(663.6) Easy NanoString Gene Expression Analysis with the NanoTube

Poster Board Number: A264

Caleb Class (Butler University), Christopher Bristow (MD Anderson Cancer Center), Kim-Anh Do (MD Anderson Cancer Center)

The NanoString nCounter analysis system has become a popular platform for the quantification of RNA expression, and numerous statistical and bioinformatic methods have been developed to analyze the resulting data. However, many of the current methods and tools are unavailable to those without expert knowledge in computer programming. We have developed the NanoTube R package to make this analysis easier for anyone with basic R skills, as well as a simple web application (developed using R-Shiny) for those with no programming skills. This includes all of the steps required in nCounter data analysis, from data processing and quality control to differential expression, gene set analysis, and data visualization.  In addition to manufacturer-recommended data analysis steps, functions for interoperability with other R packages for NanoString data are provided for those who prefer different analysis methods. And because this library is open-source, it can be expanded by others with additional analysis and visualization needs.

We demonstrate the software by applying it to a publically available data set comparing the gene expression of patients with autoimmune retinopathy against healthy controls (GEO data series GSE117751). In addition to confirming the enrichment of multiple immune pathways identified in the previous analysis of the data, the EGFR signaling pathway is identified as a potential pathway of interest in autoimmune retinopathy patients.  Use of this software will help researchers understand their gene expression data more quickly, and can also allow for the rapid reanalysis of public NanoString data sets to uncover new biological discoveries. The NanoTube R package and user’s guide are available on the Bioconductor software repository (https://www.bioconductor.org/packages/devel/bioc/html/NanoTube.html), while the beta version of the web application can be downloaded from GitHub (https://github.com/calebclass/Shiny-NanoTube).