AlphaGenomeR is a Bioconductor-ready R package that gives R researchers direct access to Google DeepMind’s AlphaGenome API without leaving their native R environment. It handles all Python interop internally viaDocumentation Index
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reticulate, so you work entirely in R while the package manages gRPC communication with the AlphaGenome service and converts results into standard matrices and data frames.
What is AlphaGenomeR?
AlphaGenome is a multimodal transformer model developed by Google DeepMind that predicts functional genomic features directly from DNA sequences at single-base resolution. Given a 1 MB genomic interval, it simultaneously predicts RNA-seq signal, chromatin accessibility, transcription factor binding, splicing patterns, and 3D chromatin contact maps — filtered by tissue or cell type. AlphaGenomeR bridges the official AlphaGenome Python SDK using thereticulate package. You call R functions, AlphaGenomeR translates your inputs into Python objects, executes the gRPC prediction request, and returns the results as R-native matrix and data.frame objects ready for downstream analysis with standard Bioconductor tools.
Key features
Multimodal predictions
Query 11+ genomic modalities in a single API call — RNA-seq, ATAC-seq, CAGE, ChIP-seq (TF and histone), DNase, splice sites, splice junctions, PRO-cap, and 3D contact maps.
Bioconductor integration
Results are returned as R-native
matrix and data.frame objects compatible with standard Bioconductor analysis workflows.Tissue specificity
Filter predictions by tissue or cell type using UBERON and CL ontology terms (e.g.,
"UBERON:0002048" for lung).High resolution
Predictions span 1 MB genomic intervals at single-base pair resolution for precise regulatory analysis.
Prerequisites
AlphaGenomeR requires the following before installation:- Python >= 3.10 — used by
reticulateto load the AlphaGenome SDK alphagenomePython package — the official SDK that handles gRPC communication with the API- AlphaGenome API key — a free, non-commercial key available from the AlphaGenome Science Page
How it works
When you callalphagenome_query(), the package uses reticulate to import the alphagenome.models.dna_client and alphagenome.data.genome Python modules. It parses your genomic region string, maps R character vectors to Python enum values, initializes a gRPC client with your API key, and calls client$predict_interval(). The raw Python response object is then converted to an R list via reticulate::py_to_r().
Extractor functions like alphagenome_get_rna_seq() and alphagenome_get_atac() pull specific modalities out of that list and return a named list with two elements: values (a numeric matrix of positions × tracks) and metadata (a data frame describing each track).
Next steps
Installation
Install AlphaGenomeR from GitHub and set up the Python dependency.
Quickstart
Make your first multimodal genomic prediction in minutes.