normalizeBAFsByRegions.PairedPSCBS | R Documentation |
Normalizes allele B fractions (BAFs) based on region-based PSCN estimates as given by the PSCBS segmentation method.
## S3 method for class 'PairedPSCBS' normalizeBAFsByRegions(fit, by=c("betaTN", "betaT"), ..., force=FALSE, cache=TRUE, verbose=FALSE)
fit |
A PairedPSCBS fit object as returned by
|
by |
A |
... |
Additional arguments passed
|
verbose |
See |
Note that his normalization method depends on the segmentation results. Hence, it recommended not to resegment the normalized signals returned by this, because such a segmentation will be highly dependent on the initial segmentation round.
Returns a PairedPSCBS fit object where the region-level decrease-in-heterozygosity (DH) means have been normalized, as well as the locus-specific tumor allele B fractions.
Henrik Bengtsson, Pierre Neuvial
Internally normalizeMirroredBAFsByRegions
is used.
library("aroma.cn") if (Sys.getenv("_R_CHECK_FULL_") != "" && require("PSCBS")) { # Load example ASCN data data <- PSCBS::exampleData("paired.chr01") R.oo::attachLocally(data) # AD HOC: Robustification CT[CT < 0] <- 0 CT[CT > 30] <- 30 # PSCBS segmentation fit <- segmentByPairedPSCBS(CT, betaT=betaT, betaN=betaN, x=x, verbose=-10) # Normalize fitN <- normalizeBAFsByRegions(fit, verbose=-10) devSet("tracks") subplots(10, ncol=2, byrow=FALSE) par(mar=c(1,3.5,1,0.5)+1) plot(fit, subplots=TRUE) plot(fitN, subplots=TRUE) devSet("C1C2") Clim <- c(0,4) subplots(4, ncol=2, byrow=TRUE) par(mar=c(1,3.5,1,0.5)+1) plotC1C2(fit, Clim=Clim) linesC1C2(fit) title(main="(C1,C2)") plotC1C2(fitN, Clim=Clim) linesC1C2(fitN) title(main="(C1,C2) - adjusted") plotC1C2(fit, col="gray", Clim=Clim) linesC1C2(fit, col="gray") pointsC1C2(fitN) linesC1C2(fitN) title(main="(C1,C2) - both") } # if (require("PSCBS"))
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