PileupSequenceData-class: PileupSequenceData

In RNAmodR: Detection of post-transcriptional modifications in high throughput sequencing data

Description

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.

Usage

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)

Arguments

df, ranges, sequence, replicate	inputs for creating a SequenceDataFrame. See SequenceDataFrame.
condition	For aggregate: condition for which the data should be aggregated.
bamfiles, annotation, seqinfo, grl, sequences, param, args, ...	See SequenceData and SequenceData-functions
x	a PileupSequenceData
name	For getDataTrack: a valid transcript name. Must be a name of ranges(x)

Value

a PileupSequenceData object

Examples

# 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)

RNAmodR documentation built on Dec. 15, 2020, 2 a.m.