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

This function assesses the significance of spatial bias. This is achieved by comparing the observed average values of logged fold-changes within a spot's spatial neighbourhood with an empirical distribution generated by permutation tests. The significance is given by (adjusted) p-values derived in one-sided permutation test.

1 | ```
p.spatial2(object,delta=2,N=-1,av="median",p.adjust.method="none")
``` |

`object` |
object of class marrayRaw or marrayNorm |

`delta` |
integer determining the size of spot neighbourhoods
( |

`N` |
number of samples for generation of empirical background distribution |

`av` |
averaging of |

`p.adjust.method` |
method for adjusting p-values due to multiple testing regime. The available
methods are “none”, “bonferroni”, “holm”, “hochberg”,
“hommel” and “fdr”. See also |

The function `p.spatial2.Rd`

is basically the same as `p.spatial`

,
but differs in its input and output formats. Details about the functionality can be found
at `p.spatial`

.

A list of a two lists of vectors is produced containing the p-values for positive (`Pp`

)
and negative (`Pn`

) deviations of
*median/mean of \code{M}* of the spot's neighbourhood is produced (see example below).

This function will be fused with `p.spatial`

in future versions using S4-style methods.

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

`fdr.int`

, `sigxy.plot`

, `p.adjust`

,`p.spatial`

1 2 3 4 5 6 7 8 9 10 11 12 | ```
# To run these examples, "un-comment" them!
#
# LOADING DATA
# data(sw)
#
# CALCULATION OF SIGNIFICANCE OF SPOT NEIGHBOURHOODS
# For this illustration, N was chosen rather small. For "real" analysis, it should be larger.
# P <- p.spatial2(sw,delta=2,N=10000,av="median")
# SIGNIFICANCE PLOTS OF ARRAY 1
# sigxy.plot2(sw[,1],P$Pp[[1]],P$Pn[[1]],color.lim=c(-5,5),main="P-value")
# SIGNIFICANCE PLOTS OF ARRAY 3
# sigxy.plot2(sw[,3],P$Pp[[3]],P$Pn[[3]],color.lim=c(-5,5),main="P-value")
``` |

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