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1 # clusterPlot
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2 # dendrogram of sample clustering
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3
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4 # input : counts, outputName, type of data (raw or norm)
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5 # output : dendrogram (jpeg)
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6
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7 # created Sept 13th, 2012
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8 # modified Oct 30th, 2012
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9 # Marie-Agnes Dillies
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10
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11
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12 clusterPlot <- function( cds, OUT_clusterPlot, type = "raw", out = TRUE ){
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13
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14 if (out) png( file=OUT_clusterPlot )
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15
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16 if (type == "norm"){
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17 cdsblind <- estimateDispersions( cds, method="blind" )
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18 vsd <- getVarianceStabilizedData( cdsblind )
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19 }
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20 else {
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21 vsd <- counts(cds)
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22 }
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23 hc <- hclust( dist(t(vsd)), method="ward" )
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24 plot( hc, xlab = "Euclidean distance, Ward criterion", main=paste("Cluster Dendrogram, ", type, " data", sep="") )
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25
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26 if (out) dev.off()
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27 }
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