Dear Anyone- can you help me I'm trying to use limma to do a time course analysis using affymetrix data, I'm new to R so I guess I'm doing something really silly so I'm sorry if I'm being stupid. I've tried searching the archive and I'm no wiser. Also sorry about the length of this posting, I wanted to try and cover everything I've tried. I've installed R version 2.0.1 and used the Packages option to install the Affy and Limma packages, can I just say that's really easy!, very nice pdf file help to :-) I started by using the affy package to read in my cel files from the directory I set Data<- ReadAffy() And for speeds sake am first trying the rma option to normalize Eset <-rma(Data) Which gives me > eset Expression Set (exprSet) with 22810 genes 24 samples phenoData object with 1 variables and 26 cases varLabels sample: arbitrary numbering I've also loaded a Targets file as below FileName Target 30MIN_SHOOT_REP1 30MIN_SHOOT_REP1.CEL con0.5hr 30MIN_SHOOT_REP2 30MIN_SHOOT_REP2.CEL con0.5hr Etc with different times and a treatment set, a set of replicates per sample. Obviously, I was being a bit ambitious, I used the info given on page 35 of the limma manual to try and analyze my time course data as per the example > lev<- c("con0.5hr", "con1hr","con3hr", "con6hr", "con12hr", "con24hr", + "tre0.5hr", "tre1hr", "tre3hr", "tre6hr", "tre12hr", "tre24hr") which gives me > lev [1] "con0.5hr" "con1hr" "con3hr" "con6hr" "con12hr" "con24hr" [7] "tre0.5hr" "tre1hr" "tre3hr" "tre6hr" "tre12hr" "tre24hr" then > f <- factor(targets$Target, levels=lev) > f [1] con0.5hr con0.5hr con1hr con1hr con3hr con3hr con6hr con6hr [9] con12hr con12hr con24hr con24hr tre0.5hr tre0.5hr tre1hr tre1hr [17] tre3hr tre3hr tre6hr tre6hr tre12hr tre12hr tre24hr tre24hr 12 Levels: con0.5hr con1hr con3hr con6hr con12hr con24hr tre0.5hr ... tre24hr then design the model matrix design <- model.matrix(~0+f) > design fcon0.5hr fcon1hr fcon3hr fcon6hr fcon12hr fcon24hr ftre0.5hr ftre1hr 1 1 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 3 0 1 0 0 0 0 0 0 4 0 1 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 6 0 0 1 0 0 0 0 0 7 0 0 0 1 0 0 0 0 8 0 0 0 1 0 0 0 0 9 0 0 0 0 1 0 0 0 10 0 0 0 0 1 0 0 0 11 0 0 0 0 0 1 0 0 12 0 0 0 0 0 1 0 0 13 0 0 0 0 0 0 1 0 14 0 0 0 0 0 0 1 0 15 0 0 0 0 0 0 0 1 16 0 0 0 0 0 0 0 1 17 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 ftre3hr ftre6hr ftre12hr ftre24hr 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 4 0 0 0 0 5 0 0 0 0 6 0 0 0 0 7 0 0 0 0 8 0 0 0 0 9 0 0 0 0 10 0 0 0 0 11 0 0 0 0 12 0 0 0 0 13 0 0 0 0 14 0 0 0 0 15 0 0 0 0 16 0 0 0 0 17 1 0 0 0 18 1 0 0 0 19 0 1 0 0 20 0 1 0 0 21 0 0 1 0 22 0 0 1 0 23 0 0 0 1 24 0 0 0 1 attr(,"assign") [1] 1 1 1 1 1 1 1 1 1 1 1 1 attr(,"contrasts") attr(,"contrasts")$f [1] "contr.treatment" Then > colnames(design)<-lev > colnames(design) [1] "con0.5hr" "con1hr" "con3hr" "con6hr" "con12hr" "con24hr" [7] "tre0.5hr" "tre1hr" "tre3hr" "tre6hr" "tre12hr" "tre24hr" But when I do lmFit I get > fit <-lmFit(eset,design) Error in lm.fit(design, t(M)) : incompatible dimensions So I tested if my expression set is a data.frame as I think it is supposed to be > is.data.frame(eset) [1] FALSE So then I tried importing my pre-normalized values into a data table using data<-read.csv("mydata.csv", header = TRUE, sep = ',') > is.data.frame(data) [1] TRUE and is formatted as following (the header names being as the targets file, shortened here to fit on screen) X 30MINREP1 30MINREP2 1 244901_at 6.34848 6.128339 etc for miles! But I get the same lmfit error as before? <-lmFit(data,design) Error in lm.fit(design, t(M)) : incompatible dimensions Can anyone give me any help, I guess I'm missing something basic, I think I have a different problem with the eset and the imported data file but am really stuck. Many thanks in advance for any help anyone can give me Sara Rollinson Dr Sara Rollinson, Academic Unit of Oncology and Haematology, Algernon Firth Building, Great George Street, University of Leeds, Leeds, Ls2 9JT. [[alternative HTML version deleted]]