initialBead: Preliminary bead classification

In jillbo1000/cytofQC: Labels normalized cells for CyTOF data and assigns probabilities for each label

Preliminary bead classification

Description

Preliminary bead classification

Usage

initialBead(x)

Arguments

x	A SingleCellExperiment created with readCytof.

Details

The beads are typically the first cell classification that is done. The different event types are labeled iteratively so the labels vector in the colData will contain all of the labels and probabilities computed up to this point. Only events that have a "cell" label can be assigned an initial event classification of "bead". This function computes a score that assesses how much an event looks like a bead and then fits a mixture model to assign each event a class of 1 for a bead, -1 for an event that is not a bead, or 0 for undetermined or previously assigned to a different event type. The score is recorded in the score object in the colData and the initial classification is recorded in the initial part of the colData.

Each bead channel should classify into two fairly clear groups where one is the beads and the other is non-beads. A histogram of the bead score should show a clear, small peak that represents the beads.

Value

A SingleCellExperiment that contains the bead score and the bead designation for each event. This information is stored in the score and initial objects in the colData for the SingleCellExperiment.

Examples

data("raw_data", package = "CATALYST")
sce <- readCytof(raw_data, beads = 'Beads', viability = c('cisPt1','cisPt2'))
sce <- initialBead(sce)
head(scores(sce))
head(initial(sce))

jillbo1000/cytofQC documentation built on Aug. 23, 2023, 9:47 p.m.