nicheMeans2D: Uncertainty plot organelle means

In pRoloc: A unifying bioinformatics framework for spatial proteomics

Description

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 MCMCParams that 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

Author(s)

Oliver M. Crook <[e-mail]>

Examples

## Not run: 
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)

## End(Not run)

pRoloc documentation built on Nov. 8, 2020, 6:26 p.m.