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barmixR

This is the development version of barmixR; to use it, please install the devel version of Bioconductor.

Bayesian Modeling of Barcoded Tumor Mixtures for Quantitative Treatment Resistance Analysis


Bioconductor version: Development (3.24)

Implements the Bayesian modeling framework underlying the barmixR (BARcode MIXture analysis) platform for high-throughput quantitative analysis of genotype-specific treatment responses in pooled cancer cell populations. The package integrates barcode sequencing count data with volumetric measurements such as tumor volume (in vivo) or cellular confluency (in vitro) using hierarchical probabilistic models. Barcode counts are modeled with a Dirichlet–multinomial distribution to account for compositional sequencing data, while volumetric measurements are modeled using log-normal (tumor volume) or beta (confluency) likelihoods. Posterior inference is performed using Hamiltonian Monte Carlo through 'rstan'. The resulting posterior distributions enable estimation of clone-specific quantitative treatment resistance (QTR) together with uncertainty propagation from both sequencing and volumetric data. Additional functions provide posterior predictive checks, estimation of resistance ratios, treatment ranking, and visualization of resistance landscapes using violin plots and bubble heatmaps. The methods are designed for multiplexed lineage-tracing experiments in cancer research and were developed to analyze treatment resistance in gastrointestinal stromal tumors (GIST), but are broadly applicable to barcoding-based studies of treatment response and clonal dynamics across diverse cancer types.

Author: Mohammad Darbalaei [aut, cre] ORCID iD ORCID: 0009-0003-4561-0048 , Daniel Hoffmann [aut] ORCID iD ORCID: 0000-0003-2973-7869 , Barbara M. Grüner [ctb], Thomas Mühlenberg [ctb], Julia Zummack [ctb]

Maintainer: Mohammad Darbalaei <mohammad.darbalaei at uni-due.de>

Citation (from within R, enter citation("barmixR")):

Mohammad Darbalaei, Daniel Hoffmann. barmixR: Bayesian Modeling of Barcoded Tumor Mixtures for Quantitative Treatment Resistance Analysis. doi:10.18129/B9.bioc.barmixR, R package version 0.99.3, https://bioconductor.org/packages/barmixR.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")

BiocManager::install("barmixR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("barmixR")
barmixR: Bayesian Modeling of Barcoded Tumor Mixtures for Quantitative Treatment Resistance Analysis HTML R Script
Reference ManualPDF
NEWSText
LICENSEText

Details

biocViews Bayesian, Sequencing, Software, Visualization
Version0.99.3
In Bioconductor sinceBioC 3.24 (R-4.6)
License GPL-3 + file LICENSE
Depends R (>= 4.3.0)
Imports utils, BiocParallel, dplyr, forcats, ggplot2, methods, patchwork, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), rstantools (>= 2.4.0), stats
System RequirementsGNU make, C++17, StanHeaders
URLhttps://github.com/MohammadDarbalaei/barmixR
Bug Reportshttps://github.com/MohammadDarbalaei/barmixR/issues
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Suggests BiocStyle, knitr, MGLM, rmarkdown, testthat, tidyverse
Linking To BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package barmixR_0.99.3.tar.gz
Windows Binary (x86_64) barmixR_0.99.3.zip (64-bit only)
macOS Binary (big-sur-x86_64) barmixR_0.99.3.tgz
macOS Binary (sonoma-arm64) barmixR_0.99.3.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/barmixR
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/barmixR
Package Short Url https://bioconductor.org/packages/barmixR/
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