PileupSequenceData-class {RNAmodR} | R Documentation |
The PileupSequenceData
aggregates the pileup of called bases per
position.
PileupSequenceData
contains five columns per data file named using the
following naming convention pileup.condition.replicate
. The five
columns are distinguished by additional identifiers -
, G
,
A
, T
and C
.
aggregate
calculates the mean and sd for each nucleotide in the
control
and treated
condition separatly. The results are then
normalized to a row sum of 1.
PileupSequenceDataFrame( df, ranges, sequence, replicate, condition, bamfiles, seqinfo ) PileupSequenceData(bamfiles, annotation, sequences, seqinfo, ...) ## S4 method for signature ## 'PileupSequenceData,BamFileList,GRangesList,XStringSet,ScanBamParam' getData(x, bamfiles, grl, sequences, param, args) ## S4 method for signature 'PileupSequenceData' aggregateData(x, condition = c("Both", "Treated", "Control")) ## S4 method for signature 'PileupSequenceData' getDataTrack(x, name, ...) pileupToCoverage(x) ## S4 method for signature 'PileupSequenceData' pileupToCoverage(x)
df, ranges, sequence, replicate |
inputs for creating a
|
condition |
For |
bamfiles, annotation, seqinfo, grl, sequences, param, args, ... |
See
|
x |
a |
name |
For |
a PileupSequenceData
object
# Construction of a PileupSequenceData object library(RNAmodR.Data) library(rtracklayer) annotation <- GFF3File(RNAmodR.Data.example.man.gff3()) sequences <- RNAmodR.Data.example.man.fasta() files <- c(treated = RNAmodR.Data.example.wt.1()) psd <- PileupSequenceData(files, annotation = annotation, sequences = sequences)