sigminer (version 1.0.6)

get_sig_similarity: Calculate Similarity between Identified Signatures and Reference Signatures

Description

The reference signatures can be either a Signature object specified by Ref argument or known COSMIC signatures specified by sig_db argument. Two COSMIC databases are used for comparisons - "legacy" which includes 30 signaures, and "SBS" - which includes updated/refined 65 signatures. This function is modified from compareSignatures() in maftools package.

Usage

get_sig_similarity(
  Signature,
  Ref = NULL,
  sig_db = "legacy",
  db_type = c("", "human-exome", "human-genome"),
  method = "cosine",
  normalize = c("row", "feature"),
  feature_setting = sigminer::CN.features,
  pattern_to_rm = NULL,
  verbose = TRUE
)

Arguments

Signature

a Signature object or a component-by-signature matrix (sum of each column is 1). More please see examples.

Ref

default is NULL, can be a same object as Signature.

sig_db

can be 'legacy' (for COSMIC v2 'SBS'), 'SBS', 'DBS', 'ID' and 'TSB' (for SBS transcriptional strand bias signatures). Default 'legacy'.

db_type

only used when sig_db is enabled. "" for keeping default, "human-exome" for transforming to exome frequency of component, and "human-genome" for transforming to whole genome frequency of component. Currently only works for 'SBS'.

method

default is 'cosine' for cosine similarity.

normalize

one of "row" and "feature". "row" is typically used for common mutational signatures. "feature" is designed by me to use when input are copy number signatures.

feature_setting

a data.frame used for classification. Only used when method is "Wang" ("W"). Default is CN.features. Users can also set custom input with "feature", "min" and "max" columns available. Valid features can be printed by unique(CN.features$feature).

pattern_to_rm

patterns for removing some features/components in similarity calculation. A vector of component name is also accepted. The remove operation will be done after normalization. Default is NULL.

verbose

if TRUE, print extra info.

Value

a list containing smilarities, aetiologies if available, and best match.

Examples

# NOT RUN {
# Load mutational signature
load(system.file("extdata", "toy_mutational_signature.RData",
  package = "sigminer", mustWork = TRUE
))

s1 <- get_sig_similarity(sig2, Ref = sig2)
s1

s2 <- get_sig_similarity(sig2)
s2
s3 <- get_sig_similarity(sig2, sig_db = "SBS")
s3

## Remove some components
## in similarity calculation
s4 <- get_sig_similarity(sig2,
  Ref = sig2,
  pattern_to_rm = c("T[T>G]C", "T[T>G]G", "T[T>G]T")
)
s4

## Same to DBS and ID signatures
# }