applyCNPmask | R Documentation |
A mask is applied to amplified or deleted segments as tabulated in
segtable
. A decision whether to mask a segment is taken based on what
portion of the segment is covered by the mask. A position is chosen at random
within a segment to be masked, the flanking segments are extended to that
position and the segment to be masked is indicated as such in the value
returned.
applyCNPmask(segtable,chrom,startPos,endPos,startProbe,endProbe, eventIndex,masktable,maskchrom,maskstart,maskend,maskindex,mincover=1, indexvals=c(-1,1))
segtable |
A matrix or a data frame with columns named or enumerated by the values of
|
chrom |
A character string specifying the name for the column in |
startPos, endPos |
Character strings or integers specifying the names or numbers of columns in
|
startProbe, endProbe |
Character strings specifying the names of columns in |
eventIndex |
A character string giving the name of a column in |
masktable |
A matrix or a data frame with columns named or enumerated as given by
|
maskchrom,maskstart,maskend |
Character strings or integers specifying the names or numbers of columns
in |
maskindex |
A numeric vector corresponding to |
mincover |
A numeric value specifying the minimal portion of the segment that must be covered by the mask in order to trigger masking. |
indexvals |
A numeric vector of length 2 specifying the two values in |
Masking is performed separately for each value in indexvals
. Segments
(rows of segtable
) with that value of eventIndex
are examined
for coverage by mask intervals with that value of maskindex
in
masktable
. If the coverage is at least mincover
, the segment is
slated for masking, while its flanking segments are extended to a random
point within the segment being masked.
A matrix with same number of observations/rows as segtable
and with
following three columns:
startProbe,endProbe |
An integer vector for the start and end positions of the segments after masking. |
toremove |
An integer vector whose values are 1 if the segment is masked and 0 otherwise. |
Alex Krasnitz
## Not run: data(segexample) data(ratexample) data(normsegs) data(cnpexample) segtable<-CNpreprocessing(segall=segexample[segexample[,"ID"]=="WZ1",], ratall=ratexample,"ID","start","end",chromcol="chrom",bpstartcol="chrom.pos.start", bpendcol="chrom.pos.end",blsize=50,minjoin=0.25,cweight=0.4,bstimes=50, chromrange=1:22,distrib="Rparallel",njobs=2,modelNames="E",normalength=normsegs[,1], normalmedian=normsegs[,2]) #form a eventIndex vector eventIndex<-rep(0,nrow(segtable)) eventIndex[segtable[,"marginalprob"]<1e-4&segtable[,"negtail"]> 0.999&segtable[,"mediandev"]<0] <- -1 eventIndex[segtable[,"marginalprob"]<1e-4&segtable[,"negtail"]> 0.999&segtable[,"mediandev"]>0] <- 1 segtable<-cbind(segtable,eventIndex) #form a cnpindex vector namps17<-cnpexample[cnpexample[,"copy.num"]=="amp",] aCNPmask<-makeCNPmask(imat=namps17,chromcol=2,startcol=3,endcol=4, nprof=1203,uthresh=0.02,dthresh=0.008) ndels17<-cnpexample[cnpexample[,"copy.num"]=="del",] dCNPmask<-makeCNPmask(imat=ndels17,chromcol=2,startcol=3,endcol=4, nprof=1203,uthresh=0.02,dthresh=0.008) cnptable<-rbind(cbind(aCNPmask,cnpindex=1),cbind(dCNPmask,cnpindex=-1)) #run the CNP test myCNPtable<-applyCNPmask(segtable,"chrom",startPos="chrom.pos.start", endPos="chrom.pos.end","start","end","eventIndex",masktable=cnptable,"chrom", maskstart="start",maskend="end",maskindex="cnpindex",mincover=0.005,indexvals=c(-1,1)) ## End(Not run)
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