Infrastructure to to store and process MCMC results

The RexParams infrastructure is used to store and process MCMC results for Rex model from Crook et al 2024.

chains(object)

# S4 method for RexParams
show(object)

# S4 method for RexChain
show(object)

# S4 method for RexSummary
show(object)

# S4 method for RexChains
length(x)

# S4 method for RexParams
length(x)

posteriorEstimates(object)

# S4 method for RexSummary
posteriorEstimates(object)

Rex.quantiles(object)

# S4 method for RexSummary
Rex.quantiles(object)

Rex.resolution(object)

# S4 method for RexSummary
Rex.resolution(object)

Rex.peptideError(object)

# S4 method for RexSummary
Rex.peptideError(object)

Rex.globals(object)

# S4 method for RexSummary
Rex.globals(object)

# S4 method for RexParams
posteriorEstimates(object)

# S4 method for RexParams
Rex.quantiles(object)

# S4 method for RexParams
Rex.resolution(object)

# S4 method for RexParams
Rex.peptideError(object)

# S4 method for RexParams
Rex.globals(object)

# S4 method for RexChains,ANY,ANY
[[(x, i, j = "missing", drop = "missing")

# S4 method for RexChains,ANY,ANY,ANY
[(x, i, j = "missing", drop = "missing")

# S4 method for RexParams,ANY,ANY,ANY
[(x, i, j = "missing", drop = "missing")

# S4 method for RexChains
show(object)

# S4 method for RexDifferential
show(object)

Rex.predictionError(object)

Rex.estimates(object)

Rex.probs(object)

Rex.eFDR(object)

# S4 method for RexDifferential
Rex.predictionError(object)

# S4 method for RexDifferential
Rex.estimates(object)

# S4 method for RexDifferential
Rex.probs(object)

# S4 method for RexDifferential
Rex.eFDR(object)

Arguments

object: An instance of appropriate class.
x: Object to be subset.
i: An integer(). Should be of length 1 for [[.
j: Missing.
drop: Missing.

Value

An object of class RexParams which stores the main results for the analysis when using Rex

Details

Objects of the RexParams class are created with the Rex() function These objects store the priors for the model and the results of the MCMC chains, which themselves are stored as an instance of class RexChains and can be accessed with the chains() function. A summary of the RexChains (or class RexSummary) can be further computed with the RexProcess function.

see the RexMS vignette for examples

Slots

chains: list() containing the individual full MCMC chain results in an RexChains instance. Each element must be a valid RexChain instance.
posteriorEstimates: A DataFrame documenting the posteriors in an RexSummary instance
diagnostics: A matrix of dimensions 1 by 2 containing the RexSummary diagnostics.
Rex.quantiles: A DataFrame of with R rows indicated quantiles for key parameters in the Rex model
Rex.globals: A DataFrame of with R rows indicated global parameters at the moment the standard deviation sigma and the model likelihoods
Rex.resolution: A DataFrame of with R rows indicated resolution metrics
Rex.peptideError: A DataFrame indicated peptide error
method: A character() storing the Rex method name
priors: A list() with the priors for the parameters
seed: An integer() with the random number generation seed.
summary: Object of class RexSummary the summarised MCMC results available in the RexParams instance.
chains: Object of class RexChains containing the full MCMC results in the RexParams instance
interval: A numeric() with the interval for the residues cover
dataset: character indicating the dataset
blong: matrix of dimensions R by numIter containing the blong values for the residues
pilong: matrix of dimensions R by numIter containing the pilong values for the residues
qlong: matrix of dimensions R by numIter containing the qlong values for the residues
dlong: matrix of dimensions R by numIter containing the dlong values for the residues
loglikelihood: numeric of length numIter containing the loglikelihood values
phi: numeric of length 1 containing the phi values for the model
UptakeGuess: list each with a matrix of dimensions R by numTimepoints containing the UptakeGuess values for the residues
numBreak: numeric of length numIter containing the number of breakpoints
Sigma: numeric of length numIter containing the Sigma values
R: integer of length 1 containing the number of residues
timepoints: numeric of length numTimepoints containing the timepoints
numIter: integer of length 1 containing the number of mcmc iterations
numPeptides: integer of length 1 containing the number of peptides
numTimepoints: integer of length 1 containing the number of timepoints
dataset: character indicating the dataset
Rex.predictionError: DFrame containing the prediction error
Rex.estimates: DFrame containing the estimates ARE, TRE, signed ARE
Rex.probs: DFrame containing the probabilities and total probabilities
Rex.eFDR: DFrame containing the eFDR