Published online 6 June 2006
© 2006 The Author(s)
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An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs
1 Molecular Biology Institute, Center for Computational Biology, Department of Chemistry and Biochemistry, University of California Los Angeles, USA 2 Department of Statistics, University of California Los Angeles, USA 3 Dental Research Institute, School of Dentistry, University of California Los Angeles, USA
*To whom correspondence should be addressed. Tel: +1 310 825 7374; Fax: +1 310 206 7286. Email: leec{at}mbi.ucla.edu
*Correspondence may also be addressed to Yi Xing. Email: yxing{at}ucla.edu
Received January 29, 2006. Revised April 13, 2006. Accepted May 10, 2006.
Reconstructing full-length transcript isoforms from sequence fragments (such as ESTs) is a major interest and challenge for bioinformatic analysis of pre-mRNA alternative splicing. This problem has been formulated as finding traversals across the splice graph, which is a directed acyclic graph (DAG) representation of gene structure and alternative splicing. In this manuscript we introduce a probabilistic formulation of the isoform reconstruction problem, and provide an expectation-maximization (EM) algorithm for its maximum likelihood solution. Using a series of simulated data and expressed sequences from real human genes, we demonstrate that our EM algorithm can correctly handle various situations of fragmentation and coupling in the input data. Our work establishes a general probabilistic framework for splice graph-based reconstructions of full-length isoforms.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
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