mcmcMain: run PICTograph in an automated pipeline

In KarchinLab/pictograph: Tools for modeling clonal evolution of a cancer

run PICTograph in an automated pipeline

Description

run MCMC chains to infer the clonal evolution of tumors from single or multi-region sequencing data. This function automatically runs a pipeline of the tool. It models uncertainty of mutation cellular fraction (MCF) in small somatic mutations (SSMs) and copy number alterations (CNAs), assigning SSMs and CNAs to subclones using a Bayesian hierarchical model, and reconstruct tumor evolutionary trees that are constrained based on principles of lineage precedence, sum condition, and optionally by sample-presence.

Usage

mcmcMain(
  mutation_file,
  outputDir = NULL,
  sample_presence = TRUE,
  score = "silhouette",
  max_K = 10,
  min_mutation_per_cluster = 5,
  cluster_diff_thresh = 0.05,
  n.iter = 5000,
  n.burn = 1000,
  thin = 10,
  mc.cores = 8,
  inits = list(.RNG.name = "base::Wichmann-Hill", .RNG.seed = 123),
  alt_reads_thresh = 0,
  vaf_thresh = 0
)

Arguments

mutation_file	a csv file that include information for SSMs.
outputDir	output directory for saving all files.
sample_presence	whether to use sample presence to separate the mutations. Not applicable if dual_model is set to FALSE and a copy number file is provided.
score	scoring function to estimate the number of clusters. silhouette or BIC.
max_K	user defined maximum number of clusters.
min_mutation_per_cluster	minumum number of mutations in each cluster.
cluster_diff_thresh	threshold to merge two clusters.
n.iter	number of iterations by JAGS.
n.burn	number of burns by JAGS.
thin	number of thin by JAGS.
mc.cores	number of cores to use for parallel computing; not applicable to windows.
inits	additional parameters by JAGS.

KarchinLab/pictograph documentation built on Oct. 25, 2024, 10:10 a.m.