Abstract #300196

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JSM 2002 Abstract #300196
Activity Number: 164
Type: Invited
Date/Time: Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing*
Abstract - #300196
Title: The Assessment of the Significance of Inter-Species Matches Based on Hidden Markov Models
Author(s): Jia Li*+
Affiliation(s): Pennsylvania State University
Address: 417A Thomas Building, University Park, Pennsylvania, 16802, USA
Keywords: Hidden Markov Models ; divergence rates ; human-mouse alignment
Abstract:

Hidden Markov Models (HMMs) form powerful tools for identifying trends in sequences. In this work, we employ an HMM to capture variations in divergence rates of evolution along an aligned pair of DNA sequences, using human-mouse alignments as an example. This allows us to take into consideration background divergence rates when assessing the statistical significance of gap-free alignments between two genomic DNA sequences. In some cases, the weaker of two matches may be judged as less likely to have arisen by chance, provided it lies in a genomic interval with a high level of background divergence. Our methods are illustrated in detail using a 1.49Mb genomic region. Preliminary results using all of human chromosome 22 indicate that these techniques will work for the entire human genome.

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Revised March 2002