There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here, an international team led by researchers at the NIST assess technical performance with a proposed standard ‘dashboard’ of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. The researchers observe different biases for measurement processes using different mRNA-enrichment protocols.
Availability – The erccdashboard R package is freely available on Bioconductor: http://bioconductor.jp/packages/3.0/bioc/html/erccdashboard.html