anovaspatial {OLIN} R Documentation

## One-factorial ANOVA assessing spatial bias

### 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

`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`

### Examples

```# 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

```

[Package OLIN version 1.3.2 Index]