BreastSubtypeR

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BreastSubtypeR — assumption-aware, multi-method intrinsic molecular subtyping for breast cancer (R / Bioconductor)

Authors: Qiao Yang, Emmanouil G. Sifakis\ Affiliation: Department of Oncology-Pathology, Karolinska Institutet (Stockholm, Sweden)\ Paper: Yang Q., Hartman J., Sifakis E.G. BreastSubtypeR: A Unified R/Bioconductor Package for Intrinsic Molecular Subtyping in Breast Cancer Research. NAR Genomics and Bioinformatics (2025). Editor’s Choice.

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Overview

BreastSubtypeR consolidates established gene-expression–based intrinsic subtyping methods into a single, reproducible R/Bioconductor package and provides a local Shiny app (iBreastSubtypeR) for users without programming experience.

Key goals: - reduce method misapplication across heterogeneous research cohorts, - enable direct cross-method benchmarking and exploration of discordant calls, - provide method-specific preprocessing and robust probe-to-gene mapping, - support privacy-preserving local analyses via a Shiny GUI.

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Main features

• Comprehensive Intrinsic Subtyping: Integrates multiple published intrinsic subtyping algorithms (NC- and SSP-based), including PAM50 variants, AIMS, ssBC, sspbc, and others.
• Unified Multi-Method Interface (BS_Multi): Run many classifiers from one consistent API and compare results side-by-side.
• AUTO Mode (cohort-aware selection): Evaluates cohort diagnostics (e.g., receptor-status distribution, subtype purity, subgroup sizes) and programmatically disables classifiers whose assumptions are likely violated—reducing misclassification in skewed or small cohorts.
• Standardised Input & Method-Specific Normalisation: Supports raw RNA-seq counts, precomputed FPKM, and log₂-normalised microarray/nCounter matrices with automated, method-appropriate transformations.
• Optimised Probe/Gene Mapping: Entrez ID–based mapping and conflict resolution to maximise marker coverage across platforms.
• Interactive Shiny App (iBreastSubtypeR): Local GUI that replicates core workflows for non-programmers and preserves data privacy.
• Bioconductor distribution & reproducibility: Unit tests, vignettes and SummarizedExperiment compatibility to support reproducible deployment.

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Methods included (single-method implementations)

| Method id | Short description | Group | Reference | |------------------|-------------------|------------------|------------------| | parker.original | Original PAM50 by Parker et al., 2009 | NC-based | Parker et al., 2009 | | genefu.scale | PAM50 implementation as in the genefu R package (scaled version) | NC-based | Gendoo et al., 2016 | | genefu.robust | PAM50 implementation as in the genefu R package (robust version) | NC-based | Gendoo et al., 2016 | | cIHC | Conventional ER-balancing using immunohistochemistry (IHC) | NC-based | Ciriello et al., 2015 | | cIHC.itr | Iterative version of cIHC | NC-based | Curtis et al., 2012 | | PCAPAM50 | Selects IHC-defined ER subsets, then uses Principal component analysis (PCA) to create ESR1 expression-based ER-balancing | NC-based | Raj-Kumar et al., 2019 | | ssBC | Subgroup-specific gene-centering PAM50 | NC-based | Zhao et al., 2015 | | ssBC.v2 | Updated subgroup-specific gene-centering PAM50 with refined quantiles | NC-based | Fernandez-Martinez et al., 2020 | | AIMS | Absolute Intrinsic Molecular Subtyping (AIMS) method | SSP-based | Paquet & Hallett, 2015 | | sspbc | Single-Sample Predictors for Breast Cancer (AIMS adaptation) | SSP-based | Staaf et al., 2022 |

(See the package vignette for implementation details.)

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Installation

Install the released version from Bioconductor:

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

BiocManager::install("BreastSubtypeR") ```

Or install the development version from GitHub:

``` r

Install devtools package if you haven't already

install.packages("devtools")

Install BreastSubtypeR from GitHub

devtools::install_github("yqkiuo/BreastSubtypeR") ```

Quick start examples

Note: this README uses example datasets included in the package. Replace BreastSubtypeRobj / OSLO2EMIT0obj with your own SummarizedExperiment object and clinical metadata..

1) Preprocessing & mapping

``` r library(BreastSubtypeR)

Example data shipped with the package

data("BreastSubtypeRobj") # package-specific object data("OSLO2EMIT0obj")

Map probes/ids to Entrez

datainput <- Mapping( OSLO2EMIT0obj$seobj, RawCounts = FALSE, method = "max", impute = TRUE, verbose = FALSE ) ```

2) Multi-method subtyping (user-defined methods)

``` r methods <- c("parker.original", "PCAPAM50", "sspbc") result <- BSMulti( datainput = data_input, methods = methods, Subtype = FALSE, hasClinical = FALSE )

View per-sample subtype calls (methods x samples)

head(result$ressubtypes[, 1:min(5, ncol(result$ressubtypes))], 5) ```

3) AUTO mode (cohort-aware selection)

``` r resultauto <- BSMulti( datainput = datainput, methods = "AUTO", Subtype = FALSE, hasClinical = FALSE )

Visualize subtype calls and inter-method concordance

VisMulti(resultauto$res_subtypes) ```

4) Launch the local Shiny app

``` r library(BreastSubtypeR) library(tidyverse) library(shiny) library(bslib)

iBreastSubtypeR() # interactive GUI (local) ```

Vignette & Documentation

A comprehensive usage guide is included as a vignette with the package—browse it through your R help system or find the rendered version in your documentation files.

For specific functions (like BS_Multi, Mapping, or iBreastSubtypeR), see their help pages (e.g., ?BS_Multi). The package manual also lists accepted input formats and parameter descriptions for ease of reference.

Contributing & issues

Contributions and issue reports are welcome. Please open issues or pull requests on the GitHub repository: https://github.com/yqkiuo/BreastSubtypeR/issues.

Citation

When using BreastSubtypeR in publications, please cite the package and the paper:

Yang Q., Hartman J., Sifakis E. G. (2025) BreastSubtypeR: A Unified R/Bioconductor Package for Intrinsic Molecular Subtyping in Breast Cancer Research. NAR Genomics and Bioinformatics. (Editor’s Choice).

You can also use citation("BreastSubtypeR") after installing the package to retrieve the canonical citation(s).

License

This project is released under the GPL-3 license.