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Bayesian Nonparametric Resolution of Multi-Strain Infections

Source: R/snp_slice.R
snp_slice.Rd

SNP-Slice is a Bayesian nonparametric method for resolving multi-strain infections using slice sampling with stick-breaking construction. The algorithm simultaneously unveils strain haplotypes and links them to hosts from sequencing data.

Usage

snp_slice(
  data,
  model = "negative_binomial",
  n_mcmc = 10000,
  burnin = NULL,
  alpha = 2.6,
  rho = 0.5,
  threshold = 0.001,
  gap = NULL,
  seed = NULL,
  verbose = TRUE,
  log_performance = FALSE,
  store_mcmc = FALSE,
  ...
)

snp_slice_categorical(data, e1 = 0.05, e2 = 0.05, ...)

snp_slice_poisson(data, ...)

snp_slice_binomial(data, ...)

snp_slice_negative_binomial(data, ...)

Arguments

data

Input data. Can be a matrix, data.frame, or file path. For read count data, should be a list with elements read1 and read0 (or total). For categorical data, can be a matrix with values 0, 0.5, or 1; or a long-format data.frame with columns specimen_id, target_id, target_value, and target_count. For a categorical data.frame, counts are converted to categories: ref-only -> 0, alt-only -> 1, both present -> 0.5, zero total -> NA. Matrix and categorical file inputs (e.g. *_cat.txt) remain supported.

model

Observation model to use. Options: "categorical", "poisson", "binomial", "negative_binomial" (default).

n_mcmc

Number of MCMC iterations (default: 10000).

burnin

Burn-in period. If NULL, defaults to n_mcmc/2.

alpha

IBP concentration parameter (default: 2.6).

rho

Dictionary sparsity parameter (default: 0.5).

threshold

Threshold for identifying single infections (default: 0.001).

gap

Early stopping threshold. If NULL, runs for full n_mcmc iterations.

seed

Random seed for reproducibility.

verbose

Whether to print progress information (default: TRUE).

log_performance

Whether to log performance metrics (default: FALSE).

store_mcmc

Whether to store full MCMC samples (default: FALSE).

...

Additional model-specific parameters.

e1

Error parameter for categorical model (default: 0.05)

e2

Error parameter for categorical model (default: 0.05)

Value

An object of class snp_slice_results containing:

  • allocation_matrix: Binary allocation matrix (A)

  • dictionary_matrix: Binary dictionary matrix (D)

  • mcmc_samples: MCMC samples (if store_mcmc = TRUE)

  • diagnostics: Convergence diagnostics

  • parameters: Model parameters used

  • model_info: Model specification

Examples

if (FALSE) { # \dontrun{
# Example with read count data
data <- list(
  read1 = matrix(c(10, 5, 15, 8), nrow = 2),
  read0 = matrix(c(90, 95, 85, 92), nrow = 2)
)

result <- snp_slice(data, model = "negative_binomial", n_mcmc = 1000)

# Extract results
strains <- extract_strains(result)
allocations <- extract_allocations(result)
} # }