Plate IV.131 · Publications

anndata: Access and store annotated data matrices

Article in Journal of Open Source Software, 16 September 2024.

Open accessResearch area: Independent Component, Graph

Authors

  1. Isaac Virshup
  2. Sergei Rybakov
  3. Fabian J. Theis
  4. Philipp Angerer
  5. F. Alexander Wolf

Abstract

anndata is a Python package for handling annotated data matrices in memory and on disk (github.com/theislab/anndata), positioned between pandas and xarray. anndata offers a broad range of computationally efficient features including, among others, sparse data support, lazy operations, and a PyTorch interface. Statement of need Generating insight from high-dimensional data matrices typically works through training models that annotate observations and variables via low-dimensional representations. In exploratory data analysis, this involves iterative training and analysis using original and learned annotations and task-associated representations. anndata offers a canonical data structure for book-keeping these, which is neither addressed by pandas (McKinney, 2010), nor xarray (Hoyer & Hamman, 2017), nor commonly-used modeling packages like scikit-learn (Pedregosa et al., 2011).

Versions2

  1. PublishedJournal of Open Source Software10.21105/joss.04371
  2. PreprintbioRxiv10.1101/2021.12.16.473007

Cite

@article{virshup2024anndata,
  title = {{anndata: Access and store annotated data matrices}},
  author = {Virshup, Isaac and Rybakov, Sergei and Theis, Fabian J. and Angerer, Philipp and Wolf, F. Alexander},
  journal = {Journal of Open Source Software},
  publisher = {The Open Journal},
  year = {2024},
  month = sep,
  doi = {10.21105/joss.04371},
  url = {https://doi.org/10.21105/joss.04371}
}
.bib file