Probabilistic Isoform Reconstruction
Title and abstract below. Details soon. This paper focuses on the method. It describes the application of EM algorithm in isoform inference from splice graph. R code will be made available. The algorithm can also be used on top of existing splice graph & putative isoforms construction method, to produce probability estimates.
An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs, Nucleic Acids Research, 2006, Accepted
Yi Xing*, Tianwei Yu*, Yingnian Wu, Meenakshi Roy, Joseph Kim and Christopher Lee
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 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 framework for splice graph-based probabilistic reconstructions of full-length isoforms.
HLA-DMB alternative splicing:
Running EM on HLA-DMB:
RT-PCR of HLA_DMB:
