Initial processing and quality control of MaxQuant data including the removal of contaminated and reverse peptides, unnecessary columns, and invalid peptides based on filtering criteria.

The function combines the raw MaxQuant data, and the outputs from confirmIntensityColumns and confirmColumnNames to form a netPhorce-class object.

processData(
  rawMaxQuant = rawMaxQuant,
  processedColNames = processedColNames,
  processedIntensity = intensity,
  minReplication = minReplication,
  minLocalProb = minLocalProb
)

Arguments

rawMaxQuant: (Required). Loaded MaxQuant data
processedColNames: (Required). Processed required columns from confirmColumnNames function.
processedIntensity: (Required). Processed required intensity columns from the confirmIntensityColumns function.
minReplication: (Required). The minimal number of valid replicate data points or replicate zeros per sample a peptide should contain across the entire time course and experiment. Peptides that do not meet these criteria are filtered out.
minLocalProb: (Required). The minimal localization probability required for a peptide to be included in downstream analyses.

Value

The netPhorce object with the following slots:

Design: Contains data design information and filtering parameters
data.filtered: Contains all the data points in a Long format that passed filtering criteria.
data.filtered.aov.summary: Contains the anova results in a Long format .
Misc: Contains accessory data including default plotting colors and FASTA Keys, if present.

Examples

if (FALSE) {
## Loading One Condition Data
data("oneConditionExample")
## Identify the Key Columns
identifiedCols <- confirmColumnNames(rawMaxQuant = oneConditionExample,
                                      positionCol = "Position",
                                      reverseCol = "Reverse",
                                      localizationProbCol = "Localization prob",
                                      potentialContaminationCol = "Potential contaminant",
                                      aminoAcidCol = "Amino acid",
                                     uniqueIDCol = "Protein",
                                      seqWindowIDCol = "Sequence window",
                                      fastaIDCol = "Fasta headers")
## Identify the Intensity Columns with Condition, Time Point and Replication Information
intensityCols <- confirmIntensityColumns(rawMaxQuant = oneConditionExample,
                                         intensityPattern = "con_time_rep",
                                         verbose = TRUE)
## Process the data based on the identified columns
netPhorceData <- processData(rawMaxQuant = oneConditionExample,
                             processedColNames = identifiedCols,
                             processedIntensity = intensityCols,
                             minReplication = 3,
                             minLocalProb = 0.75)
}