AStrap: identification of alternative splicing from transcript sequences without a reference genome
| Autor: | Guoli Ji, Moliang Chen, Xiaohui Wu, Yaru Su, Wenbin Ye, Guangzao Huang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
Sequence analysis Computational biology Biology Biochemistry Genome Machine Learning Transcriptome 03 medical and health sciences Humans Molecular Biology 030304 developmental biology 0303 health sciences Sequence Analysis RNA 030302 biochemistry & molecular biology Amborella trichopoda Alternative splicing Robustness (evolution) Computer Science Applications Alternative Splicing Computational Mathematics Computational Theory and Mathematics Proteome Reference genome |
| Zdroj: | Bioinformatics. 35:2654-2656 |
| ISSN: | 1460-2059 1367-4803 |
| Popis: | Summary Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. Availability and implementation AStrap is available for download at https://github.com/BMILAB/AStrap. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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