nbinomLRT {DESeq2} | R Documentation |
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.
nbinomLRT(object, full = design(object), reduced, betaPrior = FALSE, betaPriorVar, modelMatrixType, maxit = 100, useOptim = TRUE, quiet = FALSE, useQR = TRUE, betaPriorUpperQuantile = 0.05)
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 |
betaPrior |
whether or not to put a zero-mean normal
prior on the non-intercept coefficients (Tikhonov/ridge
regularization). While the beta prior is used typically,
for the Wald test, it can also be specified for the
likelihood ratio test. For more details on the
calculation, see |
betaPriorVar |
a vector with length equal to the number of model terms including the intercept. which if missing is estimated from the rows which do not have any zeros |
modelMatrixType |
either "standard" or "expanded",
which describe how the model matrix, X of the formula in
|
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 |
betaPriorUpperQuantile |
only used when betaPrior=TRUE, which is not the default. the upper quantile to use for calculating the variance of the beta prior. by default the 0.05 upper quantile of the absolute value of the MLE betas is matched to the 0.025 upper quantile of a zero-centered normal. |
The difference in deviance is compared to a chi-squared
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.
dds <- makeExampleDESeqDataSet() dds <- estimateSizeFactors(dds) dds <- estimateDispersions(dds) dds <- nbinomLRT(dds, reduced = ~ 1) res <- results(dds)