Loose ends in cancer genome structure
This package is dependent on the directory of reference genomes and sequences found at https://mskilab.s3.amazonaws.com/hg19/WGS/hg19_looseends.tar.gz, which is expected by default to be unzipped within the extdata/ directory (not required; alternate path can be provided)
To characterize all loose ends in a single genome graph gg:
ggraph.loose.ends(gg = gG(jabba=/path/to/jabba.rds),
cov.rds = /path/to/cov.rds,
tbam = /path/to/tumor.bam,
nbam = /path/to/normal.bam, # optional but recommended
id = "SAMPLE-ID",
outdir = /path/to/output/, # default = NULL will not write output files
purity = NULL, # default assumes purity = 1
ploidy = NULL, # default estimates ploidy from gGraph
field = "ratio", # normalized coverage field in cov.rds
PTHRESH = 3.4e-7, # recommended for 200bp bins. for 1kbp bins, use 2e-6
verbose = F,
mc.cores = 1,
ref_dir = system.file("extdata", "hg19_looseends", package = "loosends"))
- will perform quality filters on fitted loose ends and evaluate all true positives
- returns data.table describing the categorization and repeat content of each true positive loose end
Performance depends on loose end burden in graph and sequencing coverage depth
To characterize a set of loose ends of interest le:
process.loose.ends(le = GRanges(),
tbam = /path/to/tumor.bam,
nbam = /path/to/normal.bam,
id = "SAMPLE-ID",
outdir = /path/to/output/,
mc.cores = 1,
ref_dir = system.file("extdata", "hg19_looseends", package = "loosends"),
verbose = FALSE)
- returns data.table describing the categorization and repeat content of every input loose end
- tbam, nbam, and id must all either be length=1 (all loose ends from a single sample) or length=length(le)
Performance depends on sequencing coverage depth