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

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.

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

`obj` |
object of class “marrayRaw” or “marrayNorm” |

`index` |
index of array (within |

`xN` |
number of intervals in x-direction |

`yN` |
number of intervals in y-direction |

`visu` |
If visu=TRUE, results are visualised (see below) |

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).

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.

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 |

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