Description Usage Arguments Details Value Author(s) References Examples
This function implements the Wald test for performing DE according to three statistics: difference, ratio and logratio
1 |
out |
The fit of mixtNB |
statistic |
The statistic to be used: "diff" (difference, the default), "ratio" and "logratio" |
quiet |
Logical to indicate if the DE genes should be printed |
alpha |
the significance level to detect DE genes |
This function implements the Wald test for performing DE according to three statistics: difference, ratio and logratio. It returns the statistics, the p-values and the adjusted p-values according to the Benjamini and Hochberg (1995)
A list containing
stat |
The value of the Wald test |
pvalue |
nominal p-values for each gene |
pvalueadj |
adjusted p-values according to the Benjamini and Hochberg (1995) |
var |
estimated variances of the genes |
gname |
Positions of the filtered genes |
Elisabetta Bonafede, Cinzia Viroli
E. Bonafede, F. Picard, S. Robin and C. Viroli (2015), Modelling overdispersion heterogeneity in differential expression analysis using mixtures, under revision.
1 2 3 4 5 6 7 8 9 | lambda.de<-matrix(runif(100,0,250),100)
lambda.de=cbind(lambda.de,lambda.de/exp(rnorm(100,0.5,0.125)))
lambda<-rbind(lambda.de,matrix(runif(900,0,250),900,2))
a<-runif(1000,0.5,600)
cr<-rep(1:2,each=5)
y<-matrix(0,1000,10)
for (i in 1:1000) for (l in 1:10) y[i,l]<-rnbinom(1,mu=lambda[i,cr[l]],size=a[i])
fit=fit.mixtNB(y,cr,K=3)
DE.genes=wald.test(fit)
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