driftPlot {MatrixQCvis} | R Documentation

## 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(1:10, paste("sample", 1:100)))
    a[c(1, 5, 8), 1:5] <- 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")

[Package MatrixQCvis version 1.2.4 Index]