.institutionISABELA DE CASTRO SANT’ANNA, INSTITUTO AGRONÔMICO DE CAMPINASpt_BR
dc.contributor.institutionJOSÉ MARCELO SORIANO VIANA, UNIVERSIDADE FEDERAL DE VIÇOSApt_BR
dc.contributor.institutionMARCOS DEON VILELA DE RESENDE, CNPCapt_BR
dc.contributor.institutionMOYSÉS NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA.pt_BR
Aparece nas coleções:Artigo em periódico indexado (SAPC)

Arquivos associados a este item:
Arquivo TamanhoFormato 
Population-size-in-QTL-detection.pdf3,37 MBAdobe PDFVisualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace