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Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio
Sarah A Munro1, Steven P Lund2, P Scott Pine1
11] National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, USA [2] Department of Bioengineering, Stanford University, 443 Via Ortega, Stanford, California 94305, USA.
Nature Communications
|September 26, 2014
Summary
Standardized metrics for genome-scale differential gene expression experiments are needed. A new dashboard of metrics using spike-in controls shows consistent performance across labs, revealing process-specific biases.
Area of Science:
- Genomics
- Molecular Biology
- Biostatistics
Background:
- Standardized methods are crucial for assessing and comparing technical performance in genome-scale differential gene expression studies.
- Current approaches lack uniformity, hindering reproducibility and inter-laboratory comparisons.
Purpose of the Study:
- To develop and validate a standard dashboard of metrics for evaluating the technical performance of differential gene expression experiments.
- To assess the consistency and comparability of performance metrics across different laboratories and measurement processes.
Main Methods:
- Utilized external spike-in RNA control ratio mixtures with defined abundance ratios.
- Developed a suite of performance metrics including diagnostic performance, limit of detection of ratio (LODR), expression ratio variability, and measurement bias.
- Conducted an inter-laboratory study involving 12 laboratories and three distinct measurement processes.
Main Results:
- The proposed metrics dashboard effectively assesses technical performance.
- Eleven out of twelve laboratories showed consistent diagnostic power.
- Ratio measurement variability and bias were comparable within the same measurement processes across laboratories.
- Distinct biases were observed between measurement processes employing different mRNA-enrichment protocols.
Conclusions:
- The developed metrics provide a standardized approach for assessing gene expression experiment performance.
- The inter-laboratory study demonstrates the feasibility and utility of the proposed dashboard for evaluating technical consistency.
- Identifying process-specific biases, such as those related to mRNA enrichment, is critical for improving experimental accuracy and comparability.
