plotInitialGuess: Plot preliminary classification from initialGuess

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

Plot preliminary classification from initialGuess

Description

Plot preliminary classification from initialGuess

Usage

plotInitialGuess(
  x,
  IG = NULL,
  fit = NULL,
  type = c("both", "full", "truncated")
)

Arguments

x	The score (ie. debris score, doublet score, etc.) to be used for predicting each event's label (eg. "doublet" vs. "cell").
IG	If NULL, the function initialGuess is used to fit a mixture of normal distributions. Otherwise, a numeric vector can be passed to the function that contains the fitted values.
fit	If left blank or NULL, the best fit as determined by BIC will be plotted. Otherwise, a numeric value of 1, 2, or 3 can be be selected to plot single normal fit, mixture of two normals, or the mixture of three normals as fit by initialGuess.
type	Type of graph to be plotted. If 'truncated' is selected, only half of the first normal distribution will be plotted. If 'both' is selected, both the truncated and full plot will be plotted.

Value

A histogram that shows the score with the mixture of normal distributions overlayed.

Examples

data("raw_data", package = "CATALYST")
sce <- readCytof(raw_data, beads = "Beads", viability = c("cisPt1", "cisPt2"))
sce <- initialDoublet(sce)
plotInitialGuess(scores(sce, "doublet"), type = "both")
plotInitialGuess(scores(sce, "doublet"), type = "truncated")

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