Description Usage Arguments Details Value See Also Examples
This function tests for significance of change in deviance between a
full and reduced model which are provided as formula
.
Fitting uses previously calculated sizeFactors
(or normalizationFactors
)
and dispersion estimates.
1 2 3 4 5 6 7 8 9 10 11 12 
object 
a DESeqDataSet 
full 
the full model formula, this should be the formula in

reduced 
a reduced formula to compare against, e.g. the full model with a term or terms of interest removed. alternatively, can be a matrix 
betaTol 
control parameter defining convergence 
maxit 
the maximum number of iterations to allow for convergence of the coefficient vector 
useOptim 
whether to use the native optim function on rows which do not converge within maxit 
quiet 
whether to print messages at each step 
useQR 
whether to use the QR decomposition on the design matrix X while fitting the GLM 
minmu 
lower bound on the estimated count while fitting the GLM 
type 
either "DESeq2" or "glmGamPoi". If 
The difference in deviance is compared to a chisquared distribution
with df = (reduced residual degrees of freedom  full residual degrees of freedom).
This function is comparable to the nbinomGLMTest
of the previous version of DESeq
and an alternative to the default nbinomWaldTest
.
a DESeqDataSet with new results columns accessible
with the results
function. The coefficients and standard errors are
reported on a log2 scale.
1 2 3 4 5  dds < makeExampleDESeqDataSet()
dds < estimateSizeFactors(dds)
dds < estimateDispersions(dds)
dds < nbinomLRT(dds, reduced = ~ 1)
res < results(dds)

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