This function calculates overlap for all sample-pairs
in a SummarizedExperiment
object.
calculateOverlap(
x,
assay.type = assay_name,
assay_name = "counts",
detection = 0,
...
)
# S4 method for SummarizedExperiment
calculateOverlap(
x,
assay.type = assay_name,
assay_name = "counts",
detection = 0,
...
)
runOverlap(x, ...)
# S4 method for SummarizedExperiment
runOverlap(x, name = "overlap", ...)a
SummarizedExperiment
object containing a tree.
A single character value for selecting the
assay
to calculate the overlap.
a single character value for specifying which
assay to use for calculation.
(Please use assay.type instead. At some point assay_name
will be disabled.)
A single numeric value for selecting detection threshold for absence/presence of features. Feature that has abundance under threshold in either of samples, will be discarded when evaluating overlap between samples.
Optional arguments not used.
A single character value specifying the name of overlap matrix that is stored in reducedDim(x).
calculateOverlap returns sample-by-sample distance matrix.
runOverlap returns x that includes overlap matrix in its
reducedDim.
These function calculates overlap between all the sample-pairs. Overlap reflects similarity between sample-pairs.
When overlap is calculated using relative abundances, the higher the value the higher the similarity is, When using relative abundances, overlap value 1 means that all the abundances of features are equal between two samples, and 0 means that samples have completely different relative abundances.
data(esophagus)
tse <- esophagus
tse <- transformAssay(tse, method = "relabundance")
overlap <- calculateOverlap(tse, assay_name = "relabundance")
overlap
#> B C
#> C 0.8811552
#> D 0.9038734 0.8390008
# Store result to reducedDim
tse <- runOverlap(tse, assay.type = "relabundance", name = "overlap_between_samples")
head(reducedDims(tse)$overlap_between_samples)
#> B C D
#> B 0.0000000 0.8811552 0.9038734
#> C 0.8811552 0.0000000 0.8390008
#> D 0.9038734 0.8390008 0.0000000