anovaint: One-factorial ANOVA assessing intensity-dependent bias
In OLIN: Optimized local intensity-dependent normalisation of two-color microarrays

Description Usage Arguments Details Value Author(s) See Also Examples

This function performs an one-factorial analysis of variance assessing intensity-dependent 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.

1	anovaint(obj,index,N=10)

`obj`	object of class “marrayRaw” or “marrayNorm”
`index`	index of array to be tested
`N`	number of (intensity) levels for ANOVA

The function anovaint performs a one-factorial ANOVA for objects of class “marrayRaw” or “marrayNorm”. The predictor variable is the average logged intensity of both channels A=0.5*(log2(Ch1)+log2(Ch2)). 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 A-scale is divided in N intervals generating N levels of factor A. Note that N should divide the total number of spots approx. equally. The null hypothesis is the equality of mean(M) of the different levels (intervals). The model formula used is M ~ (A - 1) (without an intercept term).

The return value is a list of summary statistics of the fitted model as produced by summary.lm. For example, the squared multiple correlation coefficient R-square equals the proportion of the variation of M that can be explained by the variation of A (based on the chosen ANOVA model.)

Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)

anova, summary.lm, anovaspatial, marrayRaw, marrayNorm

# CHECK RAW DATA FOR INTENSITY-DEPENDENT BIAS
data(sw)
print(anovaint(sw,index=1,N=10))


# CHECK  DATA NORMALISED BY OLIN FOR INTENSITY-DEPENDENT BIAS
data(sw.olin)
print(anovaint(sw.olin,index=1,N=10))