Fit a bascule object
fit.Rd
Fit a bascule object
Usage
fit(
counts,
k_list,
cluster = NULL,
reference_cat = list(SBS = COSMIC_filt, DBS = COSMIC_dbs),
keep_sigs = c("SBS1", "SBS5"),
hyperparameters = NULL,
lr = 0.005,
optim_gamma = 0.1,
n_steps = 3000,
py = NULL,
enumer = "parallel",
nonparametric = TRUE,
autoguide = FALSE,
filter_dn = FALSE,
min_exposure = 0.2,
CUDA = TRUE,
compile = FALSE,
store_parameters = FALSE,
store_fits = TRUE,
seed_list = c(10)
)
Arguments
- counts
List of mutation counts matrices from multiple variant types.
- k_list
List of number of denovo signatures to test.
- cluster
Maximum number of clusters. If `NULL`, no clustering will be performed.
- reference_cat
List of reference catalogues to use for NMF. Names must be the same as input counts.
- keep_sigs
List of reference signatures to keep even if found with low exposures.
- hyperparameters
List of hyperparameters passed to the NMF and clustering models.
- lr
Learning rate used for SVI.
- optim_gamma
Deprecated
- n_steps
Number of iterations for inference.
- py
User-installed version of
pybascule
package- enumer
Enumeration used for clustering (either `parallel` or `sequential`).
- nonparametric
Deprecated. The model only works in nonparametric way.
- autoguide
Logical. If `TRUE`, the clustering model will use the Pyro autoguide.
- filter_dn
Logical. If `TRUE`, all contexts below 0.01 in denovo signatures will be set to 0, provided the filtered signatures remain consistent with the inferred ones.
- min_exposure
Reference signatures with an exposures lower than `min_exposure` will be dropped.
- CUDA
Logical. If `TRUE` and a GPU is available, the models will run on GPU.
- compile
Deprecated.
- store_parameters
Logical. If `TRUE`, parameters at every step of inference will be stored in the object.
- store_fits
Logical. If `TRUE`, all tested fits, i.e., for every value of `K`, will be stored in the object.
- seed_list
List of seeds used for every input configuration.