View source: R/extractSigsSv.R
extractSigsSv | R Documentation |
Will return a 1-column matrix containing: (if output = 'signatures') the absolute signature contributions (i.e. the number of mutations contributing to each mutational signature), or (if output = 'contexts') the mutation contexts.
To elaborate, the 6 SV signatures used are those described in this paper: https://media.nature.com/original/nature-assets/nature/journal/v534/n7605/extref/nature17676-s3.zip, in Supplementary.Table.21.Signatures.v3.xlsx. These are derived from mutation contexts composed of SV type/length.
Note that the probabilities of the clustered and non-clustered rearrangements in the signature profile have been combined. In other words, whether the rearrangements were clustered/non-clustered were not considered.
extractSigsSv(
vcf.file = NULL,
df = NULL,
output = "signatures",
sample.name = NULL,
sv.caller = "gridss",
half.tra.counts = F,
sv.len.cutoffs = if (output == "signatures") { c(10^c(3:7), Inf) } else {
c(0, 10^c(3:7), Inf) },
signature.profiles = SV_SIGNATURE_PROFILES,
verbose = F,
...
)
vcf.file |
Path to the vcf file |
df |
A dataframe with the columns: sv_type, sv_len. sv_type can be DEL, DUP, INV, TRA, BND. Note that for TRA and BND, sv_len will be ignored. Alternative input option to vcf.file |
output |
Output the absolute signature contributions (default, 'signatures'), or the SV type/length contexts ('contexts') |
sample.name |
If a character is provided, the header for the output matrix will be named to this. If none is provided, the basename of the vcf file will be used. |
sv.caller |
Can be 'manta', 'gridss', or 'pcawg' |
half.tra.counts |
Divide translocation counts by 2? |
sv.len.cutoffs |
SV length cutoff intervals as a numeric vector. |
signature.profiles |
A matrix containing the mutational signature profiles, where rows are the mutation contexts and the columns are the mutational signatures. |
verbose |
Print progress messages? |
A 1-column matrix containing the context counts or signature contributions
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