Single-patient molecular testing with nanostring ncounter data using a reference-based strategy for batch effect correction

Abstract

A major weakness in many high-throughput genomic studies is the lack of consideration of a clinical environment where one patient at a time must be evaluated. We examined generalizable and platform-specific sources of variation from NanoString gene expression data on both ovarian cancer and Hodgkin lymphoma patients. A reference-based strategy, applicable to single-patient molecular testing is proposed for batch effect correction. The proposed protocol improved performance in an established Hodgkin lymphoma classifier, reducing batch-to-batch misclassification while retaining accuracy and precision. We suggest this strategy may facilitate development of NanoString and similar molecular assays by accelerating prospective validation and clinical uptake of relevant diagnostics.