Table 1 

Statistical measures of batch effects and performance evaluation of normalization and batch correction 

Dataset 
Statistical measure 
Raw β 
QNβ 
Lumi 
ABnorm 
QNβ+ EB 
Lumi+ EB 
ABnorm+ EB 


Number (%) of CpGs associated with batch at p < 0.01 
17,458 (66) 
6,466 (24.4) 
8,478 (32) 
6,926 (26) 
12 
25 
23 

2 
PCs associated with batch(% variance explained)* 
1 (51.6) 
1 (17.9) 
1 (22.1) 
1 (18.9) 
None 
None 
None 
Number (%) of differentially methylated CpGs between case and control at p < 0.01 
345 (1.3) 
759 (2.9) 
714 (2.7) 
763 (2.9) 
1,155 (4.2) 
1,146 (4.3) 
1,229 (4.6) 



Number (%) of CpGs associated with batch at p < 0.01 
13,881 (50.0) 
10,300 (37.3) 
12,668 (46) 
9,694 (35.2) 
2 
6 
8 

3 
PCs associated with batch (% variance explained) 
1 (50.4) 
1 (24.8) 
1 (30.6) 
1 (23.8) 
None 
None 
None 
Number (%) of differentially methylated CpGs between cancer and normal at p < 0.01 
794 (2.9) 
1,877 (6.8) 
1,131 (4.1) 
1,635 (5.9) 
2,799 (10.1) 
2,400 (8.7) 
2,289 (8.3) 



Raw β: Raw average β without any correction; QNβ: quantile normalization at average β values; lumi: two step quantile normalization at probe signals implemented in R package "lumi"; ABnorm: quantile normalization for A and B signal separately; EB: Empirical Bayes batch correction. * The principal components (PC) significantly associated with batch effects at p value < 0.01 from the top 10 evaluated by Wilcoxon test and the percentage of variance the PC explains. 

Sun et al. BMC Medical Genomics 2011 4:84 doi:10.1186/17558794484 