callGainsAndLosses.CBS | R Documentation |
Calls gains and losses.
## S3 method for class 'CBS'
callGainsAndLosses(fit, adjust=1, method=c("ucsf-mad", "ucsf-dmad"), ..., verbose=FALSE)
adjust |
A positive scale factor adjusting the sensitivity of the caller, where a value less (greater) than 1.0 makes the caller less (more) sensitive. |
method |
A |
... |
Additional/optional arguments used to override the default parameters used by the caller. |
Returns a CBS
object where logical
columns
'lossCall' and 'gainCall' have been appended to the segmentation table.
If method == "ucsf-mad"
, then segments are called using [1], i.e.
a segment is called gained or lost if its segment level is
at least two standard deviations away from the median segment level
on Chr1-22, where standard deviation is estimated using MAD.
Then same is done for method == "ucsf-dmad"
with the difference
that the standard deviation is estimated using a robust first order
variance estimator.
Henrik Bengtsson
[1] Fridlyand et al. Breast tumor copy number aberration
phenotypes and genomic instability, BMC Cancer, 2006.
*callAmplifications()
.
*callOutliers()
.
For more information see CBS
.
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# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
set.seed(0xBEEF)
# Number of loci
J <- 1000
mu <- double(J)
mu[200:300] <- mu[200:300] + 1
mu[350:400] <- NA # centromere
mu[650:800] <- mu[650:800] - 1
eps <- rnorm(J, sd=1/2)
y <- mu + eps
x <- sort(runif(length(y), max=length(y))) * 1e5
w <- runif(J)
w[650:800] <- 0.001
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Segmentation
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
fit <- segmentByCBS(y, x=x)
print(fit)
plotTracks(fit)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# CALLS
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Call gains and losses by segments
fitC <- callGainsAndLosses(fit)
# Call amplifications by segments
fitC <- callAmplifications(fitC)
# Call outliers by loci
fitC <- callOutliers(fitC)
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