hist_feature_category {MatrixQCvis} | R Documentation |
The function 'hist_feature_category' creates histogram plots for each sample type in 'se'.
hist_feature_category(se, measured = TRUE, category = "type", ...)
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'. |
'plotly'
## 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")