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Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
Published on: May 9, 2017
IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels
Yu Peng1, Henry C M Leung, Siu-Ming Yiu
1Department of Computer Science, The University of Hong Kong, Hong Kong, China.
Bioinformatics (Oxford, England)
|July 2, 2013
Summary
This study introduces IDBA-Tran, a novel tool for de novo transcriptome assembly. IDBA-Tran effectively identifies low-expressed isoforms by using a probabilistic approach to remove erroneous data, improving RNA sequencing analysis.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Next-generation sequencing (NGS) enables transcriptome analysis.
- De novo transcriptome assembly is challenging due to uneven isoform expression levels.
- Distinguishing low-expressed isoforms from erroneous data in de Bruijn graphs is difficult.
Purpose of the Study:
- To develop a method for accurate de novo transcriptome assembly.
- To improve the identification of low-expressed isoforms.
- To enhance the sensitivity and specificity of transcriptome assemblers.
Main Methods:
- Utilized a probabilistic progressive approach for de Bruijn graph error correction.
- Employed local thresholds for iterative removal of erroneous vertices/edges.
- Decomposed graphs into single- or few-gene components.
Main Results:
- Successfully retained correct vertices/edges for low-expressed isoforms.
- IDBA-Tran assembled both high- and low-expressed transcripts.
- Outperformed existing assemblers in sensitivity and specificity on simulated and real data.
Conclusions:
- IDBA-Tran offers improved de novo transcriptome assembly.
- The probabilistic approach effectively handles uneven expression levels.
- This method enhances the analysis of transcriptomes from RNA sequencing data.
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