nbinomGLMTest: Perform chi-squared tests comparing two sets of GLM fits
In DESeq: Differential gene expression analysis based on the negative binomial distribution
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
For each gene, the function calculates a chi-square p value by simply calculating:
1 - pchisq(resReduced$deviance - resFull$deviance, attr(resReduced,
"df.residual") - attr(resFull, "df.residual"))
Usage
1
nbinomGLMTest(resFull, resReduced)
Arguments
resFull, resReduced
GLM fit data frames, as returned by fitNbinomGLMs,
first the full, then the reduced model.
Value
a vector of p values
Author(s)
Simon Anders, anders@embl.de
See Also
Examples
1
2
3
4
5
6
cds <- makeExampleCountDataSet()[ 1:100, ]
cds <- estimateSizeFactors( cds )
cds <- estimateDispersions( cds, method="pooled" )
fit1 <- fitNbinomGLMs( cds, count ~ condition )
fit0 <- fitNbinomGLMs( cds, count ~ 1 )
nbinomGLMTest( fit1, fit0 )
DESeq documentation built on April 28, 2020, 6:37 p.m.
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Description Usage Arguments Value Author(s) See Also Examples
Description
For each gene, the function calculates a chi-square p value by simply calculating:
1 - pchisq(resReduced$deviance - resFull$deviance, attr(resReduced,
"df.residual") - attr(resFull, "df.residual"))
Usage
1 | nbinomGLMTest(resFull, resReduced)
|
Arguments
resFull, resReduced |
GLM fit data frames, as returned by |
Value
a vector of p values
Author(s)
Simon Anders, anders@embl.de
See Also
Examples
1 2 3 4 5 6 | cds <- makeExampleCountDataSet()[ 1:100, ]
cds <- estimateSizeFactors( cds )
cds <- estimateDispersions( cds, method="pooled" )
fit1 <- fitNbinomGLMs( cds, count ~ condition )
fit0 <- fitNbinomGLMs( cds, count ~ 1 )
nbinomGLMTest( fit1, fit0 )
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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