This function is an attempt to analyze the relationship between error and k. In other words, the goal of prelimProcessAssess is to visualize the reduction in the error/residuals
prelimProcessAssess(
input,
maxProcess = 6,
approach = "counts",
plot = TRUE,
verbose = TRUE
)
a mutationCounts-class object
integer, maximum k to test
sting, "counts" or "freq"
logical, shall a plot be printed to the active device
logical, info about the ongoing analysis be messaged/printed to console
a data.frame showing the estimated total error with respect to the range of k values
This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.
More information and examples about mutational signature analysis can be found here:
GitHub Repo: https://github.com/dami82/mutSignatures/
More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/
Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/
Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6