library(FIREVAT)
# If you wish to run the sample code, change the 'output.dir' parameter
# and run the whole script.
# With 2 cores (each with 3.5GHz clock speed) this sample script
# takes about 10 minutes to complete
# Output directory
output.dir <- ""
# Sample VCF file
sample.vcf.file <- system.file("extdata", "DCC_PCAWG_Cell_Lines_HCC1954.vcf", package = "FIREVAT")
# Config file
config.file <- system.file("config", "PCAWG_DKFZ_Cell_Line_Filtering_Params.json", package = "FIREVAT")
# Annotation DB
# Download the ClinVar VCF file from
# ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh37/clinvar.vcf.gz
# Please remember to unzip the file first
clinvar.vcf.file <- ""
clinvar.vcf.obj <- ReadVCF(vcf.file = clinvar.vcf.file, genome = "hg19", split.info = TRUE)
df.annotation.db <- PrepareAnnotationDB(annotation.vcf.obj = clinvar.vcf.obj)
# Annotation parameters
cols.to.display = c("GENEINFO", "CLNSIG")
filter.key.value.pairs <- list("CLNSIG" = c("Pathogenic", "Pathogenic/Likely_pathogenic", "Likely_pathogenic"))
# Run FIREVAT
results <- RunFIREVAT(vcf.file = sample.vcf.file,
vcf.file.genome = 'hg19',
config.file = config.file,
df.ref.mut.sigs = GetPCAWGMutSigs(),
target.mut.sigs = GetPCAWGMutSigsNames(),
sequencing.artifact.mut.sigs = PCAWG.All.Sequencing.Artifact.Signatures,
output.dir = output.dir,
objective.fn = Default.Obj.Fn,
num.cores = 6,
ga.pop.size = 100,
ga.max.iter = 5,
ga.run = 5,
ga.pmutation = 0.1,
perform.strand.bias.analysis = TRUE,
ref.forward.strand.var = "TumorDPRefForward",
ref.reverse.strand.var = "TumorDPRefReverse",
alt.forward.strand.var = "TumorDPAltForward",
alt.reverse.strand.var = "TumorDPAltReverse",
annotate = TRUE,
df.annotation.db = df.annotation.db,
annotated.columns.to.display = cols.to.display,
annotation.filter.key.value.pairs = filter.key.value.pairs,
annotation.filter.condition = "AND")
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