I have a very noise RNAseq dataset with several covariates analyzed in edgeR.
design <- model.matrix(~0 + conditions + cov1 + cov2, data=pheno) d <- calcNormFactors(d, method ="TMM") d <- estimateDisp(d, design, robust=TRUE ) fit <- glmFit(d, design, dispersion=d$trended.dispersion, robust=TRUE) my.contrasts <- makeContrasts(....)
I was wondering if it is correct to extract the fitted values for visualization purposes to get rid of the noise.
norm <-cpm(fit$fitted.values, normalized.lib.sizes = TRUE, log = TRUE, prior.count = 1)
Is there any way to obtain only partial expression values related to conditions (proportion of explained variance) for downstream network analysis?
Thank you for your help.