qpcR: replist – R documentation

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replist

Amalgamation of single data models into a model containing replicates

Description

Starting from a 'modlist' containing qPCR models from single data, replist amalgamates the models according to the grouping structure as defined in group. The result is a 'replist' with models obtained from fitting the replicates by pcrfit. A kinetic outlier detection and removal option is included.

Usage

replist(object, group = NULL, check = "none",
        checkPAR = parKOD(), remove = c("none", "KOD"), 
        names = c("group", "first"), doFit = TRUE, opt = FALSE, 
        optPAR = list(sig.level = 0.05, crit = "ftest"), 
        verbose = TRUE, ...)

Arguments

`object`	an object of class 'modlist'.
`group`	a vector defining the replicates for each group.
`check`	which method to use for kinetic outlier detection. Either `none` or any of the methods in `KOD`.
`checkPAR`	parameters to be supplied to the `check` method, see `KOD`.
`remove`	which runs to remove. Either `none` or those that failed from the method defined in `check`.
`names`	how to name the grouped fit. Either 'group_1, ...' or the first name of the replicates.
`doFit`	logical. If set to `FALSE`, the replicate data is only aggregated without doing a refitting. See 'Details'.
`opt`	logical. Should model selection be applied to the final model?
`optPAR`	parameters to be supplied to `mselect`.
`verbose`	if `TRUE`, the analysis is printed to the console.
`...`	other parameters to be supplied to `mselect`.

Details

As being defined by group, the 'modlist' is split into groups of runs and these amalgamated into a nonlinear model. Runs which have failed to be fitted by modlist are automatically removed and group is updated (that is, the correpsonding entries also removed) prior to fitting the replicate model by pcrfit. Model selection can be applied to the final replicate model by setting opt = TRUE and changing the parameters in optPAR. If check is set to any of the methods in "KOD", kinetic outliers are identified and optionally removed, if remove is set to "KOD".
If doFit = FALSE, the replicate data is only aggregated and no refitting is done. This is useful when plotting replicate data by some grouping vector. See 'Examples'.

Value

An object of class 'replist' containing the replicate models of class 'nls'/'pcrfit'.

Author(s)

Andrej-Nikolai Spiess

Examples

## Convert 'modlist' into 'replist'.
ml1 <- modlist(reps, model = l4)
rl1 <- replist(ml1, group = gl(7, 4))
plot(rl1)
summary(rl1[[1]])

## Optimize model based on Akaike weights.
rl2 <- replist(ml1, group = gl(7, 4), opt = TRUE, 
               optPARS = list(crit = "weights"))
plot(rl2)

## Not run: 
## Remove kinetic outliers,
## use first replicate name for output.
ml3 <- modlist(reps, model = l4)
rl3 <- replist(ml3, group = gl(7, 4), check = "uni1", 
               remove = "KOD", names = "first")
plot(rl3, which = "single")

## Just aggregation and no refitting.
ml4 <- modlist(reps, model = l4)
rl4 <- replist(ml4, group = gl(7, 4), doFit = FALSE)
plot(rl4, which = "single")

## Scenario 1:
## automatic removal of runs that failed to
## fit during 'modlist' by using 'testdat' set.
ml5 <- modlist(testdat, model = l5)
rl5 <- replist(ml5, gl(6, 4))
plot(rl5, which = "single")

## Scenario 2:
## automatic removal of runs that failed to
## fit during 'replist':
## samples F3.1-F3.4 is set to 1.
dat1 <- reps
ml6 <- modlist(dat1)
ml6[[9]]$DATA[, 2] <- 1
ml6[[10]]$DATA[, 2] <- 1
ml6[[11]]$DATA[, 2] <- 1
ml6[[12]]$DATA[, 2] <- 1
rl6 <- replist(ml6, gl(7, 4))
plot(rl6, which = "single")

## End(Not run)

qpcR

Modelling and Analysis of Real-Time PCR Data

v1.4-1

GPL (>= 2)

Authors

Andrej-Nikolai Spiess <a.spiess@uke.uni-hamburg.de>

Initial release

2018-05-29