sbc_plot: Plot QCRSC corrected outputs

In computational-metabolomics/pmp: Peak Matrix Processing and signal batch correction for metabolomics datasets

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) 

computational-metabolomics/pmp documentation built on April 30, 2022, 4:28 a.m.