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Open Access Methodology article

iXora: exact haplotype inferencing and trait association

Filippo Utro1, Niina Haiminen1, Donald Livingstone24, Omar E Cornejo3, Stefan Royaert2, Raymond J Schnell24, Juan Carlos Motamayor4, David N Kuhn2 and Parida Laxmi1*

Author Affiliations

1 Computational Biology Center, IBM T J Watson Research, Yorktown Heights, NY, USA

2 USDA-ARS SHRS, Miami, FL, USA

3 Stanford University, Stanford, CA, USA

4 MARS, Incorporated, Miami, FL, USA

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BMC Genetics 2013, 14:48  doi:10.1186/1471-2156-14-48

Published: 6 June 2013

Abstract

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 webcite.

Keywords:
Haplotype; Phasing; Phenotype Association; Trait Association; QTL; Randomization