JSM 2005 - Toronto

Abstract #303827

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Activity Number: 370
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #303827
Title: Likelihood-based Inference for Multicolor Optical Mapping Data
Author(s): Liping Tong*+ and Mary Sara McPeek and Laurens Mets
Companies: University of Washington and The University of Chicago and The University of Chicago
Address: 1201 Ne 52nd St, Seattle, WA, 98105, United States
Keywords: Optical mapping ; Maximum likelihood ; Hidden Markov model ; Simulated annealing
Abstract:

Multicolor optical mapping is a new high-throughput technique to get the detailed physical map (indicating relative positions of various recognition sites) of any DNA molecule of interest. We consider a study design in which the data consist of noisy observations of multiple copies of a DNA molecule marked with colors at recognition sites. The primary goal is to estimate a physical map. A secondary goal is to estimate error rates associated with the experiment, which are useful for analysis and refinement of the biochemical steps in the mapping procedure. We propose statistical models for various sources of error and use maximum likelihood estimation (MLE) to construct a physical map and estimate error rates. To overcome difficulties arising in the maximization process, a hidden Markov method (HMM) is proposed and the EM algorithm is used for maximization. In addition, a simulated annealing procedure is applied to maximize the profile likelihood over the discrete space of sequences of colors. We apply the methods to the bacteriophage lambda genome.

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Revised March 2005