createPPlotScores: Evaluate assumptions of the Target Decoys Approach for...

In statOmics/TargetDecoy: Diagnostic Plots to Evaluate the Target Decoy Approach

Evaluate assumptions of the Target Decoys Approach for multiple search engines

Description

Create diagnostic PP plots in one figure to evaluate the TDA assumptions for multiple search engines. The function provides the possibility to evaluate each of the sub-engines and the overall itself.

Usage

createPPlotScores(object, scores, decoy, log10 = TRUE)

Arguments

object	A data.frame, mzID or mzRident object.
scores	A character vector of multiple score names from the input object. Typically from different search engines.
decoy	character, name of the variable that indicates if the peptide matches to a target or to a decoy. When this value is missing, a Shiny gadget is launched to select it interactively.
log10	logical to indicate if the score should be -log10-transformed. Default: TRUE. When this value is missing, a Shiny gadget is launched to select it interactively.

Value

One PP plot with all original pi0, and a standardized / rescaled PP plot with all pi0 set to 0.

Author(s)

Elke Debrie, Lieven Clement

Examples

library(mzID)

## Use one of the example files in the mzID package
exampleFile <- system.file("extdata", "55merge_tandem.mzid", package = "mzID")
mzIDexample <- mzID(exampleFile)

plots <- createPPlotScores(mzIDexample,
    scores = c("x\\!tandem:hyperscore", "x\\!tandem:expect"),
    decoy = "isdecoy", log10 = TRUE
)

statOmics/TargetDecoy documentation built on Nov. 9, 2022, 9:30 a.m.