Estimating recombination rates from single-nucleotide polymorphisms using summary statistics.
We describe a novel method for jointly estimating crossing-over and gene-conversion rates from population genetic data using summary statistics. The performance of our method was tested on simulated data sets and compared with the composite-likelihood method of R. R. Hudson. For several realistic parameter values, the new method performed similarly to the composite-likelihood approach for estimating crossing-over rates and better when estimating gene-conversion rates. We used our method to analyze a human data set recently genotyped by Perlegen Sciences.
Padhukasahasram
Badri
B
Molecular and Computational Biology and Biostatistics Division, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90089, USA. pkbadri@yahoo.com
Wall
Jeffrey D
JD
Marjoram
Paul
P
Nordborg
Magnus
M
D003198:Computer Simulation; D003434:Crossing Over, Genetic; D005785:Gene Conversion; D005828:Genetics, Population; D015894:Genome, Human; D006239:Haplotypes; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D011995:Recombination, Genetic; D017422:Sequence Analysis, DNA; D013223:Statistics as Topic