PIntron: a fast method for detecting the gene structure due to alternative splicing via maximal pairings of a pattern and a text

BMC Bioinformatics

Research

Ernesto Picardi¹  Graziano Pesole²  Paola Bonizzoni³  Raffaella Rizzi³  Yuri Pirola⁴  Gianluca Della Vedova⁵ 

[1] Dipartimento di Biochimica e Biologia Molecolare "E. Quagliariello", Univ. degli Studi di Bari, 70126, Bari, Italy;Dipartimento di Biochimica e Biologia Molecolare "E. Quagliariello", Univ. degli Studi di Bari, 70126, Bari, Italy;Istituto di Biomembrane e Bioenergetica, Consiglio Nazionale delle Ricerche, 70126, Bari, Italy;Dipartimento di Informatica Sistemistica e Comunicazione, Univ. degli Studi di Milano-Bicocca, 20126, Milano, Italy;Dipartimento di Informatica Sistemistica e Comunicazione, Univ. degli Studi di Milano-Bicocca, 20126, Milano, Italy;Centro Ricerche e Studi Agroalimentari, Parco Tecnologico Padano, 26900, Lodi, Italy;Dipartimento di Statistica, Univ. degli Studi di Milano-Bicocca, 20126, Milano, Italy;

关键词: Edit Distance;    Splice Junction;    Suffix Tree;    Embed Graph;    Transcript Cluster;   

DOI  :  10.1186/1471-2105-13-S5-S2

来源: Springer

【 摘 要 】

BackgroundA challenging issue in designing computational methods for predicting the gene structure into exons and introns from a cluster of transcript (EST, mRNA) sequences, is guaranteeing accuracy as well as efficiency in time and space, when large clusters of more than 20,000 ESTs and genes longer than 1 Mb are processed. Traditionally, the problem has been faced by combining different tools, not specifically designed for this task.ResultsWe propose a fast method based on ad hoc procedures for solving the problem. Our method combines two ideas: a novel algorithm of proved small time complexity for computing spliced alignments of a transcript against a genome, and an efficient algorithm that exploits the inherent redundancy of information in a cluster of transcripts to select, among all possible factorizations of EST sequences, those allowing to infer splice site junctions that are largely confirmed by the input data. The EST alignment procedure is based on the construction of maximal embeddings, that are sequences obtained from paths of a graph structure, called embedding graph, whose vertices are the maximal pairings of a genomic sequence T and an EST P. The procedure runs in time linear in the length of P and T and in the size of the output.The method was implemented into the PIntron package. PIntron requires as input a genomic sequence or region and a set of EST and/or mRNA sequences. Besides the prediction of the full-length transcript isoforms potentially expressed by the gene, the PIntron package includes a module for the CDS annotation of the predicted transcripts.ConclusionsPIntron, the software tool implementing our methodology, is available at http://www.algolab.eu/PIntron under GNU AGPL. PIntron has been shown to outperform state-of-the-art methods, and to quickly process some critical genes. At the same time, PIntron exhibits high accuracy (sensitivity and specificity) when benchmarked with ENCODE annotations.

【 授权许可】

Unknown   
© Pirola et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.