clamulet: clamulet

In plger/scDblFinder: scDblFinder

clamulet

Description

Classification-powered Amulet-like method

Usage

clamulet(
  x,
  artificialDoublets = NULL,
  iter = 2,
  k = NULL,
  minCount = 0.001,
  maxN = 500,
  nfeatures = 25,
  max_depth = 5,
  threshold = 0.75,
  returnAll = FALSE,
  verbose = TRUE,
  ...
)

Arguments

x	The path to a fragment file (see getFragmentOverlaps for performance/memory-related guidelines)
artificialDoublets	The number of artificial doublets to generate
iter	The number of learning iterations (should be 1 to)
k	The number(s) of nearest neighbors at which to gather statistics
minCount	The minimum number of cells in which a locus is detected to be considered. If lower than 1, it is interpreted as a fraction of the number of cells.
maxN	The maximum number of regions per cell to consider to establish windows for meta-features
nfeatures	The number of meta-features to consider
max_depth	The maximum tree depth
threshold	The score threshold used during iterations
returnAll	Logical; whether to return data also for artificial doublets
verbose	Logical; whether to print progress information
...	Arguments passed to getFragmentOverlaps

Details

'clamulet' operates similarly to the 'scDblFinder' method, but generates doublets by operating on the fragment coverages. This has the advantage that the number of loci covered by more than two reads can be computed for artificial doublets, enabling the use of this feature (along with the kNN-based ones) in a classification scheme. It however has the disadvantage of being rather slow and memory hungry, and appears to be outperformed by a simple p-value combination of the two methods (see vignette).

Value

A data.frame

plger/scDblFinder documentation built on March 20, 2024, 9:46 p.m.