rowaov {LMGene} | R Documentation |
Computes the mean squares and degrees of freedom for gene-by-gene ANOVAs.
rowaov(eS, model=NULL)
eS |
An |
model |
Model used for comparison. See details and |
If you have data in a matrix
and information about experimental design factors, then you
can use neweS
to convert the data into an ExpressionSet
object. Please see
neweS
for more detail.
The model
argument is an optional character string, constructed like the right-hand
side of a formula for lm
. It specifies which of the variables in the ExpressionSet
will
be used in the model and whether interaction terms will be included. If model=NULL
,
it uses all variables from the ExpressionSet
without interactions. Be careful of using
interaction terms with factors; this often leads to overfitting, which will yield an error.
resmat |
A matrix of MSEs and degrees of freedom for all model factors and all genes. The first rows of |
David Rocke and Geun-Cheol Lee
David M. Rocke (2004), Design and analysis of experiments with high throughput biological assay data, Seminars in Cell & Developmental Biology, 15, 703–713.
library(Biobase) library(LMGene) #data data(sample.mat) data(vlist) raw.eS <- neweS(sample.mat, vlist) # glog transform data trans.eS <- transeS(raw.eS, lambda = 727, alpha = 56) # Perform gene-by-gene anova resmat <- rowaov(trans.eS) resmat[,1:3]