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. 2009 Dec;104(488):1318-1323.
doi: 10.1198/jasa.2009.ap09575.

Rejoinder

Robert B Scharpf  1 , Håkon Tjelmeland, Giovanni Parmigiani, Andrew B Nobel
Affiliations

Rejoinder

Robert B Scharpf et al. J Am Stat Assoc. 2009 Dec.
No abstract available

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Figures

Figure 1
Figure 1
Scatterplots of expression measurements for two genes in the four breast cancer studies that show the “on/off” characteristic described by Dettling, Gabrielson, and Parmigiani (2005). ER-positive samples are denoted by the plotting symbol “x.” The ER-positive samples tend to be more prevalent when both genes are turned on in the Farmer and Huang studies. In contrast, the ER-negative phenotype of Farmer and Huang depends on the which of the two genes is overexpressed.
Figure 2
Figure 2
(a) Scatterplot of posterior mean for concordant differential expression for m = 1 (horizontal axis) versus m = 3 (vertical axis). The points to the right of the vertical lines represent a = 0.95 versus m = 3. There is but a small difference in selecting 1, 2, or 3 studies as concordantly differentially expressed; the Farmer, Hedenfalk, and Sorlie studies show great similarity. The genes have a much lower posterior probability of concordant expression in all four studies, because the genes differentially expressed in the Huang study are largely independent of the remaining studies.
Figure 3
Figure 3
Scatterplots of the estimates of Bayesian effect size for the four breast cancer studies. Darker plotting symbols highlight genes with a posterior mean of concordant differential expression >0.95. Panels (a) and (b) differ in terms of the stringency of the definition of concordance. In (a), we require that the gene be differentially expressed in at least one study (m = 1) and that the direction of differential expression be the same in all studies for which the gene is differentially expressed. In contrast, in (b), we require that the gene be differentially expressed and the direction be the same in all studies (m = 4). Increasing the stringency of the definition of concordance at a fixed threshold for the posterior mean tends to select genes with larger estimates of the Bayesian effect size.
See this image and copyright information in PMC

References

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