upset_category {MatrixQCvis} | R Documentation

## UpSet plot to display measures values across sample types

### Description

The function 'upset_category' displays the frequency of measured values per feature with respect to class/sample type to assess difference in occurrences. Internally, the measured values per sample are obtained via the 'measured_category' function: this function will access the number of measured/missing values per category and feature. From this, a binary 'tbl' will be created specifying if the feature is present/missing, which will be given to the 'upset' function from the 'UpSetR' package.

### Usage

    upset_category(se, category = colnames(colData(se))[1], ...)

### Arguments

`se` | 'SummarizedExperiment', containing the intensity values in 'assay(se)', missing values are encoded by 'NA'
`category` | 'character', corresponding to a column in 'colData(se)'
`...` | additional parameters passed to 'measured_category'

### Value

'UpSet' plot

### Examples

    ## create se
    a <- matrix(1:100, nrow = 10, ncol = 10,
                dimnames = list(1:10, paste("sample", 1:10)))
    a[c(1, 5, 8), 1:5] <- NA
    set.seed(1)
    a <- a + rnorm(100)
    cD <- data.frame(name = colnames(a), type = c(rep("1", 5), rep("2", 5)))
    rD <- data.frame(spectra = rownames(a))
    se <- SummarizedExperiment::SummarizedExperiment(assay = a,
        rowData = rD, colData = cD)

    upset_category(se, category = "type")

[Package MatrixQCvis version 1.2.4 Index]