Hello, I am interested in applying my edgeR results to a modulated modularity clustering algorithm to explore community structure in the significantly differentially expressed genes. Is there a straightforward way to calculate Pearson or deviance residual values from the glmLRT results? Thank you. Cheers, Laura [[alternative HTML version deleted]]

Dear Laura, edgeR does not automatically provide residuals, but it does provide information from which you can compute them yourself fairly easily. To get Pearson residuals: fit <- glmFit(y, design) y <- fit$counts mu <- fit$fitted.values phi <- fit$dispersion v <- mu*(1+phi*mu) resid.pearson <- (y-mu) / sqrt(v) To get deviances residuals you will need the devel version of edgeR: d <- nbinomUnitDeviance(y,mu,phi) resid.deviance <- sign(y-mu) * sqrt(d) Better than either of these however is the midp-quantile residual: resid.quantile <- zscoreNBinom(y,mu,size=1/phi) To read about quantile residuals: http://www.statsci.org/smyth/pubs/residual.html Best wishes Gordon > Date: Sat, 8 Feb 2014 16:53:27 -0500 > From: Laura Eierman <lee27 at="" cornell.edu=""> > To: bioconductor at r-project.org > Subject: [BioC] edgeR glmLRT pearson residual > > Hello, > I am interested in applying my edgeR results to a modulated modularity > clustering algorithm to explore community structure in the significantly > differentially expressed genes. > > Is there a straightforward way to calculate Pearson or deviance residual > values from the glmLRT results? > > Thank you. > Cheers, Laura ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}