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

Description

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.

Usage

 `1` ```anovaspatial(obj,index,xN=5,yN=5,visu=FALSE) ```

Arguments

 `obj` object of class “marrayRaw” or “marrayNorm” `index` index of array (within `obj`) to be tested `xN` number of intervals in x-direction `yN` number of intervals in y-direction `visu` If visu=TRUE, results are visualised (see below)

Details

The function `anovaspatial` 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 spot locations on the array is divided into `xN` intervals 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 `xN` and `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).

Value

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 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.

Author(s)

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

`anova`, `summary.lm`, `anovaint`, `marrayRaw`, `marrayNorm`
 ```1 2 3 4 5 6 7 8 9``` ```# CHECK RAW DATA FOR SPATIAL BIAS data(sw) print(anovaspatial(sw,index=1,xN=8,yN=8,visu=TRUE)) # CHECK DATA NORMALISED BY OLIN FOR SPATIAL BIAS data(sw.olin) print(anovaspatial(sw.olin,index=1,xN=8,yN=8,visu=TRUE)) # note the different scale of the colour bar ```