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EFDR()
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Compute the expected False Discovery Rate |
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besselK_boost() besselK() matern() trenchDetcpp() trenchInvcpp() loglikeGPcpp() likelihoodGPcpp() gradientrhomatern() gradientamatern() gradientGPcppmatern() LeapfrogGPcppPC() sampleGPmeanmaterncpp() makeComponent() sampleGPmeancpp() normalisedData() normalisedDatamatern() centeredDatamatern() componentloglike() comploglike() comploglikelist() sampleDirichlet() sampleOutliercpp() sampleAlloccpp() centeredData() mahaInt() dmvtInt() dmvtCpp() gradientGPcpp() LeapfrogGPcpp() rcpp_pgdraw()
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bessel function of the second kind from boost library |
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diffLocalisationProb() bootstrapdiffLocprob() binomialDiffLocProb()
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Compute differential localisation probabilities from ms-based
experiments using the bandle method |
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gradientGP() gradientGPmatern() posteriorgradientGPmatern() gradientlogprior() likelihoodGP() likelihoodGPmatern() posteriorGPmatern() Gumbel() PCrhomvar() metropolisGP() metropolisGPmatern() Gumbel() PCrhomvar()
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Compute GP gradient |
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fitGP() fitGPmaternPC() fitGPmatern() plotGPmatern()
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Fit a Gaussian process to spatial proteomics data |
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proteinAllocation() outlierAllocationProbs() sampleOutlier() covOrganelle() pg_prior() sample_weights_pg() sample_weights_dir()
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sample allocations, probabilities and compute loglikilihoods |
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meanOrganelle()
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Computes Organelle means and variances using markers |
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bandle-package
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An R package for the Bayesian analysis of differential subcellular
localisation experiments |
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plotConvergence()
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Generates a histogram of ranks (a rank plot) for convergence |
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mcmc_plot_probs()
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Generate a violin plot showing the probabilitiy of protein
localisation to different organelles |
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spatial2D()
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Generate a PCA plot with smoothed probability contours |
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plotTable()
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Generates a table for visualising changes in
localisation between two conditions/datasets |
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plotTranslocations()
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Generates a chord diagram or alluvial plot for visualising changes in
localisation between two conditions/datasets |
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StatStratum
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inherits StatSratum |
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bandlePredict()
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Make predictions from a bandle analysis |
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kldirpg() kldir() prior_pred_dir() prior_pred_pg()
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Computes the Kullback-Leibler divergence between Polya-Gamma and
Dirichlet priors |
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bandleProcess()
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process bandle results |
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sim_dynamic()
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Generate a dynamic spatial proteomics experiment |
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bandle() diffLoc()
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Differential localisation experiments using the bandle method |
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chains() show(<bandleParams>) show(<nicheParam>) show(<bandleChain>) length(<bandleChains>) length(<bandleParams>) length(<bandleSummaries>) length(<nicheParams>) length(<nicheParams>) posteriorEstimates() summaries() params() bandleJoint() `[[`(<bandleChains>,<ANY>,<ANY>) `[[`(<bandleParams>,<ANY>,<ANY>) `[`(<bandleChains>,<ANY>,<ANY>,<ANY>) `[`(<bandleParams>,<ANY>,<ANY>,<ANY>) show(<bandleChains>) show(<bandleSummaries>) `[[`(<bandleSummaries>,<ANY>,<ANY>) `[[`(<bandleSummaries>,<ANY>,<ANY>) `[`(<bandleSummaries>,<ANY>,<ANY>,<ANY>) `[[`(<nicheParams>,<ANY>,<ANY>) `[[`(<nicheParams>,<ANY>,<ANY>) `[`(<nicheParams>,<ANY>,<ANY>,<ANY>) show(<nicheParams>)
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Infrastructure to to store and process MCMC results |
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gpParams-class
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Container for GP results |
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robustMahalanobis() reprodScore() mrMethod()
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robust Mahalanobis distance |