anndata: Access and store annotated datamatrices

anndata is a Python package for handling annotated data matrices in memory and on disk (github.com/scverse/anndata),positioned between pandas and xarray.anndata offers generic data access features including, among others, sparse data support, lazy operations, and a PyTorch interface. Statement of needGenerating 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).

Authors

Publication Details

Journal
The Journal of Open Source Software
Published
2024-09-16
DOI
https://doi.org/10.21105/joss.04371
Citations
164
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
38.35
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article

anndata: Access and store annotated datamatrices

Isaac Virshup, Philipp Angerer, F. Alexander Wolf, Fabian Joachim Theis et al.
164 citations
The Journal of Open Source Software
Single-cell and spatial transcriptomics
38.35
article

anndata: Access and store annotated datamatrices

Isaac Virshup, Philipp Angerer, F. Alexander Wolf, Fabian Joachim Theis, Sergei Rybakov
article en
164 citations

Abstract

anndata is a Python package for handling annotated data matrices in memory and on disk (github.com/scverse/anndata),positioned between pandas and xarray.anndata offers generic data access features including, among others, sparse data support, lazy operations, and a PyTorch interface. Statement of needGenerating 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).

The Journal of Open Source SoftwareVol. 9(101)
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
38.35
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