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Table 2 Highest and lowest correlation among spot intensities between technical replicates in a 2D gel experiment; highest and lowest Kappa coefficients between technical replicates

From: The case for well-conducted experiments to validate statistical protocols for 2D gels: different pre-processing = different lists of significant proteins

Sample No of Replicates Highest Correlation Coefficient (R-sq%) Lowest Correlation Coefficient (R-sq%) Highest Kappa 95% CI Lowest Kappa 95% CI
6 (GSE) 3 0.774 (60%) 0.547 (30%) 0.4962 (-0.1039,1.000) 0.1476 (-0.1374,0.4326)
7 (GSE) 4 0.907 (82%) 0.589 (35%) 0.4437 (0.1004,0.7870) -0.0767 (-0.114,-0.0350)
8 (GSE) 4 0.932 (87%) 0.617 (38%) 0.4445 (0.1027,0.7864) 0.0099 (-0.0855,0.1052)
9 (GSE) 2 0.747 (56%) 0.747 (56%) 0.1299 (-0.1384,0.3982) 0.1299 (-0.1384,0.3982)
10 (GSE) 2 0.837 (70%) 0.837 (70%) 0.1231 (-0.0486,0.2948) 0.1231 (-0.0486,0.2948)
22 (CONT) 4 0.805 (65%) 0.467 (22%) 0.6538 (0.3705, 0.9372) 0.2599 (-0.0566,0.5765)
23 (CONT) 4 0.845 (71%) 0.632 (40%) 0.3269 (0.0304,0.6235) 0.0322 (-0.0296,0.0941)
24 (CONT) 2 0.711 (50%) 0.711 (50%) 0.0743 (-0.1284,0.2770) 0.0743 (-0.1284,0.2770)
25 (CONT) 3 0.837 (70%) 0.524 (27%) 0.2843 (0.0073,0.5613) 0.2384 (-0.0629,0.5397)
26 (CONT) 2 0.578 (33%) 0.578 (33%) 0.1946 (0.0531,0.3361) 0.1946 (0.0531,0.3361)
  1. The Pearson correlation coefficient is a measure of the linear relationship between two variables. R square, the square of Pearson's correlation is a measure of how much variability in one variable is explained by the variability in the other. Since technical replicates are expected to be identical, the r-squares are expected to be very high, at least 0.95. The table demonstrates the degree of variability between technical replicates after normalization. The Kappa coefficients with the 95% confidence intervals confirm the same thing. Ten out of sixteen confidence intervals span zero, indicating no agreement between technical replicates of the same sample in those cases.