Graphical Displays
Graph cumulative distribution function (CDF) graphs, relative change in area under CDF curves, heatmaps, and cluster assignment tracking plots.
graph_cdf(mat) graph_delta_area(mat) graph_heatmap(mat, main = NULL) graph_tracking(cl) graph_all(x)
mat |
same as |
main |
heatmap title. If |
cl |
same as |
x |
an object from |
graph_cdf
plots the CDF for consensus matrices from different algorithms.
graph_delta_area
calculates the relative change in area under CDF curve
between algorithms. graph_heatmap
generates consensus matrix heatmaps for
each algorithm in x
. graph_tracking
tracks how cluster assignments change
between algorithms. graph_all
is a wrapper that runs all graphing
functions.
Various plots from graph_*{}
functions. All plots are
generated using ggplot
, except for graph_heatmap
, which uses
NMF::aheatmap()
. Colours used in graph_heatmap
and graph_tracking
utilize RColorBrewer::brewer.pal()
palettes.
Derek Chiu
https://stackoverflow.com/questions/4954507/calculate-the-area-under-a-curve
# Consensus clustering for 3 algorithms library(ggplot2) set.seed(911) x <- matrix(rnorm(80), ncol = 10) CC1 <- consensus_cluster(x, nk = 2:4, reps = 3, algorithms = c("hc", "pam", "km"), progress = FALSE) # Plot CDF p <- graph_cdf(CC1) # Change y label and add colours p + labs(y = "Probability") + stat_ecdf(aes(colour = k)) + scale_color_brewer(palette = "Set2") # Delta Area p <- graph_delta_area(CC1) # Heatmaps with column side colours corresponding to clusters CC2 <- consensus_cluster(x, nk = 3, reps = 3, algorithms = "hc", progress = FALSE) graph_heatmap(CC2) # Track how cluster assignments change between algorithms p <- graph_tracking(CC1)
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