Description Usage Arguments Details Value Examples
pipeDESeq2
Run a pipeline of DESeq2 (if installed)
functions for differential gene expression.
1 2 |
counts |
A count matrix |
info |
An experimental design matrix |
formula |
A character string that can be coerced to a formula. Specify if a contrast model is not desired. |
reduced |
If testType = "LRT", a character string that can be coerced to a formula that represents a sub model to formula. If multiple formulae are specified, the number of formulae must match that of the formula argument. All reduced formulae must be sub models of the respective formula. If testType = "Wald", ignored. |
testType |
The type of statistical test to run. Possible options are "Wald" (Default) or "LRT". The latter requires the user to specify all full (formula) and reduced models to test. |
geneIDs |
The names of genes. If NA, use row names from counts matrix |
verbose |
Logical, return progress updates? |
... |
additional arguments to pass to DESeq. |
This function runs the following pipeline:
1. DESeq's pipeline using the specified test
2. Extraction of results (from DESeq2::results)
3. Renaming of columns and combining results across tests
a list with 2 elements (if simple=TRUE) the statsistics generated from DESeq2::results
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Not run:
library(DESeq2)
data(kidney)
counts<-kidney$counts
counts<-counts[sample(1:nrow(counts),1000),]
info<-data.frame(rep=kidney$replic,
treatment=kidney$treatment)
stats<-pipeDESeq(counts=counts, info=info,
formula = " ~ treatment")
stats<-pipeLIMMA(counts=counts, info=info,
formula = " ~ treatment",
reduced= "~ 1",
testType = "LRT")
## End(Not run)
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