Butte: Calculate timing of SCNA

In SunPathLab/Butte: BoUnds of Time Till Expansion, inferring the SCNA arrival time in the somatic evolution toward the most recent common ancestor of tumor sample(s).

Calculate timing of SCNA

Description

This function estimates the timing of SCNAs for the following two scenarios. For 2:0 3:1 3:0 4:1, where an identifiable history matrix is available, this function returns the time estimate and confidence interval for each stage For SCNAs with multiple or non-indentifible matrix, this function instead returns the bounds (lower and upper) of time period for the last stage of the corresponding SCNA evolution.

Usage

Butte(
  x,
  m,
  history,
  nt,
  nb,
  qmethod = c("fullMLE", "partialMLE"),
  type = c("identifiable", "butte"),
  seqError = 0,
  bootstrapCI = NULL,
  B = 500,
  CILevel = 0.9,
  purity = 1,
  verbose = TRUE,
  returnAssignments = TRUE,
  minMutations = 10,
  init = NULL,
  maxiter = 100,
  tol = 1e-04,
  mutationId = 1:length(x),
  ...
)

Arguments

x	vector of number of reads supporting SSNVs
m	vector of total read depth for SSNVs
history	a list of possible evolutionary history matrices, see also function "cnmutHistory"
nt	total copy number
nb	copy number of the minor allele
qmethod	suggest to use fullMLE, which is more accurate
type	set it to be either "identifiable" or "butte", or leave it unset
seqError	sequencing errors
bootstrapCI	set to "bootstrap" if non-parametric; or "parametric". This specify the confidence interval method. NULL if do not want to calculate CI
B	the number of bootstrapping samples
CILevel	confidence interval level
purity	tumor sample purity
verbose	logical. Turn on/off additional warnings.
returnAssignments	logical. Whether to return the probabilistic assignments of SSNVs to allele states generated by the EM algorithm, as well as the SSNV read counts (total depth and depth of the mutant allele).
minMutations	minimum number of SSNVs required for timing analysis
init	the initial value of vector q passed to function .estimateQ
maxiter	maximum number of iterations in EM algorithm when calculating the allele state distribution
tol	the tolerance in the convergence of q
mutationId	a vector of mutation IDs. The default is 1:length of x.

Value

A list of possible matrices

SunPathLab/Butte documentation built on Sept. 19, 2023, 9:42 a.m.