coverage_to_dt | R Documentation |
Convert coverage RleList to data.table
coverage_to_dt(
coverage,
keep.names = TRUE,
withFrames = FALSE,
weight = "score",
drop.zero.dt = FALSE,
fraction = NULL
)
coverage |
RleList with names |
keep.names |
logical (TRUE), keep names or not. If as.data.table is TRUE, names (genes column) will be a factor column, if FALSE it will be an integer column (index of gene), so first input grl element is 1. Dropping names gives ~ 20 % speedup. If drop.zero.dt is FALSE, data.table will not return names, will use index (to avoid memory explosion). |
withFrames |
a logical (FALSE), only available if as.data.table is TRUE, return the ORF frame, 1,2,3, where position 1 is 1, 2 is 2 and 4 is 1 etc. |
weight |
(default: 'score'), if defined a character name of valid meta column in subject. GRanges("chr1", 1, "+", score = 5), would mean score column tells that this alignment region was found 5 times. Formats which loads a score column like this: Bigwig, wig, ORFik ofst, collapsed bam, bedoc and .bedo. As do CAGEr CAGE files and many other package formats. You can also assign a score column manually. |
drop.zero.dt |
logical FALSE, if TRUE and as.data.table is TRUE, remove all 0 count positions. This greatly speeds up and most importantly, greatly reduces memory usage. Will not change any plots, unless 0 positions are used in some sense. (mean, median, zscore coverage will only scale differently) |
fraction |
integer or character, a description column. Useful for grouping multiple outputs together. If returned as Rle, this is added as: metadata(coverage) <- list(fraction = fraction). If as.data.table it will be added as an additional column. |
a data.table with column names c("count" [numeric or integer], "genes" [integer], "position" [integer])
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