Journal Article

Efficient whole-genome association mapping using local phylogenies for unphased genotype data

Zhihong Ding, Thomas Mailund and Yun S. Song

in Bioinformatics

Volume 24, issue 19, pages 2215-2221
Published in print October 2008 | ISSN: 1367-4803
Published online July 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn406
Efficient whole-genome association mapping using local phylogenies for unphased genotype data

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Motivation: Recent advances in genotyping technology has made data acquisition for whole-genome association study cost effective, and a current active area of research is developing efficient methods to analyze such large-scale datasets. Most sophisticated association mapping methods that are currently available take phased haplotype data as input. However, phase information is not readily available from sequencing methods and inferring the phase via computational approaches is time-consuming, taking days to phase a single chromosome.

Results: In this article, we devise an efficient method for scanning unphased whole-genome data for association. Our approach combines a recently found linear-time algorithm for phasing genotypes on trees with a recently proposed tree-based method for association mapping. From unphased genotype data, our algorithm builds local phylogenies along the genome, and scores each tree according to the clustering of cases and controls. We assess the performance of our new method on both simulated and real biological datasets.

Availability The software described in this article is available at http://www.daimi.au.dk/~mailund/Blossoc and distributed under the GNU General Public License.

Contact:mailund@birc.au.dk

Journal Article.  5827 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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