Hi Dan, my apologies for the slow reply. How many different PC3M samples were used? Only 1? So you want a single-column heatmap (with xxxx rows, 1 per spot?) Then just make a limma model then use makeContrasts(PC3M-Knockdown, design) then once you've done lmFit, you'll find the relative expression values in the "coefficients" part of myFitObject. Access it via myFitObject$coefficients Alternatively, if you want one heatmap column per PC3M you hybridized, you can calculate them by hand: +go to your MA object, and use the log2 relative expression levels from MA$M (you have one column per microarray). +To compare Knockdown against PC3M, - use array 1_2 data as is: MA$M[,2] - calculate Knockdown-PC3M a second time via arrays 1_3 and 3_4: MA$M[,10]+MA$M[,3] - calculate Knockdown-PC3M again via arrays 2_2 and 1_1: -MA$M[,1] -MA$M[,5] - and then again via arrays 3_1 and 3_2 heatmap(cbind(MA$M[,2], MA$M[,10]+MA$M[,3], -MA$M[,1] -MA$M[,5], ...)) Best, yannick On Nov 11, 2008, at 11:24 AM, Daniel Brewer wrote: > Hi, > > That sounds great. I am not sure exactly how you can do it and > whether > it is applicable to the experiment. Could you provide a simple > example? > > The experiment information is below and I am interested in the PC3M vs > knockdown comparison > > Targets file: > SlideNumber ArrayNumber FileName Name Cy3 Cy5 > 1 1 Input/1_1.txt 1_1 Scramble Knockdown > 1 2 Input/1_2.txt 1_2 Knockdown PC3M > 1 3 Input/1_3.txt 1_3 PNT2 PC3M > 1 4 Input/1_4.txt 1_4 Pooled PNT2 > 2 2 Input/2_2.txt 2_2 PC3M Scramble > 2 3 Input/2_3.txt 2_3 PNT2 Scramble > 3 1 Input/3_1.txt 3_1 PC3M Pooled > 3 2 Input/3_2.txt 3_2 Pooled Knockdown > 3 3 Input/3_3.txt 3_3 Scramble Pooled > 3 4 Input/3_4.txt 3_4 Knockdown PNT2 > > PC3M = the control cell line > Knockdown = PC3M with an siRNA knockdown vector > Scramble = PC3M with a vector with a scrambled sequence > PNT2 = Another cell line (not of interest here) > Pooled = poll of knockdowns before you get specific clone, > intermediate > between PCM3 and knockdown - a hetrogenious group (not considered > here) > >> design > Knockdown PNT2 Pooled Scramble > [1,] 1 0 0 -1 > [2,] -1 0 0 0 > [3,] 0 -1 0 0 > [4,] 0 1 -1 0 > [5,] 0 0 0 1 > [6,] 0 -1 0 1 > [7,] 0 0 1 0 > [8,] 1 0 -1 0 > [9,] 0 0 1 -1 > [10,] -1 1 0 0 > > Thanks Dan > > Yannick Wurm wrote: >> Hi Dan, >> >> for this kind of thing, I'll fit another limma model just to obtain >> estimates of what needs to be visualized... >> In one case, I needed to separately visualize expression levels from >> each biological replicate, but variability was such that I had >> grouped >> them together in my model. To estimate expression levels for each >> biological replicate, I recreated a targets file, separating each >> biological replicate by name. Then calculated a fit, and asked for >> contrasts between each sample and one RNA which I chose as reference. >> (centering expression levels within each gene afterwards works too) >> >> Despite a complex design it was thus possible to generate a heatmap >> where each of the 8 biological replicated RNAs from 3 different >> conditions where represented separately. >> >> hope this helps, >> >> yannick >> >> >> >> On Nov 10, 2008, at 17:33 , Daniel Brewer wrote: >> >>> Dear all, >>> >>> I am doing some work on a two-colour microarray (Agilent) >>> experiment and >>> I have used limma to do some differential analysis. The person I am >>> doing this work was keen to have a heatmap of the differentially >>> expressed genes expression levels. Unfortunately, the design is >>> rather >>> complex and random (closer to a loop design than a common >>> reference) so >>> its not possible to produce a traditional heatmap. I was >>> wondering if >>> anyone had any suggestions of a colourful way to show that the >>> expression of the two groups are different? >>> >>> In particular I was thinking that there must be estimates of the >>> expression and error in each group by the linear model, but couldn't >>> work out how to find these. >>> >>> Thanks >>> >>> Dan > > > > -- > ************************************************************** > > Daniel Brewer > > Institute of Cancer Research > Molecular Carcinogenesis > MUCRC > 15 Cotswold Road > Sutton, Surrey SM2 5NG > United Kingdom > > Tel: +44 (0) 20 8722 4109 > Fax: +44 (0) 20 8722 4141 > > Email: daniel.brewer at icr.ac.uk > > ************************************************************** > > The Institute of Cancer Research: Royal Cancer Hospital, a > charitable Company Limited by Guarantee, Registered in England under > Company No. 534147 with its Registered Office at 123 Old Brompton > Road, London SW7 3RP. > > This e-mail message is confidential and for use by the...{{dropped:13}}