protiq (version 1.2)

scampiVal-class: Class "scampiVal"

Description

This class of objects is returned by the functions runScampi and iterateScampi to contain the estimated protein abundances (and optionally the peptie abundance reassessment). Objects of this class have methods for the functions summary, show and plot.

Creation of objects

Objects are typically generated by calls to the functions runScampi and iterateScampi (in latter the scampiVal class object is in a nested list).

Slots

call:

Object of the class "call": the original function call.

parameters:

Object of class "list": list of estimated model parameter values, each list element corresponds to a different estimation method.

ppGraph:

Object of class "graphNEL": the bipartite undirected graph with peptides and proteins underlying the comuptations.

ccList:

Object of class "list": list of connected components (with some pre-processed properties) of ppGraph underlying the computations.

peptides:

Object of class "data.frame": dataframe summarizing information about the peptides (input data as well as (optionally) reassessed abundances).

proteins:

Object of class "data.frame": dataframe summarizing information about the proteins (input data as well as estimated protein abundances).

edgespp:

Object of class "data.frame": dataframe summarizing the information about the edges of ppGraph, connecting the peptides to the proteins.

Extends

Class scampi, directly.

Methods

plot

signature(x = "scampiVal", y = "missing"): For each parameter estimation method, plot the distribution of the computed protein abundance scores (histogram). If the peptide score reassessment was performed, also display a Tukey-Anscombe and Normal Q-Q plot for the peptide residuals.

show

signature(object = "scampiVal"): Display basic properties of the fitted object

summary

signature(object = "scampiVal"): Display details of the fitted object

See Also

runScampi, iterateScampi

Examples

showClass("scampiVal")

## generate a scampiVal object
data("leptoSRM")
scampiRes <- runScampi(peptides=leptoSRMpeptides, 
                       proteins=leptoSRMproteins, 
                       edgespp=leptoSRMedgespp, 
                       rescaling=FALSE, method="LSE", 
                       quantifyPeptides=FALSE)

## use methods of class scampiVal
show(scampiRes)
summary(scampiRes)
plot(scampiRes)