Boxplots of the intensity data for each time point, condition, and replicate before and after variance stabilizing normalization (vsn). The function generates a ggplot object by default. An interactive plotly version (used on our Shiny application) is included if plotly = TRUE is set.
plotDistribution(
netPhorceData = netPhorceData,
condition = NULL,
plotly = FALSE
)(Required). Processed netPhorce Object
(Required). Select a specific condition from your experiment.
(Required). If TRUE, output an interactive plotly version, else output a static ggplot2 version.
a ggplot/plotly object
if (FALSE) {
## Loading Two Conditions Example
data("twoConditionsExample")
## Identify the Key Columns
identifiedCols <- confirmColumnNames(rawMaxQuant = twoConditionsExample,
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 = twoConditionsExample,
intensityPattern = "con_time_rep",
verbose = TRUE)
## Process the data based on the identified columns
netPhorceData <- processData(rawMaxQuant = twoConditionsExample,
processedColNames = identifiedCols,
processedIntensity = intensityCols,
minReplication = 3,
minLocalProb = 0.75)
## Generate Distribution Plot – GGPLOT version (Static)
plotDistribution(netPhorceData = netPhorceData,
condition = NULL,
plotly = FALSE)
## Generate Distribution Plot – PLOTLY version (Interactive)
plotDistribution(netPhorceData = netPhorceData,
condition = NULL,
plotly = TRUE)
}