title: Improving the Flexibility of RNA-Seq Data Analysis Pipelines.
abstract: 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 by assessing its potential for novel isoform discovery and by validating its quantification performance using qRT-PCR.
authors.affiliation: Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, jhphan@gatech.edu.
authors.forename: John H
authors.initials: JH
authors.lastname: Phan
authors.affiliation: Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA, leoboki@gmail.com.
authors.forename: Po-Yen
authors.initials: PY
authors.lastname: Wu
authors.affiliation: Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, aywang@bme.gatech.edu.
authors.forename: May D
authors.initials: MD
authors.lastname: Wang