meansTest-methods: Linear model-based testing for summarized imaging experiments

In Cardinal: A mass spectrometry imaging toolbox for statistical analysis

Description

Performs hypothesis testing for imaging experiments by fitting linear mixed models to summarizations or segmentations.

Usage

## S4 method for signature 'SparseImagingExperiment'
meansTest(x, fixed, random, groups = run(x),
        BPPARAM = getCardinalBPPARAM(), ...)

## S4 method for signature 'SparseImagingExperiment'
segmentationTest(x, fixed, random, groups = run(x),
        classControl = c("Ymax", "Mscore"),
        BPPARAM = getCardinalBPPARAM(), ...)

## S4 method for signature 'SpatialDGMM'
segmentationTest(x, fixed, random, model = modelData(x),
        classControl = c("Ymax", "Mscore"),
        BPPARAM = getCardinalBPPARAM(), ...)

## S4 method for signature 'MeansTest'
summary(object, ..., BPPARAM = getCardinalBPPARAM())

## S4 method for signature 'SegmentationTest'
summary(object, ..., BPPARAM = getCardinalBPPARAM())

Arguments

x	An imaging dataset or segmented/summarized imaging dataset.
fixed	A one-sided formula giving the fixed effects of the model on the RHS. The response will added to the LHS, and the formula will be passed to the underlying modeling function.
random	A one-sided formula giving the random effects of the model on the RHS. See lme for the allowed specifications.
groups	The summarization units. Pixels from different groups will be segmented/summarized separately. Each distinct observational unit (e.g., tissue sample) should be assigned to a unique group.
model	An integer vector or list specifying which fitted model to plot. If this is an integer vector, it should give the rows indices of modelData(x) to use for plotting. Otherwise, it should be a list giving the values of parameters in modelData(x).
classControl	Either the method used to match segmented classes to the fixed effects, or a list where each element is a vector of name-value pairs giving the mapping between groups and classes (e.g., c(group1=class1, group2=class2, ...)). For automated matching methods, 'Ymax' means to use the classes with the highest mean response for each group, and 'Mscore' means to select classses based on a match score quantifying the overlap between classes and fixed effects.
...	Passed to internal linear modeling methods.
object	A fitted model object to summarize.
BPPARAM	An optional instance of BiocParallelParam. See documentation for bplapply.

Value

An object of class MeansTest or SegmentationTest, which is a ImagingResult, where each element of the resultData slot contains at least the following components:

model:

A linear model fitted using either lm or lme.

data:

The summarized data used to fit the model.

Author(s)

Dan Guo and Kylie A. Bemis

See Also

lm, lme, spatialDGMM

Examples

set.seed(1)
x <- simulateImage(preset=4, nruns=3, npeaks=10,
    dim=c(10,10), peakheight=5, peakdiff=2,
    representation="centroid")

groups <- replace(run(x), !(x$circleA | x$circleB), NA)

fit <- meansTest(x, ~ condition, groups=groups)

summary(fit)

Cardinal documentation built on Nov. 8, 2020, 11:10 p.m.