# These won't run unless you have the reads available in a BAM or BED file
data(tamoxifen_peaks)
## Not run: tamoxifen <- dba.count(tamoxifen)
# Count using a peakset made up of only peaks in all responsive MCF7 replicates
data(tamoxifen_peaks)
mcf7Common <- dba.overlap(tamoxifen,tamoxifen$masks$MCF7&tamoxifen$masks$Responsive)
## Not run: tamoxifen <- dba.count(tamoxifen,peaks=mcf7Common$inAll)
tamoxifen
#First make consensus peaksets from each set of replicates,
#then derive master consensus set for counting from those
data(tamoxifen_peaks)
tamoxifen <- dba.peakset(tamoxifen,consensus = -DBA_REPLICATE)
## Not run: tamoxifen <- dba.count(tamoxifen, peaks=tamoxifen$masks$Consensus)
tamoxifen
# Change binding affinity scores
data(tamoxifen_counts)
tamoxifen <- dba.count(tamoxifen,peaks=NULL,score=DBA_SCORE_READS)
dba.peakset(tamoxifen, bRetrieve=TRUE)
tamoxifen <- dba.count(tamoxifen,peaks=NULL,score=DBA_SCORE_RPKM_FOLD)
dba.peakset(tamoxifen, bRetrieve=TRUE)
tamoxifen <- dba.count(tamoxifen,peaks=NULL,score=DBA_SCORE_TMM_MINUS_FULL)
dba.peakset(tamoxifen, bRetrieve=TRUE)
# Plot effect of a range of filter values and then apply filter
data(tamoxifen_counts)
rate.max <- dba.count(tamoxifen, peaks=NULL, filter=0:250)
rate.sum <- dba.count(tamoxifen, peaks=NULL, filter=0:250,filterFun=sum)
plot(0:250,rate.max/rate.max[1],type='l',xlab="Filter Value",ylab="Proportion Retained Sites")
lines(0:250,rate.sum/rate.sum[1],col=2)
tamoxifen <- dba.count(tamoxifen,peaks=NULL,filter=125,filterFun=sum)
tamoxifen
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