chondro
## do baseline correction
baselines <- spc.fit.poly.below (chondro)
chondro <- chondro - baselines
## area normalization
chondro <- sweep (chondro, 1, apply (chondro, 1, mean), "/")
## substact common composition
chondro <- sweep (chondro, 2, apply (chondro, 2, quantile, 0.05), "-")
## PCA
pca <- prcomp (~ spc, data = chondro$., center = TRUE)
scores <- decomposition (chondro, pca$x, label.wavelength = "PC", label.spc = "score / a.u.")
loadings <- decomposition (chondro, t(pca$rotation), scores = FALSE, label.spc = "loading I / a.u.")
# remove outliers
out <- c(105, 140, 216, 289, 75, 69)
chondro <- chondro [- out]
# Hierarchical cluster analysis
dist <- dist (chondro [[]])
dendrogram <- hclust (dist, method = "ward")
plot (dendrogram)
clusters <- as.factor (cutree (dendrogram, k = 3))
cols <- c ("dark blue", "orange", "#C02020")
plotmap (chondro, clusters ~ x * y, col.regions = cols)
cluster.means <- aggregate (chondro, chondro$clusters, mean_pm_sd)
plot(cluster.means, stacked = ".aggregate", fill = ".aggregate", col = cols)
## plot nucleic acids
plotmap (chondro[, , c( 728, 782, 1098, 1240, 1482, 1577)],
col.regions = colorRampPalette (c("white", "gold", "dark green"), space = "Lab") (20))
vignette ("chondro", package = "hyperSpec")
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