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 = "type", ...)

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 1.0.0 Index]