subsampleBySpikeIn {BRGenomics} | R Documentation |
Randomly subsample reads according to spike-in normalization
subsampleBySpikeIn( dataset.gr, si_pattern = NULL, si_names = NULL, ctrl_pattern = NULL, ctrl_names = NULL, batch_norm = TRUE, RPM_units = FALSE, field = "score", sample_names = NULL, expand_ranges = FALSE, ncores = getOption("mc.cores", 2L) )
dataset.gr, si_pattern, si_names, ctrl_pattern, ctrl_names, batch_norm, field, sample_names, expand_ranges, ncores |
See |
RPM_units |
If set to |
Note that if field = NULL
,
An object parallel to dataset.gr
, but with fewer reads. E.g.
if dataset.gr
is a list of GRanges, the output is a list of the same
GRanges, but in which each GRanges has fewer reads.
Mike DeBerardine
getSpikeInCounts
,
getSpikeInNFs
#--------------------------------------------------# # Make list of dummy GRanges #--------------------------------------------------# gr1_rep1 <- GRanges(seqnames = c("chr1", "chr2", "spikechr1", "spikechr2"), ranges = IRanges(start = 1:4, width = 1), strand = "+") gr2_rep2 <- gr2_rep1 <- gr1_rep2 <- gr1_rep1 # set readcounts score(gr1_rep1) <- c(1, 1, 1, 1) # 2 exp + 2 spike = 4 total score(gr2_rep1) <- c(2, 2, 1, 1) # 4 exp + 2 spike = 6 total score(gr1_rep2) <- c(1, 1, 2, 1) # 2 exp + 3 spike = 5 total score(gr2_rep2) <- c(4, 4, 2, 2) # 8 exp + 4 spike = 12 total grl <- list(gr1_rep1, gr2_rep1, gr1_rep2, gr2_rep2) names(grl) <- c("gr1_rep1", "gr2_rep1", "gr1_rep2", "gr2_rep2") grl #--------------------------------------------------# # (The simple spike-in NFs) #--------------------------------------------------# # see examples for getSpikeInNFs for more getSpikeInNFs(grl, si_pattern = "spike", ctrl_pattern = "gr1", method = "SNR", ncores = 1) #--------------------------------------------------# # Subsample the GRanges according to the spike-in NFs #--------------------------------------------------# ss <- subsampleBySpikeIn(grl, si_pattern = "spike", ctrl_pattern = "gr1", ncores = 1) ss lapply(ss, function(x) sum(score(x))) # total reads in each # Put in units of RPM for the negative control ssr <- subsampleBySpikeIn(grl, si_pattern = "spike", ctrl_pattern = "gr1", RPM_units = TRUE, ncores = 1) ssr lapply(ssr, function(x) sum(score(x))) # total signal in each