R/CNVMetricsMethods.R
calculateLog2ratioMetric.RdThis function calculates a specific metric, as specified by the user, using overlapping amplified/deleted regions between to samples. The metric is calculated for the amplified and deleted regions separately. When more than 2 samples are present, the metric is calculated for each sample pair.
calculateLog2ratioMetric(
segmentData,
method = c("weightedEuclideanDistance"),
minThreshold = 0.2,
excludedRegions = NULL,
nJobs = 1
)a GRangesList that contains a collection of
genomic ranges representing copy number events, including amplified/deleted
status, from at least 2 samples. All samples must have a metadata column
called 'log2ratio' with the log2ratio values.
a character string representing the metric to be used.
This should be (an unambiguous abbreviation of) one of
"weightedEuclideanDistance". Default: "weightedEuclideanDistance".
a single positive numeric setting the minimum
value to consider two segments as different during the metric calculation.
If the absolute difference is below or equal to threshold, the difference
will be replaced by zero. Default: 0.2.
an optional GRanges containing the regions
that have to be excluded for the metric calculation. Default: NULL.
a single positive integer specifying the number of
worker jobs to create in case of distributed computation.
Default: 1 and always 1 for Windows.
an object of class "CNVMetric" which contains the calculated
metric. This object is a list with the following components:
LOG2RATIO a lower-triangular matrix with the
results of the selected metric on the log2ratio values for each paired
samples. The value NA is present when the metric cannot be
calculated. The value NA is also present in the top-triangular
section, as well as the diagonal, of the matrix.
The object has the following attributes (besides "class" equal to "CNVMetric"):
metric the metric used for the calculation.
names the names of the two matrix containing the metrics for
the amplified and deleted regions.
The weighted euclidean distance is
\((\sum((x_i - y_i)^2 * log(nbrBases_i))^0.5\)
where x and y are the
values of 2 samples for a specific segment i and nbrBases the
number of bases of the segment i.
## Load required package to generate the samples
require(GenomicRanges)
## Create a GRangesList object with 3 samples
## The stand of the regions doesn't affect the calculation of the metric
demo <- GRangesList()
demo[["sample01"]] <- GRanges(seqnames="chr1",
ranges=IRanges(start=c(1905048, 4554832, 31686841),
end=c(2004603, 4577608, 31695808)), strand="*",
log2ratio=c(2.5555, 1.9932, -0.9999))
demo[["sample02"]] <- GRanges(seqnames="chr1",
ranges=IRanges(start=c(1995066, 31611222, 31690000),
end=c(2204505, 31689898, 31895666)), strand=c("-", "+", "+"),
log2ratio=c(0.3422, 0.5454, -1.4444))
## The amplified region in sample03 is a subset of the amplified regions
## in sample01
demo[["sample03"]] <- GRanges(seqnames="chr1",
ranges=IRanges(start=c(1906069, 4558838),
end=c(1909505, 4570601)), strand="*",
log2ratio=c(3.2222, -1.3232))
## Calculating Sorensen metric
calculateLog2ratioMetric(demo, method="weightedEuclideanDistance", nJobs=1)
#> CNV Metrics
#> Metric:
#> weightedEuclideanDistance
#>
#> LOG2RATIO:
#> sample01 sample02 sample03
#> sample01 NA NA NA
#> sample02 0.06414725 NA NA
#> sample03 0.07458553 NA NA
#>