Plot normScore diagnostic items

Generates the set of diagnostic plots associated with the individual normScore evaluation items. These plots provide a visual interpretation of the criteria used to assess normalization performance, including raw total intensity, pooled coefficient of variation, within-group correlation, MA plots, mean-SD trends, RLE distributions, and intensity distributions.

Usage

plotNormScoreDiagnostics(
  normalizedDataList,
  groupData,
  rawData,
  refGroup = NULL,
  altGroup = NULL
)

Arguments

normalizedDataList

A named list of normalized data matrices or data frames. Each element should contain proteins in rows and samples in columns.

groupData

A data frame containing sample-group annotation. The first column is assumed to contain sample names and the second column group labels.

rawData

A matrix or data frame containing raw intensity values, with proteins in rows and samples in columns.

refGroup

Character string indicating the reference group used for the MA-plot diagnostic. If NULL, it is automatically selected.

altGroup

Character string indicating the alternative group used for the MA-plot diagnostic. If NULL, it is automatically selected.

Value

A named list of diagnostic plots. Each element corresponds to one normScore item. If the input contains a single group, the MA-plot element is returned as NULL.

Details

The function validates and aligns the input data before plotting. If only one group is provided, the MA-plot diagnostic is skipped because it requires a comparison between two groups.

Examples

# Simulate proteomic data
simData <- simulateData(nProteins = 1000)

# Normalyze ysing NormalyzerDE package
normalizedDataList <- list(
    Norm1 = simData$logData + 0.1,
    Norm2 = simData$logData + 1,
    Norm3 = simData$logData - 1,
    Norm4 = simData$logData * 1.1,
    Norm5 = simData$logData * 0.9,
    Norm6 = simData$logData * runif(ncol(simData$logData), 0.8, 1.2)
)

# Compute ranking
plotNormScoreDiagnostics(
    normalizedDataList = normalizedDataList,
    groupData = simData$metadata,
    rawData = simData$rawData,
    refGroup = NULL,
    altGroup = NULL
)
#> Reference group set to G2.
#> Alternative group set to G1.
#> Log2-transformed raw data were added to
#>             'normalizedDataList' as 'Log'.
#> $item0

#> 
#> $item1

#> 
#> $item2

#> 
#> $item3

#> 
#> $item4

#> 
#> $item5

#> 
#> $item6

#>