Abstract 4867: Comparative analysis of RNA sequencing methods for characterization of cancer transcriptomics
Authors: Ryan P. Abo, Ling Lin, Samuel S. Hunter, Deniz N. Dolcen, Rachel R. Paquette, Angelica Laing, Luc de Waal, Aaron R. Thorner, Matthew D. Ducar, Liuda Ziaugra, William C. Hahn, Matthew L. Meyerson, Laura E. MacConaill, Paul Van Hummelen
Journal: Cancer Research (2015)

Abstract RNA sequencing (RNASeq) provides the ability to comprehensively assay the transcriptome in a high-throughput manner. Current there are a variety of library preparation methodologies for measuring and sequencing the transcriptome depending on (a) the sample source and (b) outcomes of interest. Beyond protocol selection, the requisite computational tools and resources are significant considerations in processing, analyzing and reporting the experimental results. While there are many resources readily available to effectively perform RNA-seq experiments, optimal protocols and analysis tools for the cancer domain remain to be developed. We have developed and characterized a set of protocols and analysis procedures that comprise an RNA-seq pipeline that can effectively be used in a cancer research setting. The analysis pipeline consists of a sequence of functions and tools to process and clean the raw data, generate quality control and summary metrics, and perform secondary analyses that include expression quantification, fusion detection and somatic mutation calling. We applied this pipeline to three different RNAseq strategies (whole-transcriptome, exome, and targeted RNA-seq) and performed an in-depth comparative analysis to investigate the implications of the choice of strategy on the downstream analysis and results. More specifically, we investigated the impact of library preparation methods on the dynamic range and expression profiles, variant calling and fusion detection. While the data indicated that capture-based protocols provided efficient methods for sampling transcripts as compared to whole-transcriptome RNA-seq, there are considerations in its use, particularly for duplicate reads and uncaptured transcripts. We illustrate the implications of these issues on downstream analysis, such as somatic mutation and fusion calling and differential expression. In summary, we have described a RNA-seq analysis platform that provides a varied set of library preparations and analytical components for large-scale clinical or research transcriptomics. Our analysis has characterized the technical features of the different library preparations, providing a necessary understanding of the costs and benefits of each method and the potential effects on the downstream analyses. Citation Format: Ryan P. Abo, Ling Lin, Samuel S. Hunter, Deniz N. Dolcen, Rachel R. Paquette, Angelica Laing, Luc de Waal, Aaron R. Thorner, Matthew D. Ducar, Liuda Ziaugra, William C. Hahn, Matthew L. Meyerson, Laura E. MacConaill, Paul Van Hummelen. Comparative analysis of RNA sequencing methods for characterization of cancer transcriptomics. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4867. doi:10.1158/1538-7445.AM2015-4867