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Software design

Source: vignettes/articles/software_design.Rmd
software_design.Rmd

Introduction

anndataR is designed to be an R native implementation of the AnnData object, inspired by the of the following packages:

Ideally, this package will be a complete replacement for all of these packages, and will be the go-to package for working with AnnData files in R.

Core features

  • An R6 AnnData class to work with objects in R
  • In-memory (InMemoryAnnData), HDF5-backed (HDF5AnnData) and Python-backed (ReticulateAnnData) back ends with a consistent interface
  • Read/write .h5ad files natively
  • Convert to/from SingleCellExperiment objects
  • Convert to/from Seurat objects

Planned features

  • Zarr-backed back end (ZarrAnnData)

AnnData classes

The different AnnData classes provide a consistent interface but store and access data in different ways:

  • The InMemoryAnnData stores data within the R session. This is the simplest back end and will be most familiar to users. It is want you will want to use in most cases where you want to interact with an AnnData object.
  • The HDF5AnnData provides an interface to a H5AD file and minimal data is stored in memory until it is requested by the user. It is primarily designed as an intermediate object when reading/writing H5AD files but can be useful for accessing parts of large files.
  • The ReticulateAnnData access data stored in an AnnData object in a concurrent Python session. This comes with the overhead and complexity of using reticulate but is sometimes useful to access functionality that has not yet been implemented in anndataR.
  • The planned ZarrAnnData will provide an interface to an AnnData Zarr store, similar to HDF5AnnData.
  • An AnnDataView is returned when subsetting an AnnData object and provides access to a subset of the data in the referenced object. Some functionality (such as setting slots) requires converting to one of the full classes.

Class diagram

This diagram shows the main R6 classes provided by the package:

Notation:

  • X: Matrix - variable X is of type Matrix
  • *X: Matrix - variable X is abstract (and implemented by subclasses)
  • as_SingleCellExperiment(): SingleCellExperiment - function as_SingleCellExperiment returns object of type SingleCellExperiment
  • *as_SingleCellExperiment() - function as_SingleCellExperiment is abstract (and implemented by subclasses)
  • Dashed borders indicate classes that are planned but not yet implemented

Session info 

sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 24.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
 [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
 [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
[10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   

time zone: UTC
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] BiocStyle_2.36.0

loaded via a namespace (and not attached):
 [1] digest_0.6.37       desc_1.4.3          R6_2.6.1           
 [4] bookdown_0.45       fastmap_1.2.0       xfun_0.53          
 [7] cachem_1.1.0        knitr_1.50          htmltools_0.5.8.1  
[10] rmarkdown_2.30      lifecycle_1.0.4     cli_3.6.5          
[13] sass_0.4.10         pkgdown_2.1.3       textshaping_1.0.4  
[16] jquerylib_0.1.4     systemfonts_1.3.1   compiler_4.5.1     
[19] tools_4.5.1         ragg_1.5.0          bslib_0.9.0        
[22] evaluate_1.0.5      yaml_2.3.10         BiocManager_1.30.26
[25] jsonlite_2.0.0      rlang_1.1.6         fs_1.6.6           
[28] htmlwidgets_1.6.4