sbc_plot {pmp} | R Documentation

## Plot QCRSC corrected outputs

### Description

Plot the output from signal batch correction for the selected or the first 100 features.

### Usage

    sbc_plot(
      df,
      corrected_df,
      classes,
      batch,
      indexes = NULL,
      qc_label = "QC",
      output = "sbcms_plots.pdf"
    )

### Arguments

`df` | A matrix-like (e.g. an ordinary matrix, a data frame) or RangedSummarizedExperiment-class object with all values of class `numeric()` or `integer()` of peak intensities, areas or other quantitative characteristic.
`corrected_df` | Output from QCRSC function.
`classes` | `character()`, vector of class labels. Must be the same length as the number of sample in the input peak table. If input is `SummarizedExperiment` object, use `SummarizedExperiment_object$meta_data_column_name`.
`batch` | `numeric()` or `character()`, a vector indicating the batch each sample was measured in. If only one batch was measured then all values should be set to 1
`indexes` | `numeric()`, a vector defining which features to plot. If set to `NULL` will plot the first 100.
`qc_label` | `character(1)` or `NULL`, class label used to identify QC samples.
`output` | `character()`, a filename of the output pdf file. Can include the path. If set to `NULL` output will be list object containing class `ggplot` plots.

### Value

Pdf file or `list()` object `ggplot` class showing data before and after signal correction.

### Examples

    order <- c(1:ncol(MTBLS79))
    data <- MTBLS79[1:10, ]

    out <- QCRSC(df =data, order=order, batch=MTBLS79$Batch,
       classes=MTBLS79$Class, spar=0, minQC=4)
    plots <- sbc_plot (df=data, corrected_df=out, classes=MTBLS79$Class,
       batch=MTBLS79$Batch, output=NULL)

[Package pmp version 1.2.1 Index]