Fitting Dilution Curves to Protein Lysate Arrays with Class “RPPAFitParams”
Description
The RPPAFit
function fits an intensity response model to the
dilution series in a reversephase protein array experiment. Individual
sample concentrations are estimated by matching individual sample
dilution series to the overall logistic response for the slide.
The RPPAFitParams
class is a convenient place to wrap the parameters
that control the model fit into a reusable object.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35  RPPAFit(rppa,
design,
measure,
model="logistic",
xform=NULL,
method=c("nls", "nlrob", "nlrq"),
trim=2,
ci=FALSE,
ignoreNegative=TRUE,
trace=FALSE,
verbose=FALSE,
veryVerbose=FALSE,
warnLevel=0)
RPPAFitParams(measure,
model="logistic",
xform=NULL,
method=c("nls", "nlrob", "nlrq"),
trim=2,
ci=FALSE,
ignoreNegative=TRUE,
trace=FALSE,
verbose=FALSE,
veryVerbose=FALSE,
warnLevel=0)
RPPAFitFromParams(rppa,
design,
fitparams,
progmethod=NULL)
is.RPPAFit(x)
is.RPPAFitParams(x)
## S4 method for signature 'RPPAFitParams'
paramString(object, slots, ...)

Arguments
rppa 
object of class  
design 
object of class  
fitparams 
object of the class  
progmethod 
optional function that can be used to report progress.  
measure 
character string identifying the column of the raw RPPA data that should be used to fit to the model.  
model 
character string specifying the model for the response curve fitted for the slide. Valid values are:
 
xform 
optional function that takes a single input vector and
returns a single output vector of the same length. The  
method 
character string specifying the method for matching the individual dilution series to the response curve fitted for the slide. Valid values are:
 
trim 
numeric or logical scalar specifying trim level for
concentrations. If positive, concentrations will be trimmed to reflect
min and max concentrations we can estimate given the background noise.
If  
ci 
logical scalar. If  
ignoreNegative 
logical scalar. If  
trace 
logical scalar passed to nls in the  
verbose 
logical scalar. If  
veryVerbose 
logical scalar. If  
warnLevel 
integer scalar used to set the  
object 
object of class  
x 
object of class  
slots 
strings specifying  
... 
extra arguments for generic routines. 
Details
The basic mathematical model is given by
Y = f(Xδ_i),
where Y is the observed intensity, X is the designed dilution step and f is the model for the protein response curve. 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 δ_i, which represent the (log) concentration of the protein present in different dilution series.
As the first step in fitting the model, we compute crude estimates of the individual δ_i assuming a rough logistic shape for the protein response curve.
Next, we fit an overall response curve for the slide f using the estimated concentrations and observed intensities Y = f(δ_i). The model for f is specified in the model parameter.
Next, we update the estimates of the individual δ_i using our
improved fitted model f for the overall slide response curve. These
individual series are matched to the overall slide response curve using the
algorithm specified in method
. The default method is nls
, a
least squares matchup, but we also offer robust alternatives which can do
better.
Finally, we reestimate f using the improved estimates for δ_i. We continue to iterate between f and δ_i. We do this twice since that seems to give reasonable convergence.
If the ci
argument is TRUE
, then the function also computes
confidence intervals around the estimates of the log concentration.
Since this step can be timeconsuming, it is not performed by default.
Moreover, confidence intervals can be computed after the main model is fit
and evaluated, using the getConfidenceInterval
function.
Value
The RPPAFit
generator and RPPAFitFromParams
function return
an object of class RPPAFit
.
The RPPAFitParams
generator returns an object of class
RPPAFitParams
.
The is.RPPAFit
method returns TRUE
if its
argument is an object of class RPPAFit
.
The is.RPPAFitParams
method returns TRUE
if its
argument is an object of class RPPAFitParams
.
The paramString
method returns a character vector, possibly
empty but never NULL
.
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 RPPAFitParams
function.
Slots
measure
:character; see arguments above
xform
:function or
NULL
; see arguments abovemethod
:character; see arguments above
ci
:logical scalar; see arguments above
ignoreNegative
:logical scalar; see arguments above
trace
:logical scalar; see arguments above
verbose
:logical scalar; see arguments above
veryVerbose
:logical scalar; see arguments above
warnLevel
:numeric; see arguments above
trim
:numeric; see arguments above
model
:character; see arguments above
Methods
 paramString

signature(object = "RPPAFitParams")
:
Returns string representation of object.
Warning
The paramString
method should not be called by user except for
informational purposes. The content and format of the returned string
may vary between different versions of this package.
Author(s)
P. Roebuck proebuck@mdanderson.org, Kevin R. Coombes kcoombes@mdanderson.org
See Also
RPPAFit
,
RPPAFitclass
,
RPPA
,
RPPADesign
Examples
1 2 3 4 5 6 7 8 9 10  extdata.dir < system.file("extdata", package="SuperCurveSampleData")
txtdir < file.path(extdata.dir, "rppaTumorData")
erk2 < RPPA("ERK2.txt", path=txtdir)
design < RPPADesign(erk2,
grouping="blockSample",
controls=list("neg con", "pos con"))
fit.nls < RPPAFit(erk2, design, "Mean.Net")
summary(fit.nls)
coef(fit.nls)

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