Assessing Technical Performance in Differential Gene Expression Experiments with External Spike-in RNA Control Ratio Mixtures

TL;DR

This paper introduces a standardized set of metrics using external spike-in RNA controls to evaluate and compare the technical performance of differential gene expression experiments across laboratories.

Contribution

It proposes a comprehensive dashboard of metrics for assessing technical performance, including diagnostic power, detection limits, and bias, applicable across different experimental setups.

Findings

Metrics showed consistent diagnostic power across laboratories.

Measurement variability was comparable within the same process.

Different biases were observed with different mRNA enrichment protocols.

Abstract

There is a critical need for standard approaches to assess, report, and compare the technical performance of genome-scale differential gene expression experiments. We 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 amongst 12 laboratories with three different measurement processes demonstrated generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias were also comparable amongst laboratories for the same measurement process. Different biases were observed for measurement processes using different mRNA enrichment protocols.