GetSynSigParamsFromExposures: Empirical estimates of key parameters describing exposures...

In steverozen/SynSigGen: Create Catalogs of Synthetic Mutational Spectra

Empirical estimates of key parameters describing exposures due to signatures.

Description

Empirical estimates of key parameters describing exposures due to signatures.

Usage

GetSynSigParamsFromExposures(
  exposures,
  verbose = 0,
  distribution = NULL,
  cancer.type = NULL,
  sig.params = NULL
)

Arguments

exposures	A matrix in which each column is a sample and each row is a mutation signature, with each element being the "exposure", i.e. mutation count attributed to a (sample, signature) pair.
verbose	If > 0 cat various messages.
distribution	Probability distribution used to fit exposures due to one mutational signature. Can be neg.binom which stands for negative binomial distribution. If NULL (Default), then this function uses log normal distribution with base 10.
cancer.type	Optional argument specifying the cancer type of the samples being analyzed.
sig.params	Empirical signature parameters generated using real exposures irrespective of their cancer types. If there is only one tumor having a signature in a cancer type in exposures, we cannot fit the distribution to only one data point. Instead, we will use the empirical parameter size from sig.params. Users can use SynSigGen:::GetSynSigParamsFromExposuresOld to generate their own signature parameters. If NULL(default), this function uses the PCAWG7 empirical signature parameters. See signature.params for more details.

Value

• For log normal distribution, a data frame with one column for each of a subset of the input signatures and the following rows

  prob

  The proportion of tumors with the signature.

  mean

  The mean(log_10(number of mutations)).

  stdev

  The stdev(log_10(number of mutations)).

  Signatures not present in exposures or present only in a single tumor in exposures are removed.

• For negative binomial distribution, a data frame with one column for each of a subset of the input signatures and the following rows

  prob

  The proportion of tumors with the signature.

  size

  Dispersion parameter.

  mu

  Mean.

steverozen/SynSigGen documentation built on April 1, 2022, 8:54 p.m.