Produces a pca plot with uncertainty in organelle means projected onto the PCA plot with contours.
Usage
nicheMeans2D(
object,
params,
priors,
dims = c(1, 2),
fcol = "markers",
aspect = 0.5
)Arguments
- object
A valid object of class
MSnset- params
A valid object of class
MCMCParamsthat has been processed and checked for convergence- priors
The prior that were used in the model
- dims
The PCA dimension in which to project he data, default is
c(1,2)- fcol
The columns of the feature data which contain the marker data.
- aspect
A argument to change the plotting aspect of the PCA
Value
Used for side effect of producing plot. Invisibily returns an ggplot object that can be further manipulated
Examples
if (FALSE) { # \dontrun{
library("pRolocdata")
data("tan2009r1")
tanres <- tagmMcmcTrain(object = tan2009r1)
tanres <- tagmMcmcProcess(tanres)
tan2009r1 <- tagmMcmcPredict(object = tan2009r1, params = tanres, probJoint = TRUE)
myparams <- chains(e14Tagm_converged_pooled)[[1]]
myparams2 <- chains(mcmc_pool_chains(tanres))[[1]]
priors <- tanres@priors
pRoloc:::nicheMeans2D(object = tan2009r1, params = myparams2, priors = priors)
} # }