Transcriptome assembly and quantification from Ion Torrent RNA-Seq data

Serghei Mangul, Adrian Caciula, Sahar Al Seesi, Dumitru Brinza, Ion Mӑndoiu, Alex Zelikovsky
2014 BMC Genomics  
High throughput RNA sequencing (RNA-Seq) can generate whole transcriptome information at the single transcript level providing a powerful tool with multiple interrelated applications including transcriptome reconstruction and quantification. The sequences of novel transcripts can be reconstructed from deep RNA-Seq data, but this is computationally challenging due to sequencing errors, uneven coverage of expressed transcripts, and the need to distinguish between highly similar transcripts
more » ... d by alternative splicing. Another challenge in transcriptomic analysis comes from the ambiguities in mapping reads to transcripts. Results: We present MaLTA, a method for simultaneous transcriptome assembly and quantification from Ion Torrent RNA-Seq data. Our approach explores transcriptome structure and incorporates a maximum likelihood model into the assembly and quantification procedure. A new version of the IsoEM algorithm suitable for Ion Torrent RNA-Seq reads is used to accurately estimate transcript expression levels. The MaLTA-IsoEM tool is publicly available at: http://alan.cs.gsu.edu/NGS/?q=malta Conclusions: Experimental results on both synthetic and real datasets show that Ion Torrent RNA-Seq data can be successfully used for transcriptome analyses. Experimental results suggest increased transcriptome assembly and quantification accuracy of MaLTA-IsoEM solution compared to existing state-of-the-art approaches.
doi:10.1186/1471-2164-15-s5-s7 pmid:25082147 pmcid:PMC4120146 fatcat:2pqjoiiqafgylft7tskibudnjy