A reimplementation of the Amulet doublet detection method for single-cell
ATACseq (Thibodeau, Eroglu, et al., Genome Biology 2021), based on tile/peak
counts. Note that this is only a fast approximation to the original Amulet
method, and *performs considerably worse*; for an equivalent implementation,
see amulet.
Usage
amuletFromCounts(x, maxWidth = 500L, exclude = c("chrM", "M", "Mt"))Arguments
- x
A `SingleCellExperiment` object, or a matrix of counts with cells as columns. If the rows represent peaks, it is recommended to limite their width (see details).
- maxWidth
the maximum width for a feature to be included. This is ignored unless `x` is a `SingleCellExperiment` with `rowRanges`.
- exclude
an optional `GRanges` of regions to be excluded. This is ignored unless `x` is a `SingleCellExperiment` with `rowRanges`.
Value
If `x` is a `SingleCellExperiment`, returns the object with an additional `amuletFromCounts.q` colData column. Otherwise returns a vector of the amulet doublet q-values for each cell.
Details
The rationale for the amulet method is that a single diploid cell should not have more than two reads covering a single genomic location, and the method looks for cells enriched with sites covered by more than two reads. If the method is applied on a peak-level count matrix, however, larger peaks can however contain multiple reads even though no single nucleotide is covered more than once. Therefore, in such case we recommend to limit the width of the peaks used for this analysis, ideally to maximum twice the upper bound of the fragment size. For example, with a mean fragment size of 250bp and standard deviation of 125bp, peaks larger than 500bp are very likely to contain non-overlapping fragments, and should therefore be excluded using the `maxWidth` argument.
Examples
x <- mockDoubletSCE()
x <- amuletFromCounts(x)
table(call=x$amuletFromCounts.q<0.05, truth=x$type)
#> truth
#> call singlet doublet
#> FALSE 500 0
#> TRUE 0 22