DS5RPPAPreFitQC-class {RPPASPACE}

Class “DS5RPPAPreFitQC”

Description

The DS5RPPAPreFitQC class represents the inputs necessary to determine the quality control rating of a reverse-phase protein array slide with 5 dilution series.

Usage

## S4 method for signature 'DS5RPPAPreFitQC'
qcprob(object, ...)
## S4 method for signature 'DS5RPPAPreFitQC'
summary(object, ...)

Arguments

object

object of class DS5RPPAPreFitQC

...

extra arguments for generic routines

Details

The prediction model used multiple training datasets from the RPPA Core Facility by fitting a logistic regression model using an expert rating of a slide's quality (good, fair, or poor) as the response variable and a host of metrics about the raw positive control data as predicting variables.

Objects from the Class

Although objects of the class can be created by a direct call to new, the preferred method is to use the RPPAPreFitQC factory generator function.

Slots

antibody:

character string specifying name of antibody

slopediff:

numeric scalar specifying the difference from perfect slope

cvs:

numeric vector containing the coefficient of variance for each positive control dilution series

slopes:

numeric vector containing the slopes for each positive control dilution series

drdiffs:

numeric vector containing the difference in dynamic range of each positive control dilution series

percentgood:

numeric scalar specifying percentage of "good" sample spots on the slide

adjusted:

logical scalar specifying if adjusted measures were used

Extends

Class RPPAPreFitQC, directly.

Methods

qcprob

signature(object = "DS5RPPAPreFitQC"):
Calculates the probability of good slide, returned as numeric scalar.

summary

signature(object = "DS5RPPAPreFitQC"):
Prints a summary of the underlying data frame.

Author(s)

P. Roebuck [e-mail], James M. Melott [e-mail]

References

Ju Z, Liu W, Roebuck PL, Siwak DR, Zhang N, Lu Y, Davies MA, Akbani R, Weinstein JN, Mills GB, Coombes KR
Development of a Robust Classifier for Quality Control of Reverse Phase Protein Arrays.
Bioinformatics (2015) 31(6): 912-918.
https://pubmed.ncbi.nlm.nih.gov/25380958/