Run CHORD

Runs CHORD given SNV and SV VCF files. NOTE: make sure you have the BSgenome.Hsapiens.UCSC.hgXX installed.

Usage

chord_run(
  vcf.snv = NULL,
  vcf.sv = NULL,
  df.sv = NULL,
  sample.name = NULL,
  ref.genome = "hg38",
  sv.caller = "manta",
  outpath = NULL,
  ...
)

Arguments

vcf.snv

Path to VCF containing SNVs and INDELs.

vcf.sv

Path to VCF containing SVs.

df.sv

A data.frame object containing the columns 'SVTYPE' and 'SVLEN' from a Manta SV VCF.

sample.name

Name of sample to use.

ref.genome

Human genome assembly. One of 'hg38' (default), 'hg19' or 'GRCh37'.

sv.caller

manta (default) or gridss.

outpath

File to write CHORD predictions to on disk (should end in '.gz'). If not specified, results won't be written to disk.

...

Other arguments to be passed to https://github.com/UMCUGenetics/CHORD/blob/d7c963/R/extractSigsChord.R.

Value

List with extracted signatures and HRD prediction.

Examples

snv <- system.file("extdata/umccrise/snv/somatic-ensemble-PASS.vcf.gz", package = "gpgr")
sv <- system.file("extdata/umccrise/sv/manta.vcf.gz", package = "gpgr")
chord_res <- chord_run(
  vcf.snv = snv, df.sv = chord_mantavcf2df(sv),
  sample.name = "foo"
)
#> Warning: 
#>    No reference genome loaded. Please install and load a BSgenome.
#>    For example:
#>       install.packages('BiocManager')
#>       BiocManager::install('BSgenome.Hsapiens.UCSC.hg19')
#>       library('BSgenome.Hsapiens.UCSC.hg19')
#> 
#>    Then specify the BSgenome to the ref.genome arguemnts to the relevant functions.
#>    For example:
#>       extractSigsSnv(..., ref.genome=BSgenome.Hsapiens.UCSC.hg19)
#> Loading required package: BiocGenerics
#> 
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
#>     lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#>     pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
#>     tapply, union, unique, unsplit, which.max, which.min
#> Loading required package: S4Vectors
#> Loading required package: stats4
#> 
#> Attaching package: ‘S4Vectors’
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> 
#> 
#> 
# chord_res2 <- chord_run(vcf.snv = snv, vcf.sv = sv, sample.name = "foo",
#                         outpath = "nogit/chord_results.json.gz")