Your browser doesn't support javascript.
loading
iXora: exact haplotype inferencing and trait association.
Utro, Filippo; Haiminen, Niina; Livingstone, Donald; Cornejo, Omar E; Royaert, Stefan; Schnell, Raymond J; Motamayor, Juan Carlos; Kuhn, David N; Parida, Laxmi.
Afiliação
  • Utro F; Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY, USA.
BMC Genet ; 14: 48, 2013 Jun 06.
Article em En | MEDLINE | ID: mdl-23742238
BACKGROUND: We address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. While methods for inferring parental haplotype assignments on large F1 populations exist in theory, these approaches do not work in practice at high levels of accuracy. RESULTS: We have designed iXora (Identifying crossovers and recombining alleles), a robust method for extracting reliable haplotypes of a mapping population, as well as parental haplotypes, that runs in linear time. Each allele in the progeny is assigned not just to a parent, but more precisely to a haplotype inherited from the parent. iXora shows an improvement of at least 15% in accuracy over similar systems in literature. Furthermore, iXora provides an easy-to-use, comprehensive environment for association studies and hypothesis checking in populations of related individuals. CONCLUSIONS: iXora provides detailed resolution in parental inheritance, along with the capability of handling very large populations, which allows for accurate haplotype extraction and trait association. iXora is available for non-commercial use from http://researcher.ibm.com/project/3430.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Haplótipos / Locos de Características Quantitativas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Haplótipos / Locos de Características Quantitativas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2013 Tipo de documento: Article