Transcriptome Data Analysis

Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, Baohong Zhang

Sequencing of transcribed RNA molecules (RNA-Seq) has been used wildly for studying cell transcriptomes in bulk or at the single-cell level (Wang et al., Nat Rev Genet, 10:57-63, 2009; Ozsolak and Milos, Nat Rev Genet, 12:87-98, 2011; Sandberg, Nat Methods, 11:22-24, 2014) and is becoming the de facto technology for investigating gene expression level changes in various biological conditions, on the time course, and under drug treatments. Furthermore, RNA-Seq data helped identify fusion genes that are related to certain cancers (Maher et al., Nature, 458:97-101, 2009). Differential gene expression before and after drug treatments provides insights to mechanism of action, pharmacodynamics of the drugs, and safety concerns (Dixit et al., Genomics, 107:178-188, 2016). Because each RNA-Seq run generates tens to hundreds of millions of short reads with size ranging from 50 to 200 bp, a tool that deciphers these short reads to an integrated and digestible analysis report is in high demand. QuickRNASeq (Zhao et al., BMC Genomics, 17:39-53, 2016) is an application for large-scale RNA-Seq data analysis and real-time interactive visualization of complex data sets. This application automates the use of several of the best open-source tools to efficiently generate user friendly, easy to share, and ready to publish report. Figures in this protocol illustrate some of the interactive plots produced by QuickRNASeq. The visualization features of the application have been further improved since its first publication in early 2016. The original QuickRNASeq publication (Zhao et al., BMC Genomics, 17:39-53, 2016) provided details of background, software selection, and implementation. Here, we outline the steps required to implement QuickRNASeq in user's own environment, as well as demonstrate some basic yet powerful utilities of the advanced interactive visualization modules in the report.