Unknown

Dataset Information

0

Predicting RNA splicing from DNA sequence using Pangolin.


ABSTRACT: Recent progress in deep learning has greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues. Pangolin outperforms state-of-the-art methods for predicting RNA splicing on a variety of prediction tasks. Pangolin improves prediction of the impact of genetic variants on RNA splicing, including common, rare, and lineage-specific genetic variation. In addition, Pangolin identifies loss-of-function mutations with high accuracy and recall, particularly for mutations that are not missense or nonsense, demonstrating remarkable potential for identifying pathogenic variants.

SUBMITTER: Zeng T 

PROVIDER: S-EPMC9022248 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Predicting RNA splicing from DNA sequence using Pangolin.

Zeng Tony T   Li Yang I YI  

Genome biology 20220421 1


Recent progress in deep learning has greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues. Pangolin outperforms state-of-the-art methods for predicting RNA splicing on a variety of prediction tasks. Pangolin improves prediction of the impact of genetic variants on RNA splicing, including common, rare, and lineage-specific genetic variation. In addition, Pangolin identifies loss-of-f  ...[more]

Similar Datasets

| S-EPMC3322362 | biostudies-literature
| S-EPMC3287504 | biostudies-literature
| S-EPMC7800584 | biostudies-literature
| S-EPMC9271978 | biostudies-literature
| S-EPMC5490186 | biostudies-literature
| S-EPMC2217580 | biostudies-literature
| S-EPMC4232354 | biostudies-literature
| S-EPMC6054316 | biostudies-literature
| S-EPMC8776474 | biostudies-literature
| S-EPMC5739081 | biostudies-literature