R: Class "RPPAFit"

RPPAFit-class {RPPASPACE}

R Documentation

Class “RPPAFit”

Description

Objects of the RPPAFit class represent the results of fitting a statistical model of response to the dilution series in a reverse-phase protein array experiment.

Usage

## S4 method for signature 'RPPAFit'
coef(object, ...)
## S4 method for signature 'RPPAFit'
coefficients(object, ...)
## S4 method for signature 'RPPAFit'
fitted(object,
       type=c("Y", "y", "X", "x"),
       ...)
## S4 method for signature 'RPPAFit'
hist(x,
     type=c("Residuals", "StdRes", "ResidualsR2"),
     xlab=NULL,
     main=NULL,
     ...)
## S4 method for signature 'RPPAFit'
image(x,
      measure=c("Residuals", "ResidualsR2", "StdRes", "X", "Y"),
      main,
      ...)
## S4 method for signature 'RPPAFit,missing'
plot(x, y,
     type=c("cloud", "series", "individual", "steps", "resid"),
     col=NULL,
     main,
     xform=NULL,
     xlab="Log Concentration",
     ylab="Intensity",
     ...)
## S4 method for signature 'RPPAFit'
resid(object,
      type=c("raw", "standardized", "r2"),
      ...)
## S4 method for signature 'RPPAFit'
residuals(object,
          type=c("raw", "standardized", "r2"),
          ...)
## S4 method for signature 'RPPAFit'
summary(object, ...)

Arguments

`object`	object of class `RPPAFit`
`x`	object of class `RPPAFit`
`type`	character string describing the type of fitted values, residuals, images, histograms, or plots
`measure`	character string specifying measure to compute from fit
`xlab`	graphics parameter specifying how the x-axis should be labeled
`ylab`	graphics parameter specifying how the y-axis should be labeled
`main`	character string specifying title for the plot
`xform`	function to transform the raw data associated with the `measure` for the plot. If `NULL`, no transformation occurs.
`y`	not used
`col`	graphics parameter, used only if `type='series'`, to color the lines connecting different dilution series. Eight default colors are used if the argument is `NULL`.
`...`	extra arguments for generic or plotting routines

Details

The RPPAFit class holds the results of fitting a response model to all the dilution series on a reverse-phase protein array. For details on how the model is fit, see the RPPAFit function. By fitting a joint model, we assume that the response curve is the same for all dilution series on the array. The real point of the model, however, is to be able to draw inferences on the \delta_i, which represent the (log) concentration of the protein present in different dilution series.

Value

The coef and coefficients methods return the numeric model coefficients from objects returned by modeling functions.

The fitted method returns a numeric vector.

The hist method returns an object of class histogram.

The image method invisibly returns the object x on which it was invoked.

The plot method invisibly returns the object x on which it was invoked.

The resid and residuals methods return a numeric vector.

The summary method invisibly returns NULL.

Objects from the Class

Objects should be constructed using the RPPAFit function.

Slots

call:: object of class call specifying the function call that was used to generate this model fit
rppa:: object of class RPPA containing the raw data that was fit
measure:: character string containing the name of the measurement column in the raw data that was fit by the model
method:: character string containing the name of the method that was used to estimate the upper and lower limit parameters in the model
trimset:: numeric vector of length 5 containing the low and high intensities, the low and high concentrations that mark the trimming boundaries, and the trim level used
model:: object of class FitClass unique to the model that was fit
noise:: numeric vector of estimated relative background concentrations for noise for use in calculating qc values for positive control dilution series with Spot.Types designated as posCtrl-Noise or Noise.
concentrations:: numeric vector of estimates of the relative log concentration of protein present in each sample
lower:: numeric vector containing the lower bounds on the confidence interval of the log concentration estimates
upper:: numeric vector containing the upper bounds on the confidence interval of the log concentration estimates
conf.width:: numeric scalar specifying width of the confidence interval
intensities:: numeric vector containing the predicted observed intensity at the estimated concentrations for each dilution series
ss.ratio:: numeric vector containing statistic measuring the R^2 for each individual dilution series
warn:: character vector containing any warnings that arose when trying to fit the model to individual dilution series
version:: character string containing the version of RPPASPACE that produced the fit

Methods

coef: signature(object = "RPPAFit"):
Extracts model coefficients from objects returned by modeling functions.
coefficients: signature(object = "RPPAFit"):
An alias for coef.
fitted: signature(object = "RPPAFit"):
Extracts the fitted values of the model. This process is more complicated than it may seem at first, since we are estimating values on both the X and Y axes. By default, the fitted values are assumed to be the intensities, Y, which are obtained using either an uppercase or lowercase 'y' as the type argument. The fitted log concentrations are returned when type is set to either uppercase or lowercase 'x'. In the notation used above to describe the model, these fitted values are given by X_i = X - \delta_i.
hist: signature(x = "RPPAFit"):
Produces a histogram of the residuals. The exact form of the residuals being displayed depends on the value of the type argument.
image: signature(x = "RPPAFit"):
Produces a 'geographic' plot of either the residuals or the fitted values, depending on the value of the measure argument. The implementation reuses code from the image method for an RPPA object.
plot: signature(x = "RPPAFit", y = "missing"):
Produces a diagnostic plot of the model fit. The default type, 'cloud', simply plots the fitted X values against the observed Y values as a cloud of points around the jointly estimated sigmoid curve. The 'series' plot uses different colored lines to join points belonging to the same dilution series. The 'individual' plot produces separate graphs for each dilution series, laying each one alongside the jointly fitted sigmoid curve.
resid: signature(object = "RPPAFit"):
An alias for residuals.
residuals: signature(object = "RPPAFit"):
Reports the residual errors. The 'raw' residuals are defined as the difference between the observed intensities and the fitted intensities, as computed by the fitted function. The 'standardized' residuals are obtained by standardizing the raw residuals.
summary: signature(object = "RPPAFit"):
Prints a summary of the RPPAFit object, which reports the function call used to fit the model and important fitting parameters.

Author(s)

Kevin R. Coombes coombes.3@osu.edu, P. Roebuck paul_roebuck@comcast.net, James M. Melott jmmelott@mdanderson.org