1. Implications for Powering Biomarker Discovery Studies
Sian M. Dibben, Robert J. Holt, Timothy S. Davison, Claire L. Wilson, Janet Taylor, Ian Paul, Kieran McManus, Paul J. Kelly, Vitali Proutski, D. Paul Harkin, Peter Kerr, Dean A. Fennell, Jacqueline A. James, Richard D. Kennedy 
The Journal of Molecular Diagnostics 
Volume 14, Issue 2, Pages (March 2012)
DOI: /j.jmoldx
Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

2. Figure 1
Heterogeneity score distribution for squamous whole gene expression data. A: Sampling ranges for the median-based sampling. The yellow line is the median; red lines, 1, 2, and 3 SDs from the median. B: Sliding-scale sampling, where yellow lines represent 1, 2, and 3 SDs from 0.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

3. Figure 2
PCA of global gene expression showing the three primary sources of variation (principal components) within the data set. Component 1 (the major source of variation) is on the x axis, component 2 (the second most source of variation) is on the y axis, and component 3 is on the z axis. Different patients are identified by different colors. A: The whole data set, including all samples. B: The whole FFPE samples. C: The macrodissected samples. AD, adenocarcinoma; SQ, squamous.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

4. Figure 3
Sources of variation derived from the analysis of variance. Each factor is scaled in relation to experimental error: histological characteristic, squamous or adenocarcinoma; patient, between individual patients; sample type, whole FFPE section or macrodissected tumor; block, between different FFPE blocks of the same patient; and experimental error, the level of experimental error in the system is assumed to be one.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

5. Figure 4
Biomarker discovery and validation workflow. Use of a pilot study ensures the correct number of samples is used for biomarker discovery. Failure to perform a pilot study may result in increased cost (if too many samples are used) or a failure to identify/validate a biomarker (if too few samples are used). NPV, negative predictive value; PPV, positive predictive value.
The Journal of Molecular Diagnostics  , DOI: ( /j.jmoldx )
Copyright © 2012 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions