TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data

• Main Authors: Jae Hyun Lim, Soo Youn Lee, Ju Han Kim
• Format: Article
• Language: English
• Published: Korea Genome Organization 2017-03-01
• Series: Genomics & Informatics
• Subjects: base sequence; gene expression profiling; molecular sequence data; programming languages; sequence analysis/RNA; software
• Online Access: http://genominfo.org/upload/pdf/gni-15-51.pdf

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.