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PALMA: mRNA to Genome Alignments using Large Margin Algorithms

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84118

Hepp B, Ong,  CS
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84153

Rätsch,  G
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Schulze, U., Hepp B, Ong, C., & Rätsch, G. (2007). PALMA: mRNA to Genome Alignments using Large Margin Algorithms. Bioinformatics, 23(15), 1892-1900. doi:10.1093/bioinformatics/btm275.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-CDBD-6
Zusammenfassung
Motivation: Despite many years of research on how to properly align sequences in the presence of sequencing errors, alternative splicing and micro-exons, the correct alignment of mRNA sequences to genomic DNA is still a challenging task. Results: We present a novel approach based on large margin learning that combines accurate plice site predictions with common sequence alignment techniques. By solving a convex optimization problem, our algorithm – called PALMA – tunes the parameters of the model such that true alignments score higher than other alignments. We study the accuracy of alignments of mRNAs containing artificially generated micro-exons to genomic DNA. In a carefully designed experiment, we show that our algorithm accurately identifies the intron boundaries as well as boundaries of the optimal local alignment. It outperforms all other methods: for 5702 artificially shortened EST sequences from C. elegans and human it correctly identifies the intron boundaries in all except two cases. The best other method is a recently proposed method called exalin which misaligns 37 of the sequences. Our method also demonstrates robustness to mutations, insertions and deletions, retaining accuracy even at high noise levels. Availability: Datasets for training, evaluation and testing, additional results and a stand-alone alignment tool implemented in C++ and python are available at http://www.fml.mpg.de/raetsch/projects/palma.