ScoreMatrixBin-methods.Rd

% Generated by roxygen2 (4.1.0.9001): do not edit by hand
% Please edit documentation in R/scoreMatrixBin.R
\docType{methods}
\name{ScoreMatrixBin}
\alias{ScoreMatrixBin}
\alias{ScoreMatrixBin,GRanges,GRanges-method}
\alias{ScoreMatrixBin,RleList,GRanges-method}
\alias{ScoreMatrixBin,character,GRanges-method}
\title{Get bin score for bins on each window}
\usage{
ScoreMatrixBin(target, windows, bin.num = 10, bin.op = "mean",
  strand.aware = FALSE, weight.col = NULL, is.noCovNA = FALSE,
  type = "", rpm = FALSE, unique = FALSE, extend = 0, param = NULL,
  bam.paired.end = FALSE, stranded = TRUE)

\\S4method{ScoreMatrixBin}{RleList,GRanges}(target, windows, bin.num, bin.op, strand.aware)

\\S4method{ScoreMatrixBin}{GRanges,GRanges}(target,windows,bin.num,bin.op,strand.aware,weight.col,is.noCovNA)

\\S4method{ScoreMatrixBin}{character,GRanges}(target, windows, bin.num=10, bin.op='mean',
                                                     strand.aware, type, rpm, unique, extend, param,
                                                     bam.paired.end=FALSE, stranded=TRUE)
}
\arguments{
\item{target}{\code{RleList},  \code{GRanges}, BAM file or a bigWig file
object to be overlapped with ranges in \code{windows}}

\item{windows}{\code{GRanges} object that contains the windows of interest.
It could be promoters, CpG islands, exons, introns. However,
the sizes of windows does NOT have to be equal.}

\item{bin.num}{single \code{integer} value denoting how many bins there
should be for each window}

\item{bin.op}{bin operation that is either one of the following strings:
"max","min","mean". The operation is applied on the
values in the bin. Defaults to "mean"}

\item{strand.aware}{If TRUE (default: FALSE), the strands of the windows will
be taken into account in the resulting \code{scoreMatrix}.
If the strand of a window is -, the values of the bins
for that window will be reversed}

\item{weight.col}{if the object is \code{GRanges} object a numeric column
 in meta data part can be used as weights. This is particularly
useful when genomic regions have scores other than their
coverage values, such as percent methylation, conservation
scores, GC content, etc.}

\item{is.noCovNA}{(Default:FALSE)
if TRUE,and if 'target' is a GRanges object with 'weight.col'
 provided, the bases that are uncovered will be preserved as
 NA in the returned object. This useful for situations where
 you can not have coverage all over the genome, such as CpG
  methylation values.}

\item{type}{if target is a character vector of file paths, then type designates
the type of the corresponding files (bam or bigWig)}

\item{rpm}{boolean telling whether to normalize the coverage to per milion reads.
FALSE by default.}

\item{unique}{boolean which tells the function to remove duplicated reads
based on chr, start, end and strand}

\item{extend}{numeric which tells the function to extend the reads to width=extend}

\item{param}{ScanBamParam object}

\item{bam.paired.end}{boolean indicating whether given BAM file contains paired-end reads (default:FALSE).
Paired-reads will be treated as fragments.}

\item{stranded}{boolean which tells whether given BAM file is from a strand-specific protocol (default:TRUE). If FALSE then
                strands of reads will be set up to "*".}
}
\value{
returns a \code{scoreMatrix} object
}
\description{
The function firsts bins each window to equal number of bins, and calculates
the a summary metrix for scores of each bin (currently, mean, max and min supported)
A scoreMatrix object can be used to draw average profiles or heatmap of read coverage or wig track-like data.
\code{windows} can be a predefined region such as CpG islands or gene bodies that are not necessarily equi-width.
Each window will be chopped to equal number of bins based on \code{bin.num} option.
}
\examples{
#  data(cage)
#  data(cpgi)
#  data(promoters)
#  myMat=ScoreMatrixBin(target=cage,
#                      windows=cpgi,bin.num=10,bin.op="mean",weight.col="tpm")
# plot(colMeans(myMat,na.rm=TRUE),type="l")

# myMat2=ScoreMatrixBin(target=cage,
#                       windows=promoters,bin.num=10,bin.op="mean",
#                       weight.col="tpm",strand.aware=TRUE)
# plot(colMeans(myMat2,na.rm=TRUE),type="l")
}
\seealso{
\code{\link{ScoreMatrix}}
}