segTable {genoset} | R Documentation |
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.
segTable(object, ...) ## S4 method for signature 'Rle' segTable(object, locs = NULL, chr.ind = NULL, start = NULL, end = NULL, factor.chr = TRUE) ## S4 method for signature 'DataFrame' segTable(object, locs, factor.chr = TRUE, stack = FALSE)
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? |
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.
one or a list of data.frames with columns chrom, loc.start, loc.end, num.mark, seg.mean
Other 'segmented data': bounds2Rle
,
rangeSegMeanLength
, runCBS
,
segPairTable
, segs2Granges
,
segs2RleDataFrame
, segs2Rle
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] )