nbinomLRT: Likelihood ratio test (chi-squared test) for GLMs

In aghozlane/DESeq2shaman: Differential gene expression analysis based on the negative binomial distribution

Description

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.

Usage

nbinomLRT(object, full = design(object), reduced, betaPrior = FALSE,
  betaPriorVar, modelMatrixType = "standard", maxit = 100,
  useOptim = TRUE, quiet = FALSE, useQR = TRUE)

Arguments

object	a DESeqDataSet
full	the full model formula, this should be the formula in design(object). alternatively, can be a matrix
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
betaPrior	whether or not to put a zero-mean normal prior on the non-intercept coefficients 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 nbinomWaldTest.
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 DESeq, is formed. "standard" is as created by model.matrix using the design formula. "expanded" includes an indicator variable for each level of factors in addition to an intercept, in order to ensure that the log2 fold changes are independent of the choice of base level. betaPrior must be set to TRUE in order for expanded model matrices to be fit.
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

Details

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.

Value

a DESeqDataSet with new results columns accessible with the results function. The coefficients and standard errors are reported on a log2 scale.

See Also

DESeq, nbinomWaldTest

Examples

dds <- makeExampleDESeqDataSet()
dds <- estimateSizeFactors(dds)
dds <- estimateDispersions(dds)
dds <- nbinomLRT(dds, reduced = ~ 1)
res <- results(dds)

aghozlane/DESeq2shaman documentation built on Nov. 1, 2019, 9:01 p.m.