hist_feature_category {MatrixQCvis}

R Documentation

Histogram of features per sample type

Description

The function 'hist_feature_category' creates histogram plots for each sample type in 'se'.

Usage

hist_feature_category(se, measured = TRUE, category = "type", ...)

Arguments

se	'SummarizedExperiment', the assay slot contains the intensity values per sample. Missing values are encoded as 'NA'.
measured	'logical', should the measured values ('measured = TRUE') or missing values ('measured = FALSE') be taken
category	'character', corresponding to a column in 'colData(se)'
...	additional parameters passed to 'geom_histogram', e.g. 'binwidth'.

Value

'plotly' object from 'ggplotly'

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)

hist_feature_category(se, measured = TRUE, category = "type")

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