Data processing |
Data was normalised within arrays using loess normalisation, and between arrays with quantile normalisation in limma. DE was analyzed in limma with: design<-cbind(array=c(0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1), citr=c(0,0,0,-1,0,0,0,0,0,0,0,0,0,-1,0,0), citr_bi=c(0,0,0,0,0,-1,0,0,0,0,0,-1,0,0,0,0), mut=c(0,0,0,0,-1,0,0,0,0,0,-1,0,0,0,0,0), mut_bi=c(0,0,0,0,0,0,-1,0,0,0,0,0,-1,0,0,0), sms=c(0,0,0,0,0,0,0,-1,0,-1,0,0,0,0,0,0), sms_bi=c(0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,-1), wt=c(0,0,-1,0,0,0,0,0,-1,0,0,0,0,0,0,0), wt_bi=c(-1,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0)) contrast.matrix<-cbind(mu_wt=c(0,0,0,1,0,0,0,-1,0), citr_wt=c(0,1,0,0,0,0,0,-1,0), sms_wt=c(0,0,0,0,0,1,0,-1,0), mu_bi_wt_bi=c(0,0,0,0,1,0,0,0,-1), citr_bi_wt_bi=c(0,0,1,0,0,0,0,0,-1), sms_bi_wt_bi=c(0,0,0,0,0,0,1,0,-1), wt_bi_wt=c(0,0,0,0,0,0,0,-1,1), mu_bi_mu=c(0,0,0,-1,1,0,0,0,0), citr_bi_citr=c(0,-1,1,0,0,0,0,0,0), sms_bi_sms=c(0,0,0,0,0,-1,1,0,0), sms_citr=c(0,-1,0,0,0,1,0,0,0), sms_citr_bi=c(0,0,-1,0,0,0,1,0,0), citr_mu=c(0,1,0,-1,0,0,0,0,0), citr_mu_bi=c(0,0,1,0,-1,0,0,0,0), sms_mu=c(0,0,0,-1,0,1,0,0,0), sms_mu_bi=c(0,0,0,0,-1,0,1,0,0))
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