I have a few queries regarding Agilent data processing by Limma package.
1) I tried to test the use-case describe in Limma package vignette " Time Course Eects of Corn Oil on Rat Thymus with Agilent 4x44K Arrays". I downloaded the same data as named in the package. I tried the following code
SDRF <- read.delim("EGEOD-33005.sdrf.txt",check.names=FALSE,stringsAsFactors=FALSE) x <- read.maimages(SDRF[,"Array Data File"],source="agilent",green.only=TRUE) y <- backgroundCorrect(x,method="normexp") neg95 <- apply(y$E[y$genes$ControlType==-1,],2,function(x) quantile(x,p=0.95)) cutoff <- matrix(1.1*neg95,nrow(y),ncol(y),byrow=TRUE) isexpr <- rowSums(y$E > cutoff) >= 4 y0 <- y[y$genes$ControlType==0 & isexpr,] Treatment <- SDRF[,"Characteristics[treatment]"] levels <- c("10 ml/kg saline","2 ml/kg corn oil","5 ml/kg corn oil","10 ml/kg corn oil") Treatment <- factor(Treatment,levels=levels) design <- model.matrix(~Treatment)
and works fine.
But when i run the following line, gives an error.
fit <- lmFit(y0,design) Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), : 'data' must be of a vector type, was 'NULL'.
And how to get the fold-change and p-value of the individual study in case of differential expression.
2) If i am not interested to perform the differential expression of the Agilent data, can i pass the individual text data file without targets(SDRF) file and after preprocessing get the probe name, expression value and p-value of an individual study.