projcells: Compute transcriptome entropy of each cell

In RaceID: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Compute transcriptome entropy of each cell

Description

This function computes the projections of cells onto inter-cluster links in a high-dimensional embedded space.

Usage

projcells(object, cthr = 5, nmode = TRUE, knn = 3, fr = FALSE, um = FALSE)

Arguments

object	Ltree class object.
cthr	Positive integer number. Clusters to be included into the StemID2 analysis must contain more than cthr cells. Default is 5.
nmode	logical. If TRUE, then a cell of given cluster is assigned to the link to the cluster with the smallest average distance of the knn nearest neighbours within this cluster. Default is TRUE.
knn	Positive integer number. See nmode. Default is 3.
fr	logical. Use Fruchterman-Rheingold layout instead of t-SNE for dimensional-reduction representation of the lineage graph. Default is FALSE.
um	logical. Use umap representation instead of t-SNE for dimensional-reduction representation of the lineage graph. Default is FALSE.

Value

An Ltree class object with all information on cell projections onto links stored in the ldata slot.

Examples

sc <- SCseq(intestinalDataSmall)
sc <- filterdata(sc)
sc <- compdist(sc)
sc <- clustexp(sc)
sc <- findoutliers(sc)
sc <- comptsne(sc)
ltr <- Ltree(sc)
ltr <- compentropy(ltr)
ltr <- projcells(ltr)

RaceID documentation built on May 29, 2024, 11:17 a.m.