Bertrand
2014-Dec-03 10:58 UTC
[R] Question on LIMMA analysis with covariates and some missing data
Hello, I have a dataset of asthma patients for which white blood cells gene expression was measured with one-color Affymetrix microarrays (N~500, asthma is a factor with 4 levels: control, moderate, severe, severe & smokers). I also have an extensive clinical dataset related, but with many missing values (for example, our controls don't have asthma exacerbations counts). Our goal is to find DEGs between asthma groups, but we suspect that some of those clinical variables have an influence on gene expression, so we want to treat those as covariates in the model. Now the question: can LIMMA handle missing data in the covariates and produce accurately corrected p-values for the genes ? The model matrix is constructed like so (example with age and sex as covariates): # Microarray data is in 'data' variable asthma<-factor("Control", "Moderate", "Severe", "SevereSmokers") design<-model.matrix(~0 + asthma + age + sex) contrast.matrix<-makeContrasts(Control-Moderate, Control-Severe, Control-SevereSmokers, levels=design) fit<-lmFit(data, design) fit2<-contrasts.fit(fit, contrast.matrix) fit2<-eBayes(fit2) Many thanks, Bertrand -- EISBM logo <http://www.eisbm.org> *Bertrand De Meulder Researcher * European Institute for Systems Biology and Medicine Campus Charles M?rieux - Universit? de Lyon CNRS - UCBL - ENS *E-mail:*bdemeulder at eisbm.org <mailto:bdemeulder at eisbm.org> *Office:* +33(0)4 37 28 74 41 *Office* Universit? Claude Bernard 3^e ?tage plot 2 50 Avenue Tony Garnier 69366 Lyon cedex 07 France *Laboratory* LyonBioP?le - Centre d'Infectiologie 2^e ?tage B?t. Domilyon 321 Avenue Jean Jaur?s 69007 Lyon France Follow us : EISBM eisbm.org <http://www.eisbm.org> | Facebook Facebook <http://www.facebook.com/EISBM> | Twitter Twitter <http://twitter.com/EISBM_EU>