View source: R/plot_compare_indels.R
plot_compare_indels | R Documentation |
Plots two indel mutation profiles and their difference, reports the residual sum of squares (RSS).
plot_compare_indels( profile1, profile2, profile_names = c("profile 1", "profile 2"), profile_ymax = 0.2, diff_ylim = c(-0.1, 0.1) )
profile1 |
First mutation profile |
profile2 |
Second mutation profile |
profile_names |
Character vector with names of the mutations profiles used for plotting, default = c("profile 1", "profile 2") |
profile_ymax |
Maximum value of y-axis (relative contribution) for profile plotting. This can only be used to increase the y axis. If bars fall outside this limit, the maximum value is automatically increased. default = 0.2. |
diff_ylim |
Y-axis limits for profile difference plot, default = c(-0.1, 0.1) |
A ggplot2 object
plot_compare_profiles
,
plot_compare_dbs
,
plot_compare_mbs
Other Indels:
count_indel_contexts()
,
get_indel_context()
,
plot_indel_contexts()
,
plot_main_indel_contexts()
## Get the indel counts ## See 'count_indel_contexts()' for more info on how to do this. indel_counts <- readRDS(system.file("states/blood_indel_counts.rds", package = "MutationalPatterns" )) ## Get indel refit info. ## See 'fit_to_signatures()' for more info on how to do this. fit_res <- readRDS(system.file("states/indel_refit.rds", package = "MutationalPatterns" )) ## Compare the reconstructed profile of sample 1 with the original profile ## The same thing could be done with a reconstructed profile from NMF. plot_compare_indels(indel_counts[, 1], fit_res$reconstructed[, 1]) ## You could also compare regular mutation profiles with eachother. plot_compare_indels( indel_counts[, 1], indel_counts[, 2] ) ## Or change the names of the profiles plot_compare_indels(indel_counts[, 1], indel_counts[, 2], profile_names = c("Original", "Reconstructed") ) ## You can also change the y limits. ## This can be done separately for the profiles and the different facets. plot_compare_indels(indel_counts[, 1], indel_counts[, 2], profile_ymax = 0.3, diff_ylim = c(-0.03, 0.03) )
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