Refine Tier 1 Models and Their Segment Calls

For each candidate (mu, rho) model in tier1, extracts and refines segment calls, computes fit statistics, and returns a list of calls and model summaries.

Usage

RefineTier1Models(
  tier1,
  results,
  top_likelihood_rows,
  likelihood_min,
  seg,
  modelminprobes,
  gender,
  callcov,
  modelminAIsize
)

Arguments

tier1

Data frame or tibble. Each row is a candidate model with columns mu and rho.

results

Data frame or tibble. The full set of segment likelihoods/results.

top_likelihood_rows

Data frame or tibble. Top likelihood calls for each segment.

likelihood_min

Numeric. The minimum log-likelihood value to use as a penalty.

seg

Data frame or tibble. Segment information.

modelminprobes

Integer. Minimum number of probes for model inclusion.

gender

Character. Sample gender ("male" or "female").

callcov

Numeric. Subclonal events calling cutoff based on CNF.

modelminAIsize

Numeric. Minimum segment size for model inclusion.

Value

A list of length equal to nrow(tier1). Each element is a list with:

calls

Refined segment calls for the model.

model

Summary statistics for the model (data.frame).

Details

For each (mu, rho) combination, extracts and refines calls, computes distances to integer copy number, ploidy, and likelihoods, and summarizes the results.

Examples

# RefineTier1Models(tier1, results, top_likelihood_rows, likelihood_min, seg, modelminprobes = 20, gender = "female", callcov = 0.3, modelminAIsize = 500000)