Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/coverage.correlation.R
Visualization of target coverage correlations between pairs of samples.
1 2 | coverage.correlation(coveragelist, normalized = TRUE, plotfrac = 0.001, seed = 123, labels, main, pch = ".", cex.labels,
cex.pch = 2, cex.main = 1.2, cex.corr, font.labels = 1, font.main = 2, ...)
|
coveragelist |
List where each element is the output of function |
normalized |
if |
plotfrac |
numeric value between 0 and 1. Coverages for a fraction of |
seed |
seed for random selection of |
labels |
sample names that are written in the diagonal panels; if missing, names of |
main |
main title |
pch |
plot symbol for the scatter plots |
cex.labels, cex.pch, cex.main |
sizes of sample labels, plot symbols, main title |
cex.corr |
size of the correlation values; if missing, sizes are made proportionally to the values of (positive) correlation. |
font.labels, font.main |
fonts for sample labels and main title |
... |
further graphical parameters, e.g. limits and symbol color for the scatter plots |
If normalized = TRUE
, the function calculates normalized coverages: per-base coverages divided by
average coverage over all targeted bases. Normalized coverages are not dependent
on the absolute quantity of reads and are hence better comparable between different samples
or even different experiments.
'pairs'-style plot where upper panels show scatter plot of (a randomly chosen fraction of) coverage values for pairs of samples. The lower panels show the respective Pearson correlation coefficients, calculated using all coverage values (even if not all of them are shown in the scatter plot).
Manuela Hummel m.hummel@dkfz.de
coverage.target
, covered.k
, coverage.hist
,
coverage.density
, coverage.uniformity
, coverage.plot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## get reads and targets
exptPath <- system.file("extdata", package="TEQC")
readsfile <- file.path(exptPath, "ExampleSet_Reads.bed")
reads <- get.reads(readsfile, idcol=4, skip=0)
targetsfile <- file.path(exptPath, "ExampleSet_Targets.bed")
targets <- get.targets(targetsfile, skip=0)
## calculate per-base coverages
Coverage <- coverage.target(reads, targets, perBase=TRUE)
## simulate another sample
r <- sample(length(reads), 0.1 * length(reads))
reads2 <- reads[-r,,drop=TRUE]
Coverage2 <- coverage.target(reads2, targets, perBase=TRUE)
## coverage uniformity plot
covlist <- list(Coverage, Coverage2)
coverage.correlation(covlist, plotfrac=0.1)
|
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colMeans, colSums, colnames, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
setdiff, sort, table, tapply, union, unique, unsplit, which,
which.max, which.min
Loading required package: IRanges
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
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expand.grid
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: Biostrings
Loading required package: XVector
Attaching package: 'Biostrings'
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Loading required package: hwriter
[1] "read 19546 sequenced reads"
[1] "read 50 (non-overlapping) target regions"
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