Call CNVs in a pseudobulk profile using the Numbat joint HMM
analyze_bulk(
bulk,
t = 1e-05,
gamma = 20,
theta_min = 0.08,
logphi_min = 0.25,
nu = 1,
min_genes = 10,
exp_only = FALSE,
allele_only = FALSE,
bal_cnv = TRUE,
retest = TRUE,
find_diploid = TRUE,
diploid_chroms = NULL,
classify_allele = FALSE,
run_hmm = TRUE,
prior = NULL,
exclude_neu = TRUE,
phasing = TRUE,
verbose = TRUE
)
a pseudobulk profile dataframe with called CNV information
dataframe Pesudobulk profile
numeric Transition probability
numeric Dispersion parameter for the Beta-Binomial allele model
numeric Minimum imbalance threshold
numeric Minimum log expression deviation threshold
numeric Phase switch rate
integer Minimum number of genes to call an event
logical Whether to run expression-only HMM
logical Whether to run allele-only HMM
logical Whether to call balanced amplifications/deletions
logical Whether to retest CNVs after Viterbi decoding
logical Whether to run diploid region identification routine
character vector User-given chromosomes that are known to be in diploid state
logical Whether to only classify allele (internal use only)
logical Whether to run HMM (internal use only)
numeric vector Prior probabilities of states (internal use only)
logical Whether to exclude neutral segments from retesting (internal use only)
logical Whether to use phasing information (internal use only)
logical Verbosity
bulk_analyzed = analyze_bulk(bulk_example, t = 1e-5, find_diploid = FALSE, retest = FALSE)
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