driftPlot: Plot the trend line for aggregated values

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

Plot the trend line for aggregated values

Description

The function driftPlot aggregates the (count/intensity) values from the assay() slot of a SummarizedExperiment by the median or sum of the (count/intensity) values. driftPlot then visualizes these aggregated values and adds a trend line (using either LOESS or a linear model) from (a subset of) the aggregated values. The subset is specified by the arguments category and level.

Usage

driftPlot(
  se,
  aggregation = c("median", "sum"),
  category = colnames(colData(se)),
  orderCategory = colnames(colData(se)),
  level = c("all", unique(colData(se)[, category])),
  method = c("loess", "lm")
)

Arguments

se	SummarizedExperiment
aggregation	character, type of aggregation of (count/intensity) values
category	character, column of colData(se)
orderCategory	character, column of colData(se)
level	character, from which samples should the LOESS curve be calculated, either "all" or one of the levels of the selected columns of colData(se) ("category")
method	character, either "loess" or "lm"

Details

The x-values are sorted according to the orderCategory argument: The levels of the corresponding column in colData(se) are pasted with the sample names (in the column name) and factorized. Internal usage in shinyQC.

Value

gg object from ggplot2

Examples

#' ## create se
set.seed(1)
a <- matrix(rnorm(1000), nrow = 10, ncol = 100, 
    dimnames = list(seq_len(10), paste("sample", seq_len(100))))
a[c(1, 5, 8), seq_len(5)] <- NA
cD <- data.frame(name = colnames(a), type = c(rep("1", 50), rep("2", 50)))
rD <- data.frame(spectra = rownames(a))
se <- SummarizedExperiment::SummarizedExperiment(assay = a, 
    rowData = rD, colData = cD)

driftPlot(se, aggregation = "sum", category = "type", 
    orderCategory = "type", level = "1", method = "loess")

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