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 |

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.

`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.

https://stackoverflow.com/questions/4954507/calculate-the-area-under-a-curve

Derek Chiu

# 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)