Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S28-S34, December 2008

Statistical Evaluation of Quality Performance on Genomic Composite Biomarker Classifiers

  • Jen-Pei Liu

      Affiliations

    • Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan
    • Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan, Taiwan
    • Corresponding Author InformationCorrespondence to: Dr Jen-Pei Liu, Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei, Taiwan
    • ,
  • Li-Tien Lu

      Affiliations

    • Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan

Received 30 July 2008; received in revised form 15 September 2008; accepted 19 September 2008.

Article Outline

Background/Purpose

After completion of the Human Genome Project, genomic composite biomarker classifiers (GCBCs) became available. However, quality performance of GCBCs varies. We propose statistical methods for evaluation of the quality performance of GCBCs on selection of differentially expressed genes, agreement and reproducibility.

Methods

For detection of differentially expressed genes, an interval hypothesis was employed to take into account both biological and statistical significance. The concordance correlation coefficient (CCC) was used to evaluate the agreement of expression levels of technical replicates. The intraclass correlation coefficient (ICC) was suggested to assess the reproducibility between laboratories.

Results

A two one-sided test procedure was proposed to test the interval hypothesis. Statistical methods based on the generalized pivotal quantities for CCC and ICC were suggested to test the hypotheses for agreement and reproducibility. Simulation results demonstrated that all three methods could adequately control the type I error rate at the nominal level for assessment of differentially expressed genes, agreement and reproducibility.

Conclusion

Three appropriate statistical methods were developed for evaluation of quality performance on differentially expressed genes, agreement and reproducibility of GCBCs.

Key Words:  agreement , differentially expressed genes , genomic composite biomarker classifier , reproducibility of results

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PII: S0929-6646(09)60006-1

doi:10.1016/S0929-6646(09)60006-1

Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S28-S34, December 2008

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