BMC Genomics 2008, 9:230 http://www.biomedcentral.com/1471-2164/9/230 TFihgruesrheo3ld dependent analysis Threshold dependent analysis. Each circle represents the accuracy (ACC in the first row), sensitivity (Sn in the second row) or specificity (Sp in the third row) for each array using the optimal LR thresholds that maximized the accuracy values. Actual optimal threshold values are given in a supplementary table [see Additional file 1]. Labels in the x axis identify the hybridization: RT – R6 (test) with TIGR4 control, GT – G54 with TIGR4 control, RM – R6 with mix control and GM - G54 with mix control. In the left column, values were obtained analyzing together all the spots in the array. In the right column, val- ues were obtained analyzing separately two classes of spots according to the expected control signal and excluding the TRG set of spots, as detailed in the methods section. This exclusion precludes the direct comparison of the numeric values between the left and right column. However, the removed TRG spots are expected to have similar quality performances with both types of control and should mainly increase true present call, which has a positive impact on sensitivity and accuracy values. separately. Although the advantages of performing an analysis by spot classes were not formally explored, a few previous studies using multistrain arrays with a single strain control have opted for defining two thresholds for spots present or absent in the control [9] or running the analysis algorithm twice, inverting the LR values [8]. Since there is no universal consensus on analyzing all spots together or splitting them into classes according to the expected signal in the control channel, we compared control performances in each of these situations. For both of these approaches the use of mix control led to better results, measured by increased discriminatory power of LR Page 6 of 11 (page number not for citation purposes)