An expectation-maximization framework for comprehensive prediction of isoform-specific functions.
Bioinformatics
; 39(4)2023 04 03.
Article
em En
| MEDLINE
| ID: mdl-36929917
ABSTRACT
MOTIVATION Advances in RNA sequencing technologies have achieved an unprecedented accuracy in the quantification of mRNA isoforms, but our knowledge of isoform-specific functions has lagged behind. There is a need to understand the functional consequences of differential splicing, which could be supported by the generation of accurate and comprehensive isoform-specific gene ontology annotations. RESULTS:
We present isoform interpretation, a method that uses expectation-maximization to infer isoform-specific functions based on the relationship between sequence and functional isoform similarity. We predicted isoform-specific functional annotations for 85 617 isoforms of 17 900 protein-coding human genes spanning a range of 17 430 distinct gene ontology terms. Comparison with a gold-standard corpus of manually annotated human isoform functions showed that isoform interpretation significantly outperforms state-of-the-art competing methods. We provide experimental evidence that functionally related isoforms predicted by isoform interpretation show a higher degree of domain sharing and expression correlation than functionally related genes. We also show that isoform sequence similarity correlates better with inferred isoform function than with gene-level function. AVAILABILITY AND IMPLEMENTATION Source code, documentation, and resource files are freely available under a GNU3 license at https//github.com/TheJacksonLaboratory/isopretEM and https//zenodo.org/record/7594321.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Software
/
Motivação
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article