|Genome Informatics Section
DOE Human Genome Program Contractor-Grantee Workshop
115. Allele Frequency Estimation from Sequence Trace Data
David G. Politte, David R. Maffitt, and
David J. States
Parametric model fitting of unprocessed sequencing-gel trace data and a least squares optimization algorithm provide a method for accurately determining allele frequencies of a single nucleotide polymorphism in a population. The method uses trace data from one or two homozygous individuals as a reference to estimate allele frequencies present in DNA derived from a pooled population. A parametric model is fit to each of the traces to estimate the amount of each of the four fluorescent dyes that is present at each site. The parameters estimated from each trace are then normalized to account for scalar variations due to differences in the amount of template or sample loaded. The parameters estimated from the trace of the heterozygous individual or from the mixture are viewed as a weighted sum of the parameters estimated from the traces of the homozygous individuals. The weights, or allele frequencies, are estimated by minimizing the sum of squared errors between the linear combination of homozygous traces and the mixed trace. Comparison of allele frequencies estimated by our method to known frequencies at polymorphic sites in three pools of CEPH individuals show that our method is accurate to ~10% even when only a single homozygous reference is available. The allele frequency estimator is accessed via a portable Java based interface that reads ABD or SCF format trace files and allows the user to interactively select sites of interest. When a site has been identified, allele frequency estimation calculations are performed remotely using HTTP mediated requests. Our method is automatic and much less labor intensive than previous approaches. Software is available at http://www.ibc.wustl.edu/ software/allele-estimation.
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