Package: bandle 1.11.0

Oliver M. Crook

bandle: An R package for the Bayesian analysis of differential subcellular localisation experiments

The Bandle package enables the analysis and visualisation of differential localisation experiments using mass-spectrometry data. Experimental methods supported include dynamic LOPIT-DC, hyperLOPIT, Dynamic Organellar Maps, Dynamic PCP. It provides Bioconductor infrastructure to analyse these data.

Authors:Oliver M. Crook [aut, cre], Lisa Breckels [aut]

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bandle.pdf |bandle.html✨
bandle/json (API)
NEWS

# Install 'bandle' in R:

install.packages('bandle', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ococrook/bandle/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On BioConductor:bandle-1.11.0(bioc 3.21)bandle-1.10.0(bioc 3.20)

bayesian classification clustering immunooncology qualitycontrol dataimport proteomics massspectrometry

5.48 score 5 stars 3 scripts 137 downloads 35 exports 227 dependencies

Last updated 19 days agofrom:ca58277144. Checks:OK: 1 WARNING: 8. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 02 2024
R-4.5-win-x86_64	WARNING	Nov 02 2024
R-4.5-linux-x86_64	WARNING	Nov 02 2024
R-4.4-win-x86_64	WARNING	Nov 02 2024
R-4.4-mac-x86_64	WARNING	Nov 02 2024
R-4.4-mac-aarch64	WARNING	Nov 02 2024
R-4.3-win-x86_64	WARNING	Nov 02 2024
R-4.3-mac-x86_64	WARNING	Nov 02 2024
R-4.3-mac-aarch64	WARNING	Nov 02 2024

Exports:bandle bandle_get_outliers bandleJoint bandlePredict bandleProcess binomialDiffLocProb bootstrapdiffLocprob calculateGelman covOrganelle diffLoc diffLocalisationProb dmvtCpp EFDR fitGP fitGPmatern fitGPmaternPC Gumbel kldir kldirpg mcmc_plot_probs meanOrganelle mrMethod pg_prior plotConvergence plotGPmatern plotOutliers plotTable plotTranslocations posteriorEstimates prior_pred_dir prior_pred_pg sim_dynamic spatial2D StatStratum summaries

Dependencies:abind affy affyio annotate AnnotationDbi AnnotationFilter askpass assertthat base64enc BH Biobase BiocBaseUtils BiocFileCache BiocGenerics BiocManager BiocParallel BiocStyle biomaRt Biostrings bit bit64 blob bookdown bslib cachem caret circlize class cli clock clue cluster coda codetools colorspace commonmark cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray dendextend DEoptimR diagram digest diptest doParallel dplyr e1071 evaluate fansi farver fastmap filelock flexmix FNN fontawesome foreach formatR fpc fs futile.logger futile.options future future.apply gbm gdata genefilter generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggalluvial ggplot2 ggrepel ggvis GlobalOptions globals glue gower gridExtra gtable gtools hardhat hexbin highr hms htmltools htmlwidgets httpuv httr httr2 hwriter igraph impute ipred IRanges isoband iterators jquerylib jsonlite KEGGREST kernlab KernSmooth knitr labeling lambda.r LaplacesDemon later lattice lava lazyeval lbfgs lifecycle limma listenv lpSolve lubridate magrittr MALDIquant MASS Matrix MatrixGenerics matrixStats mclust memoise mgcv mime mixtools mlbench MLInterfaces ModelMetrics modeltools MsCoreUtils MSnbase MultiAssayExperiment munsell mvtnorm mzID mzR ncdf4 nlme nnet numDeriv openssl parallelly pcaMethods pillar pkgconfig plogr plotly pls plyr png prabclus preprocessCore prettyunits pROC prodlim progress progressr pRoloc pRolocdata promises ProtGenerics proxy PSMatch purrr QFeatures R6 randomForest rappdirs RColorBrewer Rcpp RcppArmadillo recipes reshape2 Rhdf5lib rlang rmarkdown robustbase rpart RSQLite S4Arrays S4Vectors sampling sass scales segmented sfsmisc shape shiny snow sourcetools SparseArray SQUAREM statmod stringi stringr SummarizedExperiment survival sys threejs tibble tidyr tidyselect timechange timeDate tinytex tzdb UCSC.utils utf8 vctrs viridis viridisLite vsn withr xfun XML xml2 xtable XVector yaml zlibbioc

Vignette 1: Getting Started with BANDLE

Oliver M. Crook, Lisa M. Breckels

Rendered fromv01-getting-started.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-11-01
Started: 2022-02-02

Vignette 2: A workflow for analysing differential localisation

Oliver M. Crook, Lisa M. Breckels

Rendered fromv02-workflow.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-11-01
Started: 2022-02-02

Citation

Development and contributors

Readme and manuals

Help Manual

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