Improving the flexibility of RNA-Seq data analysis pipelines

• Published in: IEEE International Workshop on Genomic Signal Processing and Statistics (Print) Vol. 2012; pp. 70 - 73
• Main Authors: Phan, J. H., Po-Yen Wu, Wang, M. D.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.12.2012
• Subjects: data analysis pipeline; gene expression; Next-generation sequencing; RNA-seq; spliced mapping
• ISBN: 9781467352345; 1467352349
• ISSN: 2150-3001; 2150-301X
• DOI: 10.1109/GENSIPS.2012.6507729

Accurate quantification of gene or isoform expression with RNA-Seq depends on complete knowledge of the transcriptome. Because a complete genomic annotation does not yet exist, novel isoform discovery is an important component of the RNA-Seq quantification process. Thus, a typical RNA-Seq pipeline includes a transcriptome mapping step to quantify known genes and isoforms, and a reference genome mapping step to discover new genes and isoforms. Several tools implement this approach, but are limited in that they force the use of a single mapping algorithm at both the transcriptome and reference genome mapping stages. The choice of mapping algorithm could affect quantification accuracy on a per-dataset basis. Thus, we describe a method that enables the merging of transcriptome and reference genome mapping stages provided that they conform to the standard SAM/BAM format. This procedure could potentially improve the accuracy of gene or isoform quantification by increasing flexibility when selecting RNA-Seq data analysis pipelines. We demonstrate an example of a flexible RNA-Seq pipeline, assess its potential for novel isoform discovery and validate its quantification performance using qRT-PCR.