detectSB {MANOR} | R Documentation |
This function detects spatial bias on array CGH.
detectSB.arrayCGH(arrayCGH, variable, proportionup=0.25, proportiondown,type="up", thresholdup=0.2, thresholddown=0.2, ... )
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. |
... |
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.
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. |
People interested in tools for array-CGH analysis can visit our web-page: http://bioinfo.curie.fr.
Philippe Hupé, Philippe.Hupe@.curie.fr.
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. In preparation.
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)