Question: limma - different parametrization and weights
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gravatar for Hans-Ulrich Klein
11.1 years ago by
United States
Hans-Ulrich Klein330 wrote:
Dear All, I used limma with two different parametrizations. Both approaches should be equivalent in my opinion. However, if I use weights, the results differ. (Results of both approaches are equal without weights.) I attached an example below. Does someone know the reason for this? Regards, Hans-Ulrich Here is the example: library("limma") n=30 m=100 data = matrix(rnorm(n*m, mean=8, sd=1), ncol=n, nrow=m) W = matrix(rbinom(n*m, 1, p=0.8), ncol=n, nrow=m) W[W==0] = 1/2 disease = factor(c(rep("D1", n/3), rep("D2", n/3), rep("D3", n/3))) batch = factor(sample(c("B1", "B2"), n, replace=TRUE)) D1 = model.matrix(~ disease + batch) D2 = model.matrix(~ 0 + disease + batch) fit1 = lmFit(data, D1, weights=W) fit2 = lmFit(data, D2, weights=W) contrs = makeContrasts(contrasts= c("diseaseD2-diseaseD1", "diseaseD3-diseaseD1"), levels=D2) fit2c = contrasts.fit(fit2, contrs) eFit1 = eBayes(fit1) eFit2 = eBayes(fit2c) topTable(eFit1, coef="diseaseD2") logFC AveExpr t P.Value adj.P.Val B 71 1.0992458 8.414207 2.547634 0.01148965 0.6240313 -4.461615 79 1.0701491 8.306736 2.412824 0.01660306 0.6240313 -4.482316 65 0.9004096 7.956182 2.061818 0.04033472 0.6240313 -4.515367 73 0.8769716 7.822919 2.014672 0.04508839 0.6240313 -4.519390 97 -0.8838333 8.059430 -1.969606 0.05006854 0.6240313 -4.526330 28 -0.9103940 8.163924 -2.000665 0.04658917 0.6240313 -4.527588 92 -0.8426017 7.948664 -1.885870 0.06055682 0.6240313 -4.530451 78 0.8518031 7.921508 1.928056 0.05506380 0.6240313 -4.531817 96 -0.8062308 8.137124 -1.833017 0.06807629 0.6240313 -4.542318 76 0.7613192 8.176955 1.771061 0.07785820 0.6240313 -4.543365 topTable(eFit2, coef="diseaseD2-diseaseD1") logFC AveExpr t P.Value adj.P.Val B 71 1.0992458 8.414207 2.525839 0.01220672 0.6062981 -4.466368 79 1.0701491 8.306736 2.344510 0.01989314 0.6062981 -4.495402 28 -0.9103940 8.163924 -2.104442 0.03641183 0.6062981 -4.510339 65 0.9004096 7.956182 2.083941 0.03825580 0.6062981 -4.511464 73 0.8769716 7.822919 2.003999 0.04622820 0.6062981 -4.521191 78 0.8518031 7.921508 1.993785 0.04734180 0.6062981 -4.521311 92 -0.8426017 7.948664 -1.905554 0.05793940 0.6062981 -4.527255 97 -0.8838333 8.059430 -1.942207 0.05331756 0.6062981 -4.530611 45 0.7744936 7.745213 1.769790 0.07807041 0.6062981 -4.544968 8 -0.7040262 7.806587 -1.693483 0.09170026 0.6062981 -4.547372 sessionInfo() R version 2.8.0 (2008-10-20) x86_64-pc-linux-gnu locale: C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] limma_2.16.2 -- Hans-Ulrich Klein Department of Medical Informatics and Biomathematics University of M?nster, Germany Tel.: +49 (0)251 83-58405
limma • 361 views
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