genoset (version 1.28.2)

segTable: Convert Rle objects to tables of segments

Description

Like the inverse of segs2Rle and segs2RleDataFrame. Takes a Rle or a RleDataFrame and the rowRanges both from a GenoSet object and makes a list of data.frames each like the result of CBS's segment. Note the loc.start and loc.stop will correspond exactly to probe locations in rowRanges and the input to segs2RleDataFrame are not necessarily so. For a DataFrame, the argument stack combines all of the individual data.frames into one large data.frame and adds a "Sample" column of sample ids.

Usage

segTable(object, ...)
## S3 method for class 'Rle':
segTable(object, locs = NULL, chr.ind = NULL,
  start = NULL, end = NULL, factor.chr = TRUE)
## S3 method for class 'DataFrame':
segTable(object, locs, factor.chr = TRUE,
  stack = FALSE)

Arguments

object

Rle or RleDataFrame

...

in generic, for extra args in methods

locs

GenomicRanges with rows corresponding to rows of df

chr.ind

matrix, like from chrIndices method

start

integer, vector of feature start positions

end

integer, vector of feature end positions

factor.chr

scalar logical, make 'chrom' column a factor?

stack

logical, rbind list of segment tables for each sample and add "Sample" column?

Value

• one or a list of data.frames with columns chrom, loc.start, loc.end, num.mark, seg.mean

Details

For a Rle, the user can provide locs or chr.ind, start and stop. The latter is surprisingly much faster and this is used in the DataFrame version.

See Also

Other "segmented data": bounds2Rle, rangeSegMeanLength, runCBS, segPairTable, segs2Granges, segs2RleDataFrame, segs2Rle

Examples

data(genoset,package="genoset")
  seg.list = runCBS( genoset.ds[, , "lrr"], rowRanges(genoset.ds), return.segs=TRUE )
  df = segs2RleDataFrame( seg.list, rowRanges(genoset.ds) )  # Loop segs2Rle on list of data.frames in seg.list
  genoset.ds[ , , "lrr.segs"] = df
  segTable( df, rowRanges(genoset.ds) )
  segTable( genoset.ds[ , , "lrr.segs"], rowRanges(genoset.ds) )
  segTable( genoset.ds[ , 1, "lrr.segs"], rowRanges(genoset.ds), colnames(genoset.ds)[1] )