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Article

MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.

Genome biology - 13 Jan 2014

Mort Matthew, Sterne-Weiler Timothy, Li Biao, Ball Edward V, Cooper David N, Radivojac Predrag, Sanford Jeremy R, Mooney Sean D

Abstract excerpt

We have developed a novel machine-learning approach, MutPred Splice, for the identification of coding region substitutions that disrupt pre-mRNA splicing. Applying MutPred Splice to human disease-causing exonic mutations suggests that 16% of mutations causing inherited disease and 10 to 14% of somatic mutations in cancer may disrupt pre-mRNA splicing. For inherited disease, the main mechanism responsible for the...

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Identifiers

PMID: 24451234
DOI: 10.1186/gb-2014-15-1-r19
PMCID: PMC4054890

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