## Chunk 1
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library("Biobase")
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## Chunk 2
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library("ALL")
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## Chunk 3
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GOTFfun = function(GOID) {
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## Chunk 4
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iqrs = esApply(es2, 1, IQR)
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## Chunk 5
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cols = ifelse(es2$mol.biol == "BCR/ABL", "black",
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## Chunk 9
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mD = as.matrix(manDist)
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## Chunk 11
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hc1 = hclust(manDist)
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## Chunk 12
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par(mfrow=c(4,1))
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## Chunk 15
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cph1 = cophenetic(hc1)
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## Chunk 17
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km2 = kmeans(gvals, centers=2, nstart=5)
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## Chunk 21
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pam2 = pam(manDist, k=2, diss=TRUE)
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## Chunk 22
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all(names(km2$cluster) == names(pam2$clustering))
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## Chunk 26
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set.seed(123)
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## Chunk 29
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set.seed(777)
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## Chunk 30
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cD = dist(s4$code)
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## Chunk 31
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newCodes = s4$code[-c(2,5,6,10, 15, 9, 11, 13, 14),]
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## Chunk 34
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samp.hobj = hopach(gvals, dmat = manDist)
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## Chunk 35
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samp.hobj$clust$sizes
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## Chunk 36
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gene.dist = distancematrix(t(gvals), d = "cosangle")
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## Chunk 37
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gene.hobj$clust$sizes
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## Chunk 38
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silpam2 = silhouette(pam2)
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## Chunk 39
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plot(silpam2, main="")
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## Chunk 40
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silpam3 = silhouette(pam3)
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## Chunk 41
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plot(silpam3, main="")
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## Chunk 42
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silpam3[silpam3[,"sil_width"] < 0,]
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|
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## Chunk 45
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rtt = rowttests(ALLfilt_bcrneg, "mol.biol")
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## Chunk 46
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pairs(t(exprs(esTT)[1:5,]),
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## Chunk 47
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pc = prcomp(t(exprs(esTT)))
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## Chunk 48
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pairs(pc$x[,1:5], col=ifelse(esTT$mol.biol=="NEG",
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## Chunk 49
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biplot(pc)
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|
## Chunk 51
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## esTT.K = ALLfilt_bcrneg[ordtt[1:K],]
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