ScoreMatrixList-methods: Make ScoreMatrixList from multiple targets
In BIMSBbioinfo/genomation: Summary, annotation and visualization of genomic data

Description Usage Arguments Value Examples

The function constructs a list of ScoreMatrix objects in the form of ScoreMatrixList object. This object can be visualized using multiHeatMatrix, heatMeta or plotMeta

ScoreMatrixList(targets, windows = NULL, bin.num = NULL, bin.op = "mean",
  strand.aware = FALSE, weight.col = NULL, is.noCovNA = FALSE,
  type = "auto", rpm = FALSE, unique = FALSE, extend = 0,
  param = NULL, library.size = NULL, cores = 1)

`targets`	can be a list of `scoreMatrix` objects, that are coerced to the `ScoreMatrixList`, a list of `RleList` objects, or a character vector specifying the locations of mulitple bam files or bigWig files that are used to construct the `scoreMatrixList`. If it is either a RleList object or a character vector of files, it is obligatory to give a windows argument.
`windows`	`GenomicRanges` containing viewpoints for the scoreMatrix or ScoreMatrixList functions
`bin.num`	an integer telling the number of bins to bin the score matrix
`bin.op`	an name of the function that will be used for smoothing windows of ranges
`strand.aware`	a boolean telling the function whether to reverse the coverage of ranges that come from - strand (e.g. when plotting enrichment around transcription start sites)
`weight.col`	if the object is `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.
`is.noCovNA`	(Default:FALSE) if TRUE,and if 'targets' 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.
`type`	(Default:"auto") if `targets` is a character vector of file paths, then type designates the type of the corresponding files (bam or bigWig)
`rpm`	boolean telling whether to normalize the coverage to per milion reads. FALSE by default. See `library.size`.
`unique`	boolean which tells the function to remove duplicated reads based on chr, start, end and strand
`extend`	numeric which tells the function to extend the features ( i.e aligned reads) to total length ofwidth+extend
`param`	ScanBamParam object
`library.size`	a numeric vector of the same length as `targets` indicating total number of mapped reads in BAM files (`targets`). If is not given (default: NULL) then library sizes for every target is calculated using the Rsamtools idxstatsBam function: sum(idxstatsBam(target)$mapped). `rpm` argument has to be set to TRUE.
`cores`	the number of cores to use (default: 1)

returns a ScoreMatrixList object

# visualize the distribution of cage clusters and cpg islands around promoters
library(GenomicRanges)
data(cage)
data(cpgi)
data(promoters)
 
cage$tpm = NULL
targets = GRangesList(cage=cage, cpgi=cpgi)
sml = ScoreMatrixList(targets, promoters, bin.num=10, strand.aware=TRUE)
sml

multiHeatMatrix(sml)