run_joint_hmm_s15 {hahmmr}

Run 15-state joint HMM on a pseudobulk profile

Description

Run 15-state joint HMM on a pseudobulk profile

Usage

run_joint_hmm_s15(
  pAD,
  DP,
  p_s,
  Y_obs = 0,
  lambda_ref = 0,
  d_total = 0,
  theta_min = 0.08,
  theta_neu = 0,
  bal_cnv = TRUE,
  phi_del = 2^(-0.25),
  phi_amp = 2^(0.25),
  phi_bamp = phi_amp,
  phi_bdel = phi_del,
  mu = 0,
  sig = 1,
  r = 0.015,
  t = 1e-05,
  gamma = 18,
  prior = NULL,
  exp_only = FALSE,
  allele_only = FALSE,
  classify_allele = FALSE,
  debug = FALSE,
  ...
)

Arguments

pAD

integer vector Paternal allele counts

DP

integer vector Total alelle counts

p_s

numeric vector Phase switch probabilities

Y_obs

numeric vector Observed gene counts

lambda_ref

numeric vector Reference expression rates

d_total

integer Total library size for expression counts

theta_min

numeric Minimum haplotype imbalance threshold

theta_neu

numeric Haplotype imbalance threshold for neutral state

bal_cnv

logical Whether to include balanced CNV states

phi_del

numeric Expected fold change for deletion

phi_amp

numeric Expected fold change for amplification

phi_bamp

numeric Expected fold change for balanced amplification

phi_bdel

numeric Expected fold change for balanced deletion

mu

numeric Global expression bias

sig

numeric Global expression variance

r

numeric Variant mapping bias

t

numeric Transition probability between copy number states

gamma

numeric Overdispersion in the allele-specific expression

prior

numeric vector Prior probabilities for each state

exp_only

logical Whether to only use expression data

allele_only

logical Whether to only use allele data

classify_allele

logical Whether to classify allele states

debug

logical Whether to print debug messages

...

Additional parameters

Value

character vector Decoded states

Examples

with(bulk_example, {
    run_joint_hmm_s15(pAD = pAD, DP = DP, p_s = p_s, Y_obs = Y_obs, lambda_ref = lambda_ref, 
    d_total = na.omit(unique(d_obs)), mu = mu, sig = sig, t = 1e-5, gamma = 30, theta_min = 0.08)
})