BMC Bioinformatics

Table 1 AUC values for ROC curves

From: Extended analysis of benchmark datasets for Agilent two-color microarrays

			No BA			BA			FE
	Site	RNA	mean	t-statistic	SAM-statistic	mean	t-statistic	SAM-statistic	mean	t-statistic	SAM-statistic
Agilent Dataset	1	A	0.998	0.995	0.998	0.998	0.995	0.998	0.971	0.992	0.996
	1	B	0.998	0.994	0.998	0.998	0.994	0.998	0.901	0.995	0.998
	2	A	0.993	0.974	0.992	0.990	0.975	0.990	0.907	0.984	0.970
	2	B	0.995	0.993	0.996	0.992	0.994	0.996	0.810	0.996	0.995
	3	A	0.999	0.976	0.995	0.997	0.976	0.995	0.816	0.976	0.991
	3	B	0.997	0.991	0.997	0.997	0.992	0.997	0.760	0.983	0.840

AUC values for ROC curves summarizing the sensitivity and specificity of detection for the six datasets from sites 1,2,3 and RNAs A and B. A perfect AUC is 1.0. AUC over 0.99 bold; AUC under 0.95 underlined.

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ISSN: 1471-2105

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