Hi Sally -- "Sally" <sagoldes at="" shaw.ca=""> writes: > I wrote a script for LIMMA about 9 months ago, which worked fine. > > Today ran it again (I've updated to the current R version) But got the following error message after this script: > > > adf<-new("AnnotatedDataFrame",data=phenotypicdata) > > Error in getClass(Class, where = topenv(parent.frame())) : "AnnotatedDataFrame" is not a defined class > This is unusual... > > The entire script is below. The offending script is in red. > > #Load libraries > source("http://bioconductor.org/biocLite.R") 'source' isn't needed here, but shouldn't cause problems. > library(limma) > library(Biobase) does library(Biobase) evaluate correctly, or is there an error here that you didn't notice? Can you be more specific about your software, by providing the output of sessionInfo() at this point in your script? Also, after the error occurs, what does traceback() say? It might also be a useful trouble-shooting effort to follow the instructions for updating packages at http://bioconductor.org/docs/install/ Martin > #change directory to folder where files are (c:/limmadegenes) > #Change to directory with original data files > #read in expression data file and phenotypic data. > #Note that row.names=1 means that row names are #in column 1, > exprdata<-read.table("exprsData.txt", header=TRUE,sep="\t",row.names=1,as.is=TRUE,fill=TRUE,) > class(exprdata) > dim(exprdata) > colnames(exprdata) > head(exprdata) > #printout too long to paste > phenotypicdata<-read.table("phenotypicdata.txt",row.names=1,header=T RUE,sep="\t") > class(phenotypicdata) > #returns: [1] "data.frame" > dim(phenotypicdata) > #returns: [1] 28 2 > colnames(phenotypicdata) > #returns: [1] "Species" "Time" > rownames(phenotypicdata) > #Coerse exprdata into a matrix > myexprdata<-as.matrix(exprdata) > class(myexprdata) > #[1] "matrix" > rownames(myexprdata) > colnames(myexprdata) > #Coerse phenotypicdata into a data frame > myphenotypicdata<-as.data.frame(phenotypicdata) > rownames(myphenotypicdata) > colnames(myphenotypicdata) > #[1] "species" "time" > summary(myphenotypicdata) > all(rownames(myphenotypicdata)==colnames(myexprdata)) > #[1] TRUE > #Create annotated Data Frame > adf<-new("AnnotatedDataFrame",data=phenotypicdata) > #dim means: dimension of an object. > dim(adf) > #rowNames columnNames > # 28 2 > rownames(adf) > #NULL > #Create eset object > eset<-new("ExpressionSet",exprs=myexprdata,phenoData=adf) > #Read in targets file > targets <- readTargets("targets.txt") > targets > # Set up character list defining your arrays, include replicates > TS <- paste(targets$Species, targets$Time, sep=".") > #This script returns the following: > TS > # Turn TS into a factor variable which facilitates fitting > TS <- factor(TS) > #This script returns the following > design <- model.matrix(~0+TS) > #write design object to text file > write.table(design,file="design.txt",sep="\t",col.names=NA) > colnames(design) <- levels(TS) > #for eset put in your M values - see ?lmFit for object types > fit <- lmFit(eset, design) > #contrast matrix > cont.matrix<-makeContrasts(s24vss0=s.24-s.0, s48vss24=s.48-s.24, s96vss48=s.96-s.48, c24vsc0=c.24-c.0, c48vsc24=c.48-c.24, c96vsc48=c.96-c.48, c0vss0=c.0-s.0, c24vss24=c.24-s.24, c48vss48=c.48-s.48, c96vss96=c.96-s.96, levels=design) > write.table(cont.matrix,file="cont.matrix.txt",sep="\t",col.names=NA) > #estimate the contrasts and put in fit2 > fit2 <- contrasts.fit(fit, cont.matrix) > fit2 <- eBayes(fit2) > s24vss0<-topTable(fit2,coef="s24vss0",number=400,adjust.method="BH", p.value=1) > > write.table(s24vss0,file="s24vss0.txt",sep="\t") > > > s48vss24<-topTable(fit2,coef="s48vss24",number=400,adjust.method="BH ",p.value=1) > > write.table(s48vss24,file="s48vss24.txt",sep="\t") > > > s96vss48<-topTable(fit2,coef="s96vss48",number=400,adjust.method="BH ",p.value=1) > > write.table(s96vss48,file="s96vss48.txt",sep="\t") > > > c24vsc0<-topTable(fit2,coef="c24vsc0",number=400,adjust.method="BH", p.value=1) > > write.table(c24vsc0,file="c24vsc0.txt",sep="\t") > > > c48vsc24<-topTable(fit2,coef="c48vsc24",number=400,adjust.method="BH ",p.value=1) > > write.table(c48vsc24,file="c24vsc48.txt",sep="\t") > > > c96vsc48<-topTable(fit2,coef="c96vsc48",number=400,adjust.method="BH ",p.value=1) > > write.table(c96vsc48,file="c96vsc48.txt",sep="\t") > > > c0vss0<-topTable(fit2,coef="c0vss0",number=400,adjust.method="BH",p. value=1) > > write.table(c0vss0,file="c0vss0.txt",sep="\t") > > > c24vss24<-topTable(fit2,coef="c24vss24",number=400,adjust.method="BH ",p.value=1) > > write.table(c24vss24,file="c24vss24.txt",sep="\t") > > > c48vss48<-topTable(fit2,coef="c48vss48",number=400,adjust.method="BH ",p.value=1) > > write.table(c48vss48,file="c48vss48.txt",sep="\t") > > > c96vss96<-topTable(fit2,coef="c96vss96",number=400,adjust.method="BH ",p.value=1) > > write.table(c96vss96,file="c96vss96.txt",sep="\t") > > > > > > Thank-you > > Sally > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Martin Morgan Computational Biology / Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109 Location: Arnold Building M2 B169 Phone: (206) 667-2793