RleDataFrame-views: Calculate summary statistics on views of an RleDataFrame
In genoset: A RangedSummarizedExperiment with methods for copy number analysis

Description Usage Arguments Details Value See Also Examples

These methods mirror the viewMeans type functions from IRanges for SimpleRleList. They differ in that they work on an RleDataFrame and an IRanges directly and also have a simplify argument. This works out to be faster (compute-wise) and also convenient.

Still, an RleDataFrame inherits from SimpleRleList, so all of the views functions will work.

rangeSums(x, bounds, na.rm=FALSE, simplify=TRUE)
rangeMeans(x, bounds, na.rm=FALSE, simplify=TRUE, ...)
rangeMins(x, bounds, na.rm=FALSE, simplify=TRUE)
rangeMaxs(x, bounds, na.rm=FALSE, simplify=TRUE)
rangeWhichMins(x, bounds, na.rm=FALSE, simplify=TRUE)
rangeWhichMaxs(x, bounds, na.rm=FALSE, simplify=TRUE)

`x`	RleDataFrame
`bounds`	Matrix with two columns or IRanges representing ranges of rows of `x` to process. If `bounds` is a matrix, an IRanges is constructed assuming the first two columns represent the start and end of the ranges. The names for the IRanges is taken from the rownames of the matrix. Such a matrix can constructed with `boundingIndicesByChr` and is the preferred input.
`na.rm`	Scalar logical. Ignore NAs in calculations?
`simplify`	Scalar logical. Simplify result? If TRUE, the return value will be a vector or matrix. For a single view, a vector will be returned. Otherwise a matrix with one row per view and one column per column of x will be returned. If FALSE, the return value will be a list of length `ncol(x)` of vectors of length `nrow(bounds)`.
`...`	Additional arguments for other methods.

The "range" name prefixes here serve to differentiate these functions from the "view" functions. This may change. I will be asking the IRanges team to add "..." and "simplify" to the "view" methods so that I can just make additional methods for RleDataFrame.

With simplify == TRUE, a vector for single view or a matrix otherwise. When simplify == FALSE, a list of vectors length ncol(x) where each element is of length nrows(bounds).

RleDataFrame boundingIndicesByChr

df = RleDataFrame(list(a=Rle(1:5, rep(2, 5))), b=Rle(1:5, rep(2, 5)),
row.names=LETTERS[1:10])
mat = matrix(c(1,4,3,5),ncol=2,dimnames=list(c("Gene1","Gene2"),c("start","end")))
bounds = IRanges(start=c(1, 4), end=c(3, 5), names=c("Gene1","Gene2"))

rangeMeans(df,bounds,simplify=FALSE)
rangeMeans(df,bounds,simplify=TRUE)
rangeMeans(df,mat,simplify=TRUE)

rangeMeans(df,bounds)
rangeSums(df,bounds)
rangeMins(df,bounds)
rangeMaxs(df,bounds)
rangeWhichMins(df,bounds)
rangeWhichMaxs(df,bounds)

# RleDataFrame isa SimpleRleList, so all the IRanges view* methods work too:
v = RleViewsList( lapply( df, Views, start=bounds ) )
viewMeans(v)