topFeatures-methods {Cardinal} | R Documentation

## Top-ranked features from imaging analysis results

### Description

Extract the top-ranked features from the results of imaging analysis, based on post-hoc correlation, test statistics, p-values, or adjusted p-values. The result is sorted data frame that can be further manipulated for downstream postprocessing.

### Usage

    #### Methods for Cardinal >= 2.x classes ####

    ## S4 method for signature 'SpatialShrunkenCentroids2'
    topFeatures(object, ..., n = 10, model = modelData(object))

    ## S4 method for signature 'SpatialKMeans2'
    topFeatures(object, ..., n = 10, model = modelData(object))

    ## S4 method for signature 'MeansTest'
    topFeatures(object, ..., n = 10, p.adjust = "BH")

    ## S4 method for signature 'SegmentationTest'
    topFeatures(object, ..., n = 10, model = modelData(object), p.adjust = "BH")

    #### Methods for Cardinal 1.x classes ####

    ## S4 method for signature 'ResultSet'
    topFeatures(object, n = 6,
        model = pData(modelData(object)),
        type = c('+', '-', 'b'),
        sort.by = fvarLabels(object),
        filter = list(),
        ...)

    ## S4 method for signature 'PCA'
    topFeatures(object, n = 6,
        sort.by = "loadings",
        ...)

    ## S4 method for signature 'PLS'
    topFeatures(object, n = 6,
        sort.by = c("coefficients", "loadings", "weights"),
        ...)

    ## S4 method for signature 'OPLS'
    topFeatures(object, n = 6,
        sort.by = c("coefficients",
                "loadings", "Oloadings",
                "weights", "Oweights"),
        ...)

    ## S4 method for signature 'SpatialKMeans'
    topFeatures(object, n = 6,
        sort.by = c("betweenss", "withinss"),
        ...)

    ## S4 method for signature 'SpatialShrunkenCentroids'
    topFeatures(object, n = 6,
        sort.by = c("tstatistics", "p.values"),
        ...)

    ## S4 method for signature 'CrossValidated'
    topFeatures(object, ...)

### Arguments

`object` | The results of an imaging experiment analysis.
`n` | The number of top-ranked records to return.
`model` | If more than one model was fitted, results from which should be shown? Defaults to all models in the object This can name the models explicitly or specify a list of parameter values.
`p.adjust` | The `p.adjust` method used adjust p-values to account for multiple testing. Defaults to Benjamini \& Hochberg ("BH") to control the false discovery rate (FDR).
`...` | For newer classes, additional arguments to be passed to `filter`, to further filter the results.
`type` | How should the records be ranked? '+' shows greatest values first (decreasing order), '-' shows least values first (increasing order), and 'b' uses decreasing order based on absolute values.
`sort.by` | What variable should be used for sorting?
`filter` | A list of named variables with values to use to filter the results. For example, for testing or classification, this can be used to only show rankings for a particular condition.

### Value

A data frame with the top-ranked features.

### Author(s)

Kylie A. Bemis

### See Also

`meansTest`, `segmentationTest`, `spatialShrunkenCentroids`

### Examples

    setCardinalBPPARAM(SerialParam())

    set.seed(1)
    x <- simulateImage(preset=2, npeaks=10, dim=c(10,10),
        snoise=1, sdpeaks=1, representation="centroid")

    y <- makeFactor(circle=pData(x)$circle, square=pData(x)$square)

    res <- spatialShrunkenCentroids(x, y, r=1, s=c(0,3,6))

    topFeatures(res, model=list(s=6))

[Package Cardinal version 2.6.0 Index]