findoutliers: Inference of outlier cells and final clustering

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

Inference of outlier cells and final clustering

Description

This functions performs the outlier identification based on the clusters infered with the clustexp function.

Usage

findoutliers(
  object,
  probthr = 0.001,
  outminc = 5,
  outlg = 2,
  outdistquant = 0.95,
  verbose = TRUE
)

Arguments

object	SCseq class object.
probthr	outlier probability threshold for a minimum of outlg genes to be an outlier cell. This probability is computed from a negative binomial background model of expression in a cluster. Default is 0.001.
outminc	minimal transcript count of a gene in a clusters to be tested for being an outlier gene. Default is 5.
outlg	Minimum number of outlier genes required for being an outlier cell. Default is 2.
outdistquant	Real number between zero and one. Outlier cells are merged to outlier clusters if their distance smaller than the outdistquant-quantile of the distance distribution of pairs of cells in the orginal clusters after outlier removal. Default is 0.95.
verbose	logical. If FALSE then status output messages are disabled. Default is TRUE.

Value

SCseq object with outlier data stored in slot out and slot outlierpar. The final clustering partition is stored in cpart.

Examples

sc <- SCseq(intestinalDataSmall)
sc <- filterdata(sc)
sc <- compdist(sc)
sc <- clustexp(sc)
sc <- findoutliers(sc)

RaceID documentation built on Sept. 28, 2023, 5:06 p.m.