SignatureFit_withBootstrap: Mutational Signatures Fit with Bootstrap

In pdiakumis/hrdetect: Signature Tools

Description

Fit a given set of mutational signatures into mutational catalogues to extimate the activty/exposure of each of the given signatures in the catalogues. Implementation of method similar to Huang et al. 2017, Detecting presence of mutational signatures with confidence, which uses a bootstrap apporach to calculate the empirical probability of an exposure to be larger or equal to a given threshold (i.e. 5 This probability can be used to decide which exposures to remove from the initial fit, thus increasing the sparsity of the exposures.

Usage

SignatureFit_withBootstrap(
  cat,
  signature_data_matrix,
  nboot = 100,
  threshold_percent = 5,
  threshold_p.value = 0.05,
  method = "KLD",
  bf_method = "CosSim",
  alpha = -1,
  verbose = TRUE,
  doRound = TRUE,
  nparallel = 1,
  n_sa_iter = 500
)

Arguments

cat	catalogue matrix, patients as columns, channels as rows
signature_data_matrix	signatures, signatures as columns, channels as rows
nboot	number of bootstraps to use, more bootstraps more accurate results
threshold_percent	threshold in percentage of total mutations in a sample, only exposures larger than threshold are considered
threshold_p.value	p-value to determine whether an exposure is above the threshold_percent. In other words, this is the empirical probability that the exposure is lower than the threshold
method	KLD or NNLS or SA
bf_method	bleeding filter method, one of KLD or CosSim, only if bleeding filter is used (alpha>-1)
alpha	set alpha to -1 to avoid Bleeding Filter
verbose	use FALSE to suppress messages
doRound	round the exposures to the closest integer
nparallel	to use parallel specify >1
n_sa_iter	set max Simulated Annealing iterations if method==SA

Value

returns the activities/exposures of the signatures in the given sample and other information, such as p-values and exposures of individual bootstrap runs.

References

Huang, X., Wojtowicz, D., & Przytycka, T. M. (2017). Detecting Presence Of Mutational Signatures In Cancer With Confidence. bioRxiv, (October). https://doi.org/10.1101/132597

Examples

res <- SignatureFit_withBootstrap(catalogues,signature_data_matrix)

pdiakumis/hrdetect documentation built on May 17, 2020, 5:30 p.m.