As-quant: Detection and visualization of alternative splicing events with rna-seq data

Naima Ahmed Fahmi, Heba Nassereddeen, Jae Woong Chang, Meeyeon Park, Hsin Sung Yeh, Jiao Sun, Deliang Fan, Jeongsik Yong, Wei Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

(1) Background: A simplistic understanding of the central dogma falls short in correlating the number of genes in the genome to the number of proteins in the proteome. Post-transcriptional alternative splicing contributes to the complexity of the proteome and is critical in understanding gene expression. mRNA-sequencing (RNA-seq) has been widely used to study the transcriptome and provides opportunity to detect alternative splicing events among different biological conditions. Despite the popularity of studying transcriptome variants with RNA-seq, few efficient and user-friendly bioinformatics tools have been developed for the genome-wide detection and visualization of alternative splicing events. (2) Results: We propose AS-Quant, (Alternative Splicing Quantitation), a robust program to identify alternative splicing events from RNA-seq data. We then extended AS-Quant to visualize the splicing events with short-read coverage plots along with complete gene annotation. The tool works in three major steps: (i) calculate the read coverage of the potential spliced exons and the corresponding gene; (ii) categorize the events into five different categories according to the annotation, and assess the significance of the events between two biological condi-tions; (iii) generate the short reads coverage plot for user specified splicing events. Our extensive experiments on simulated and real datasets demonstrate that AS-Quant outperforms the other three widely used baselines, SUPPA2, rMATS, and diffSplice for detecting alternative splicing events. Moreover, the significant alternative splicing events identified by AS-Quant between two biological contexts were validated by RT-PCR experiment. (3) Availability: AS-Quant is implemented in Python 3.0. Source code and a comprehensive user’s manual are freely available online.

Original languageEnglish (US)
Article number4468
JournalInternational journal of molecular sciences
Volume22
Issue number9
DOIs
StatePublished - May 1 2021

Bibliographical note

Funding Information:
Funding: The research works are supported by grant from the National Science Foundation [IIS 1755761 and FET 1908495] and National Institutes of Health [2R01GM113952].

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Alternative splicing
  • RNA-seq
  • RT-PCR
  • Transcriptome
  • Visualization

PubMed: MeSH publication types

  • Journal Article

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