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I am a senior lecturer in the Department of Statistics at The University
of Auckland.
Contact information
E-mail: s.browning@auckland.ac.nz.
Phone: +64-9-3737-599 x88745.
Location:
Building 303 (Science Centre / Maths-Physics building), Room 220.
For mailing/fax
information see the Department of Statistics webpage.
My current research is focussed on linkage disequilibrium gene
mapping, particularly on methods that make use of the correlation structure in
closely spaced genetic markers, and that are fast enough to be applied to whole
genome scans (500K+ markers). The BEAGLE program implements much of my recent research work (in collaboration with Brian Browning, the author of this software). BEAGLE is useful for haplotypic association testing, haplotype inference and imputation, all on a genome-wide scale. More applications will be coming soon...
I am
affiliated with the Bioinformatics
Institute and am interested in all areas of bioinformatics, especially
those that directly impact human health.
I am a member of MapNet and the associated New Zealand Virtual Institute of Statistical Genetics.
I am an associate editor for Statistical Applications in Genetics and Molecular Biology.
I am an invited speaker at the 2009 Australian GeneMappers conference.
Recent
publications with comments and links to abstracts/articles:
·
Browning, B. L. and S. R. Browning, 2009. A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals
American Journal of Human Genetics, 84: 210-223 (link to abstract/article). We extended our earlier haplotype phasing work to imputation of ungenotyped markers and to phasing of parent-offspring trios. Our approach is applicable to whole genome association data, and has high computational efficiency as well as excellent accuracy.
·
Madsen, B. E. and S. R. Browning, 2009. A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic
PLOS Genetics, 5: e1000384 (link to abstract/article). We provide a test for whether mutations are more common in cases than in controls (in a gene or set of genes), which provides a useful complement to single-marker association testing, particularly in those diseases for which de novo mutations play an important role.
·
Browning, S. R. 2008. Missing data imputation and haplotype phase inference for genome-wide association studies
Human Genetics, 124:439-450 (link to abstract/article). This is a review article.
·
Black J. M., S. R. Browning, A. V. Collins, and J. R. Phillips 2008. A canine model of inherited myopia: Familial aggregation of refractive error in Labrador Retrievers.
Investigative Ophthalmology and Visual Science,49:4784-4789 (link to abstract/article).
·
Browning S. R. 2008. Estimation of pairwise identity by
descent from dense genetic marker data in a population sample of haplotypes.
Genetics, 178:2123-2132 (link to abstract/article). I use
the BEAGLE model for linkage disequilibrium. This allows me to estimate IBD using full
multilocus information. Future extension to unphased genotype data is planned.
·
Browning B. L. and S. R. Browning 2008. Haplotypic analysis of
Wellcome Trust Case Control Consortium data.
Human Genetics, 123:273-280 (link
to abstract/article). We applied BEAGLE to haplotype and analyze
the Wellcome Trust Case Control data. We found a several novel associations, as
well as some interesting artifacts.
·
Browning, S.R. and J. Thomas 2007. Multilocus analysis of GAW15 NARAC
chromosome 18 case-control data, Genetic Analysis
Workshop 15, St. Pete Beach, Florida, USA, 11-15 November 2006, BMC Proceedings, 1(Suppl
1): S11 (link to open
access article). We applied the multilocus association method
implemented in Beagle to Rheumatoid Arthritis data from the Genetic Analysis
Workshop.
·
Browning S. R. and B. L. Browning 2007. Rapid and accurate haplotype phasing and
missing data inference for whole genome association studies using localized
haplotype clustering. American Journal of Human Genetics,
81:1084-1097 (link
to abstract/article). This new method
for haplotype phasing is available in the latest release of the BEAGLE program.
·
Browning B. L. and S. R. Browning 2007. Efficient multilocus association testing
for whole genome association studies using localized haplotype clustering. Genetic
Epidemiology, 31:365-375 (link
to abstract/article). Provides
efficient software implementation of the method proposed in Browning 2006, and
extensive simulation results assessing the value of the method. Link to BEAGLE
program. This paper received the Best Paper Award from the International Genetic Epidemiology Society for best paper published in Genetic Epidemiology in 2007.
·
Browning S. R. 2006. Multilocus
association mapping using variable-length Markov chains. American Journal of Human Genetics, 78:903-913
(link to
abstract/article).
Variable length Markov chains are like higher-order Markov chains,
but allow the order to depend on the context.
They are a useful way to represent linkage disequilibrium and cluster
haplotypes for association analysis, particularly over large genomic regions. (Old R code
for HapVLMC. New BEAGLE
Java program is easier to use and fast and memory efficient for large data
sets.)
Link
to list of earlier publications.
Places
I’ve worked:
Genetics
Research, GlaxoSmithKline, 2002-2005.
Bioinformatics Research Center, North Carolina State University, 2000-2002.
Department
of Statistics, Texas A&M, 1999-2000.
Education:
PhD in Statistics, University of Washington,
BScHons in Mathematics, University
of Auckland, 1995.
Other
links:
Brian Browning’s PRESTO program (rapid permutation testing for
genetic association studies).
Brian Browning’s FLOSS (FLexible
Ordered SubSets) program.
Last
updated: 27 January, 2009