hello, ? my name is Eyal and i am new to R, cut and paste level. i have created a DGEList object - d?following case study 3.3.3. i ran the calcNormFactors(d). the output i need is a normalized table. ?> library(edgeR) > library(limma) > raw.data <- read.delim("myFile.txt") > names(raw.data) ?d <- raw.data[, 2:64] ?rownames(d) <- raw.data[, 1] ? i did not group, irrelevant for me ?d <- DGEList(counts = d) ?dim(d) ? result was [1] number... 3 ?> cpm.d <- cpm(d) > d <- d[ rowSums(cpm.d > 1) >=3, ] > d <- calcNormFactors(d) ? thx, ? Eyal

Hi Eyal, You might read the posting guide: http://www.bioconductor.org/help/mailing-list/posting-guide/ I don't really understand your question, but from your subject and your cryptic description, I think you've used the right function - cpm() - to get a normalized matrix. You might also consider using : cpm.d <- cpm(d, normalized.lib.sizes=TRUE) More description by typing: ?cpm Best, Mark On 04.10.2012, at 16:21, eyal avisar wrote: > hello, > > my name is Eyal and i am new to R, cut and paste level. > i have created a DGEList object - d following case study 3.3.3. > i ran the calcNormFactors(d). > the output i need is a normalized table. > > library(edgeR) >> library(limma) >> raw.data <- read.delim("myFile.txt") >> names(raw.data) > d <- raw.data[, 2:64] > rownames(d) <- raw.data[, 1] > > i did not group, irrelevant for me > d <- DGEList(counts = d) > dim(d) > > result was [1] number... 3 > > cpm.d <- cpm(d) >> d <- d[ rowSums(cpm.d > 1) >=3, ] >> d <- calcNormFactors(d) > > thx, > > Eyal_______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor