Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/908682
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dc.contributor.authorHIGA, R.pt_BR
dc.contributor.authorBARRICHELLO, F.pt_BR
dc.contributor.authorNICIURA, S.pt_BR
dc.contributor.authorMEIRELLES, S.pt_BR
dc.contributor.authorREGITANO, L.pt_BR
dc.date.accessioned2011-12-06T11:11:11Zpt_BR
dc.date.accessioned2011-12-06T11:11:11Zpt_BR
dc.date.available2011-12-06T11:11:11Zpt_BR
dc.date.available2011-12-06T11:11:11Zpt_BR
dc.date.created2011-12-06pt_BR
dc.date.issued2011pt_BR
dc.identifier.citationIn: INTERNATIONAL CONFERENCE OF THE BRAZILIAN ASSOCIATION FOR BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 7.; INTERNATIONAL CONFERENCE OF THE IBEROAMERICAN SOCIETY FOR BIOINFORMATICS, 3., 2011, Florianópolis. Proceedings... Florianópolis: Associação Brasileira de Bioinformática e Biologia Computacional, 2011.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/908682pt_BR
dc.descriptionRecent advances in massive genotyping technology based on SNP (Single Nucleotide Polymorphisms) markers are pushing animal breeding research into a new era where the entire genome is screened in the search for genes which affect traits of economic interest, called genome wide association studies (GWAS). The first step in setting up a GWAS is to perform a quality control analysis (QC) on the genotyped data in order to filter out samples and SNPs not satisfying a previously defined set of criteria [1]. The most common criteria include sample and SNP call rate, minor allele frequency (MAF) and Hardy-Weinberg equilibrium (HWE). It is also recommended to analyze the heterozygosity and the presence of population structure and outlier samples. However, a different set of criteria and thresholds may be more appropriate for different datasets. We wrote an R script [2] which implements a number of QC criteria, making them available as functions and allowing users to use those QC criteria which are more appropriate to their dataset. In this work, we describe a set of functions implemented in our R script and illustrate its use in a GWAS of cattle meat quality in a Canchim cattle breed population.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectMarcadores SNPpt_BR
dc.subjectPolimorfismo de nucleotídeo únicopt_BR
dc.titleAn R script for quality control in genome-wide association studies.pt_BR
dc.typeResumo em anais e proceedingspt_BR
dc.date.updated2020-01-24T11:11:11Zpt_BR
dc.subject.thesagroGenomapt_BR
dc.subject.thesagroGado de Cortept_BR
dc.subject.nalthesaurusGenomept_BR
dc.subject.nalthesaurusSingle nucleotide polymorphismpt_BR
dc.subject.nalthesaurusCattlept_BR
dc.description.notesX-MEETING 2011.pt_BR
dc.format.extent2Não paginado.pt_BR
riaa.ainfo.id908682pt_BR
riaa.ainfo.lastupdate2020-01-24 -02:00:00pt_BR
dc.contributor.institutionROBERTO HIROSHI HIGA, CNPTIA; FABIANA BARRICHELLO, UFSCar; SIMONE CRISTINA MEO NICIURA, CPPSE; SARAH MEIRELLES, UFLA; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE.pt_BR
Appears in Collections:Resumo em anais de congresso (CNPTIA)

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