library("PSCBS")
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Load SNP microarray data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
data <- PSCBS::exampleData("paired.chr01")
str(data)
# Drop single-locus outliers
dataS <- dropSegmentationOutliers(data)
# Run light-weight tests by default
if (Sys.getenv("_R_CHECK_FULL_") == "") {
# Use only every 5th data point
dataS <- dataS[seq(from=1, to=nrow(data), by=5),]
# Number of segments (for assertion)
nSegs <- 3L
# Number of bootstrap samples (see below)
B <- 100L
} else {
# Full tests
nSegs <- 8L
B <- 1000L
}
str(dataS)
R.oo::attachLocally(dataS)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulate that genotypes are known by other means
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
library("aroma.light")
muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1))
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Paired PSCBS segmentation
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE,
chromosome=chromosome, x=x,
seed=0xBEEF, verbose=-10)
print(fit)
# Plot results
plotTracks(fit)
# Sanity check
stopifnot(nbrOfSegments(fit) == nSegs)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Bootstrap segment level estimates
# (used by the AB caller, which, if skipped here,
# will do it automatically)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10)
print(fit)
plotTracks(fit)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Calling segments in allelic balance (AB) and
# in loss-of-heterozygosity (LOH)
# NOTE: Ideally, this should be done on whole-genome data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
fit <- callAB(fit, verbose=-10)
fit <- callLOH(fit, verbose=-10)
print(fit)
plotTracks(fit)
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