Hi! I am "pure" biologist so I strictly follow the limma userguide commands in my analysis but I have a problem. I have a set of microarrays with a common control channel. I have 4 biological replicates of each experiment. If I perform the simplest possible analysis for the first treatment (wt.NaCl/wt.pool) using only files 043,046,048,077 as targets ("targetsA.txt"), I obtain different adjusted p.values (and different topTable) comparing to analysis with all twenty input files ("targetsB.txt") and extracting wt.NaCl contrast. Why? Which topTable is correct? Agnieszka Here are my targets files and the codes: TargetsA.txt SlideNumber Name FileName Cy3 Cy5 43 wt.Na1 043.gpr wt.pool wt.NaCl 46 wt.Na2 046.gpr wt.pool wt.NaCl 48 wt.Na3 048.gpr wt.pool wt.NaCl 77 wt.Na4 077.gpr wt.pool wt.NaCl TargetsB.txt SlideNumber Name FileName Cy3 Cy5 43 wt.Na1 043.gpr wt.pool wt.NaCl 46 wt.Na2 046.gpr wt.pool wt.NaCl 48 wt.Na3 048.gpr wt.pool wt.NaCl 77 wt.Na4 077.gpr wt.pool wt.NaCl 44 wt.Cd1 044.gpr wt.pool wt.CdCl2 47 wt.Cd2 047.gpr wt.pool wt.CdCl2 49 wt.Cd3 049.gpr wt.pool wt.CdCl2 78 wt.Cd4 078.gpr wt.pool wt.CdCl2 75 mu1.U1 075.gpr wt.pool mu1.U 70 mu1.U2 070.gpr wt.pool mu1.U 71 mu1.U3 071.gpr wt.pool mu1.U 80 mu1.U4 080.gpr wt.pool mu1.U 67 mu2.U1 067.gpr wt.pool mu2.U 74 mu2.U2 074.gpr wt.pool mu2.U 79 mu2.U3 079.gpr wt.pool mu2.U 68 mu2.U4 068.gpr wt.pool mu2.U 72 mu3.U1 072.gpr wt.pool mu3.U 73 mu3.U2 073.gpr wt.pool mu3.U 69 mu3.U3 069.gpr wt.pool mu3.U 88 mu3.U4 088.gpr wt.pool mu3.U > targetsA=readTargets("targetsA.txt") > RGA=read.maimages(targetsA,source="genepix",wt.fun=wtflags(weight=0, cutoff=-50)) Read 043.gpr Read 046.gpr Read 048.gpr Read 077.gpr > spottypes=readSpotTypes("SpotTypes.txt") > RG$genes$Status=controlStatus(spottypes,RGA) Matching patterns for: ID Name Found 31200 cDNA Found 48 no_change Setting attributes: values Color > RGAb=backgroundCorrect(RGA, method="normexp", offset=50) Green channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Red channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 > MAA=normalizeWithinArrays(RGAb) > fitA=lmFit(MAA) Warning message: In lmFit(MAA) : Some coefficients not estimable: coefficient interpretation may vary. > fitA=eBayes(fitA) > write.table(topTable(fitA, + number=100,adjust.method="BH",p.value=0.05,lfc=1,sort.by="P",resort.by ="logFC"),"topTableA.txt") > write.fit(fitA, digits=6,F.adjust="BH",file="resultsA.txt") --------------------------------- > targetsB=readTargets("targetsB.txt") > RGB=read.maimages(targetsB,source="genepix",wt.fun=wtflags(weight=0, cutoff=-50)) Read 043.gpr Read 046.gpr Read 048.gpr Read 077.gpr Read 044.gpr Read 047.gpr Read 049.gpr Read 078.gpr Read 075.gpr Read 070.gpr Read 071.gpr Read 080.gpr Read 067.gpr Read 074.gpr Read 079.gpr Read 068.gpr Read 072.gpr Read 073.gpr Read 069.gpr Read 088.gpr > spottypes=readSpotTypes("SpotTypes.txt") > RG$genes$Status=controlStatus(spottypes,RGB) Matching patterns for: ID Name Found 31200 cDNA Found 48 no_change Setting attributes: values Color > RGBb=backgroundCorrect(RGB, method="normexp", offset=50) Green channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Corrected array 5 Corrected array 6 Corrected array 7 Corrected array 8 Corrected array 9 Corrected array 10 Corrected array 11 Corrected array 12 Corrected array 13 Corrected array 14 Corrected array 15 Corrected array 16 Corrected array 17 Corrected array 18 Corrected array 19 Corrected array 20 Red channel Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Corrected array 5 Corrected array 6 Corrected array 7 Corrected array 8 Corrected array 9 Corrected array 10 Corrected array 11 Corrected array 12 Corrected array 13 Corrected array 14 Corrected array 15 Corrected array 16 Corrected array 17 Corrected array 18 Corrected array 19 Corrected array 20 > MAB=normalizeWithinArrays(RGBb) > designB=modelMatrix(targetsB,ref="wt.pool") Found unique target names: mu1.U mu2.U mu3.U wt.CdCl2 wt.NaCl wt.pool > designB mu1.U mu2.U mu3.U wt.CdCl2 wt.NaCl [1,] 0 0 0 0 1 [2,] 0 0 0 0 1 [3,] 0 0 0 0 1 [4,] 0 0 0 0 1 [5,] 0 0 0 1 0 [6,] 0 0 0 1 0 [7,] 0 0 0 1 0 [8,] 0 0 0 1 0 [9,] 1 0 0 0 0 [10,] 1 0 0 0 0 [11,] 1 0 0 0 0 [12,] 1 0 0 0 0 [13,] 0 1 0 0 0 [14,] 0 1 0 0 0 [15,] 0 1 0 0 0 [16,] 0 1 0 0 0 [17,] 0 0 1 0 0 [18,] 0 0 1 0 0 [19,] 0 0 1 0 0 [20,] 0 0 1 0 0 > fitB=lmFit(MAB,designB) Warning message: In lmFit(MAB, designB) : Some coefficients not estimable: coefficient interpretation may vary. > contrast.matrix=makeContrasts(wt.NaCl,levels=designB) > contrast.matrix Contrasts Levels wt.NaCl mu1.U 0 mu2.U 0 mu3.U 0 wt.CdCl2 0 wt.NaCl 1 > fitB=contrasts.fit(fitB,contrast.matrix) > fitB=eBayes(fitB) > write.table(topTable(fitB, + number=100,adjust.method="BH",p.value=0.05,lfc=1,sort.by="P",resort.by ="logFC"),"topTableB.txt") > write.fit(fitB, digits=6,F.adjust="BH",file="resultsB.txt") Dr Agnieszka ?mie?ko Centrum Doskonalosci CENAT Instytut Chemii Bioorganicznej Polskiej Akademii Nauk Noskowskiego 12/14 61-704 Pozna? tel. (61) 8528503 wew. 249 fax: (61) 8520532 Agnieszka Zmienko, Ph.D. CENAT Institute of Bioorganic Chemistry Polish Academy of Sciences Noskowskiego 12/14 61-704 Poznan, Poland phone (0048) 61-8528503 ext. 249 fax: (0048) 61-8520532