predict_exposure: Prediction of exposures in new samples using pre-existing...

In campbio/musicatk: Mutational Signature Comprehensive Analysis Toolkit

Prediction of exposures in new samples using pre-existing signatures

Description

Exposures for samples will be predicted using an existing set of signatures stored in a musica_result object. Algorithms available for prediction include a modify version of "lda", and "decompTumor2Sig".

Usage

predict_exposure(
  musica,
  table_name,
  signature_res,
  algorithm = c("lda", "decompTumor2Sig"),
  signatures_to_use = seq_len(ncol(signatures(signature_res))),
  verbose = FALSE
)

Arguments

musica	A musica object.
table_name	Name of table used for posterior prediction. Must match the table type used to generate the prediction signatures
signature_res	Signatures used to predict exposures for the samples musica object. Existing signatures need to stored in a musica_result object.
algorithm	Algorithm to use for prediction of exposures. One of "lda" or "decompTumor2Sig".
signatures_to_use	Which signatures in the signature_res result object to use. Default is to use all signatures.
verbose	If TRUE, progress will be printing. Only used if algorithm = "lda". Default FALSE.

Value

Returns a A musica_result object containing signatures given by the signature_res parameter and exposures predicted from these signatures.

Examples

data(musica)
data(cosmic_v2_sigs)
g <- select_genome("19")
build_standard_table(musica, g, "SBS96", overwrite = TRUE)
result <- predict_exposure(musica = musica, table_name = "SBS96",
signature_res = cosmic_v2_sigs, algorithm = "lda")

# Predict using LDA-like algorithm with seed set to 1
set.seed(1)
predict_exposure(musica = musica, table_name = "SBS96",
signature_res = cosmic_v2_sigs, algorithm = "lda")

campbio/musicatk documentation built on July 14, 2024, 8:28 a.m.