| bet.coinertia {made4} | R Documentation |
Between class coinertia analysis. cia of 2 datasets where
covariance between groups or classes of cases, rather than individual cases are maximised.
bet.coinertia(df1, df2, fac1, fac2, cia.nf = 2, type = "nsc", ...)
df1 |
First dataset.A matrix, data.frame,
exprSet or marrayRaw.
If the input is gene expression data in a matrix or data.frame. The
rows and columns are expected to contain the variables (genes) and cases (array samples)
respectively.
|
df2 |
Second dataset. A matrix, data.frame,
exprSet or marrayRaw.
If the input is gene expression data in a matrix or data.frame. The
rows and columns are expected to contain the variables (genes) and cases (array samples)
respectively. |
fac1 |
A factor or vector which describes the classes in df1 |
fac2 |
A factor or vector which describes the classes in df2 |
cia.nf |
Integer indicating the number of coinertia analysis axes to be saved. Default value is 2. |
type |
A character string, accepted options are type="nsc" or type="pca" |
... |
further arguments passed to or from other methods |
A list of class bet.cia of length 5
coin |
An object of class 'coinertia', sub-class dudi. See
coinertia |
coa1, pca1 |
An object of class 'nsc' or 'pca', with sub-class
'dudi'. See dudi,
dudi.pca or dudi.nsc |
bet1 |
An object of class 'bga', with sub-class
'dudi'. See dudi,
bga or between |
bet2 |
An object of class 'bga', with sub-class
'dudi'. See dudi,
bga or between. |
This is very computational intensive. The authors of ade4 are currently re-writing the code for coinertia analysis, so that it should substantially improve the computational requirements (May 2004).
Aedin Culhane
Culhane AC, et al., 2003 Cross platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics. 4:59
### NEED TO DO
if (require(ade4, quiet = TRUE)) {}