upsetCategory: UpSet plot to display measures values across sample types

In tnaake/MatrixQCvis: Shiny-based interactive data-quality exploration for omics data

UpSet plot to display measures values across sample types

Description

The function upsetCategory 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 measuredCategory 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

upsetCategory(se, category = colnames(colData(se)), measured = TRUE)

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)
measured	logical, should the measured values (measured = TRUE) or missing values (measured = FALSE) be taken

Details

Presence is defined by a feature being measured in at least one sample of a set.

Absence is defined by a feature with only missing values (i.e. no measured values) of a set.

Value

upset plot

Examples

## create se
a <- matrix(seq_len(100), nrow = 10, ncol = 10, 
            dimnames = list(seq_len(10), paste("sample", seq_len(10))))
a[c(1, 5, 8), seq_len(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)

upsetCategory(se, category = "type")

tnaake/MatrixQCvis documentation built on Nov. 4, 2024, 7:42 a.m.