View source: R/runing_functions.R
Run.DESeq2 | R Documentation |
Prepare and Run DESeq
Run.DESeq2(
expr.data,
sample.data,
formula,
test,
fitType,
sfType,
betaPrior,
reduced,
minReplicatesForReplace,
modelMatrixType,
useT,
minmu
)
expr.data |
expression matrix |
sample.data |
sample infomation meta data |
formula |
experiment design formula |
test |
either "Wald" or "LRT", which will then use either Wald significance tests (defined by nbinomWaldTest), or the likelihood ratio test on the difference in deviance between a full and reduced model formula (defined by nbinomLRT) |
fitType |
either "parametric", "local", or "mean" for the type of fitting of dispersions to the mean intensity. |
sfType |
either "ratio", "poscounts", or "iterate" for teh type of size factor estimation. |
betaPrior |
whether or not to put a zero-mean normal prior on the non-intercept coefficients |
reduced |
for test="LRT", a reduced formula to compare against |
minReplicatesForReplace |
the minimum number of replicates required in order to use replaceOutliers on a sample. |
modelMatrixType |
either "standard" or "expanded", which describe how the model matrix, X of the GLM formula is formed. |
useT |
logical, passed to nbinomWaldTest, default is FALSE, where Wald statistics are assumed to follow a standard Normal |
minmu |
lower bound on the estimated count for fitting genewise dispersion and for use with nbinomWaldTest and nbinomLRT |
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