detectSB {MANOR} | R Documentation

## Spatial bias detection

### Description

This function detects spatial bias on array CGH.

### Usage

    ## S3 method for class 'arrayCGH':
    detectSB(arrayCGH, variable, proportionup=0.25,
    proportiondown,type="up", thresholdup=0.2, thresholddown=0.2, ... )

### Arguments

`arrayCGH` | Object of `arrayCGH`.
`variable` | Variable used to compare the mean of zones detected by `nem`
`proportionup` | Maximal proportion of the array which may be affected by spatial bias with high values.
`proportiondown` | Maximal proportion of the array which may be affected by spatial bias with low values.
`type` | Type of spatial bias detected. Specify either "up" (to detect spatial bias with high values), or "down" (to detect spatial bias with low values) or "upanddown" (to detect both type of spatial bias).
`thresholdup` | Threshold used to detect spatial bias with high values.
`thresholddown` | Threshold used to detect spatial bias with low values.
`...` |

### Details

You must run the `arrayTrend` and `nem` function before detecting spatial bias: the `arrayTrend` computes a spatial trend and the `nem` function performs a classification with spatial constraints defining different zones on the array. Based on those results, spatial bias is detected.

### Value

An object of class `arrayCGH` with the following added information in the data.frame attribute `arrayValues`:

`SB` | Spots located in zone of spatial bias are coded either by 1 (if they correspond to a spatial bias with high values) or by -1 (if they correspond to a spatial bias with low values). Otherwise they are coded by 0.

### Note

People interested in tools for array-CGH analysis can visit our web-page: http://bioinfo.curie.fr.

### Author(s)

Philippe Hupé, Philippe.Hupe@.curie.fr.

### References

P. Neuvial, P. Hupé, I. Brito, S. Liva, E. Manié, C. Brennetot, A. Aurias, F. Radvanyi, and E. Barillot. Spatial normalization of array-CGH data. BMC Bioinformatics, 7(1):264. May 2006.

### See Also

`arrayTrend`, `nem`

### Examples

    data(spatial)  ## arrays with local spatial effects

    ## Plot of LogRatio measured on the array CGH
    arrayPlot(edge,"LogRatio", main="Log2-Ratio measured on the array
    CGH", zlim=c(-1,1), bar="v", mediancenter=TRUE)

    ## Spatial trend of the scaled log-ratios (the variable "ScaledLogRatio"
    ## equals to the log-ratio minus the median value of the corresponding
    ## chromosome arm)

    edgeTrend <- arrayTrend(edge, variable="ScaledLogRatio",
    span=0.03, degree=1, iterations=3, family="symmetric")
    arrayPlot(edgeTrend, variable="Trend", main="Spatial trend of the
    array CGH", bar="v")

    ## Not run:
    ## Classification with spatial constraint of the spatial trend
    edgeNem <- nem(edgeTrend, variable="Trend")
    arrayPlot(edgeNem, variable="ZoneNem", main="Spatial zones identified
    by nem", bar="v")

    # Detection of spatial bias
    edgeDet <- detectSB(edgeNem, variable="LogRatio", proportionup=0.25,type="up", thresholdup=0.15)
    arrayPlot(edgeDet, variable="SB", main="Zone of spatial bias in red", bar="v")

    # CGH profile
    plot(LogRatio ~ PosOrder, data=edgeDet$arrayValues,
    col=c("black","red")[as.factor(SB)], pch=20, main="CGH profile: spots
    located in spatial bias are in red")
    ## End(Not run)

[Package MANOR version 1.16.0 Index]