messina (version 1.8.2)

plot,MessinaClassResult,missing-method: Plot the results of a Messina analysis on a classification / differential expression problem.

Description

Produces a separate plot for each supplied feature index (either as an index into the expression data x as-supplied, or as an index into the features sorted by Messina margin, depending on the value of sort_features), showing sample expression levels, group membership, threshold value, and margin locations. Two different types of plots can be produced. See the vignette for examples.

Usage

## S3 method for class 'MessinaClassResult,missing':
plot(x, y, ...)

Arguments

x

the result of a Messina analysis, as returned by functions messina or messinaDE.

...

additional options to control the plot: [object Object],[object Object],[object Object]

y

the y coordinates of points in the plot, optional if x is an appropriate structure.

See Also

MessinaClassResult-class

messina

messinaDE

Examples

## Load some example data
library(antiProfilesData)
data(apColonData)

x = exprs(apColonData)
y = pData(apColonData)$SubType

## Subset the data to only tumour and normal samples
sel = y %in% c("normal", "tumor")
x = x[,sel]
y = y[sel]

## Run Messina to rank probesets on their classification ability, with
## classifiers needing to meet a minimum sensitivity of 0.95, and minimum
## specificity of 0.85.
fit = messina(x, y == "tumor", min_sens = 0.95, min_spec = 0.85)

## Make bar plots of the five best fits
plot(fit, indices = 1:5, sort_features = TRUE, plot_type = "bar")

## Make a point plot of the fit to the 10th feature
plot(fit, indices = 10, sort_features = FALSE, plot_type = "point")