Statistical evaluation of quality performance on genomic composite biomarker classifiers.
OBJECTIVE
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.


CONCLUSIONS
Three appropriate statistical methods were developed for evaluation of quality performance on differentially expressed genes, agreement and reproducibility of GCBCs.
Liu
Jen-Pei
JP
Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, Taipei, and Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan, Taiwan. jpliu@ntu.edu.tw
Lu
Li-Tien
LT
D014408:Biomarkers, Tumor; D020869:Gene Expression Profiling; D005819:Genetic Markers; D023281:Genomics; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics* / Q000628:therapy*; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D015203:Reproducibility of Results
D014408:Biomarkers, Tumor; D005819:Genetic Markers