anovapin: One-factorial ANOVA assessing pin-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 pin-dependent bias for a single array

1	anovapin(obj,index)

`obj`	object of class “marrayRaw” or “marrayNorm”
`index`	index of array to be tested

The function anovapin performs a one-factorial ANOVA for objects of class “marrayRaw” or “marrayNorm”. The predictor variable is the pin index; the response variable is the logged fold-change M=(log2(Ch2)-log2(Ch1)). The null hypothesis is equal mean(M) of groups of spots printed by the same pin i.e. a spot's M does not dependent on the pin used from printing the spot. The model formula used is M ~ (pin.index - 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 pin index (based on the chosen ANOVA model.)

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

anova, summary.lm

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


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