SignacX: CID.smooth – R documentation

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CID.smooth

Smoothing function

Description

CID.smooth uses k-nearest neighbors to identify cells which correspond to a different label than the majority of their first-degree neighbors. If so, those annotations are "smoothed."

Usage

CID.smooth(ac, dM)

Arguments

`ac`	list containing a character vector where each element is a cell type or cell state assignment.
`dM`	distance matrix (see ?CID.GetDistMat).

Value

A character vector with smoothed labels

Examples

## Not run: 
# load data classified previously (see SignacFast)
P <- readRDS("celltypes.rds")
S <- readRDS("pbmcs.rds")

# get edges from default assay from Seurat object
default.assay <- Seurat::DefaultAssay(S)
edges = S@graphs[[which(grepl(paste0(default.assay, "_nn"), names(S@graphs)))]]

# get distance matrix
D = CID.GetDistMat(edges)

# smooth labels
smoothed = CID.smooth(ac = P$CellTypes, dM = D[[1]])

## End(Not run)

SignacX

Cell Type Identification and Discovery from Single Cell Gene Expression Data

v2.2.0

GPL-3

Authors

Mathew Chamberlain [aut, cre], Virginia Savova [aut], Richa Hanamsagar [aut], Frank Nestle [aut], Emanuele de Rinaldis [aut], Sanofi US [fnd]

Initial release

2021-02-24