Format

Send to

Choose Destination
Bioinformatics. 2018 Jan 1;34(1):56-63. doi: 10.1093/bioinformatics/btx557.

SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data.

Author information

1
Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
2
Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA.
3
Department of Oncology and Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, USA.

Abstract

Motivation:

Recent advances in high-throughput RNA sequencing (RNA-seq) technologies have made it possible to reconstruct the full transcriptome of various types of cells. It is important to accurately assemble transcripts or identify isoforms for an improved understanding of molecular mechanisms in biological systems.

Results:

We have developed a novel Bayesian method, SparseIso, to reliably identify spliced isoforms from RNA-seq data. A spike-and-slab prior is incorporated into the Bayesian model to enforce the sparsity for isoform identification, effectively alleviating the problem of overfitting. A Gibbs sampling procedure is further developed to simultaneously identify and quantify transcripts from RNA-seq data. With the sampling approach, SparseIso estimates the joint distribution of all candidate transcripts, resulting in a significantly improved performance in detecting lowly expressed transcripts and multiple expressed isoforms of genes. Both simulation study and real data analysis have demonstrated that the proposed SparseIso method significantly outperforms existing methods for improved transcript assembly and isoform identification.

Availability and implementation:

The SparseIso package is available at http://github.com/henryxushi/SparseIso.

Contact:

xuan@vt.edu.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28968634
PMCID:
PMC5870564
[Available on 2019-01-01]
DOI:
10.1093/bioinformatics/btx557
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center