This function performs an one-factorial analysis of variance to test for spatial bias for a single array. The predictor variable is the average logged intensity of both channels and the response variable is the logged fold-change.
object of class “marrayRaw” or “marrayNorm”
index of array (within
number of intervals in x-direction
number of intervals in y-direction
If visu=TRUE, results are visualised (see below)
anovaspatial performs a one-factorial ANOVA for objects of class “marrayRaw” or
“marrayNorm”. The predictor variable is the average logged intensity of both channels
Ch1,Ch2 are the fluorescence intensities of channel 1
and channel 2, respectively. The response variable is the logged fold-change
M=(log2(Ch2)-log2(Ch1))). The spot locations on the array is divided into
in x-direction and
yN intervals in y-direction. This division defines (
xN x yN)
rectangular spatial blocks on
the array, and thus, (
xN x yN) levels (or treatments) for
A. Note that
values chosen for
yN should divide the array columns and rows approx. equally.
The null hypothesis is the equality of mean(
M) of the different levels.
The model formula used by
anovaspatial is M ~ (A - 1)
(without an intercept term).
The return value is a list of summary statistics of the fitted model as produced by
For example, the squared multiple correlation coefficient R-square equals the proportion
of the variation of
M that can be related to the spot location (based on the chosen
ANOVA.) Optionally, the distribution of p-values (as derived by t-test and stated in the summary statistics)
can be visualised.
Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)
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