{"doi":"10.1101/2021.12.16.473007","title":"anndata: Annotated data","abstract":"<h4>Summary</h4> 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. <h4>Statement of need</h4> 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).","journal":null,"year":2021,"id":4971,"datarank":0.8590271621380796,"base_score":5.726847747587197,"endowment":5.726847747587197,"self_citation_contribution":0.8590271621380796,"citation_network_contribution":0.0,"self_endowment_contribution":0.8590271621380796,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":306,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0504,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-12-19","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1695,"name":"Sergei Rybakov","orcid":"0000-0002-4944-6586","position":1,"is_corresponding":false},{"id":42,"name":"Fabian Joachim Theis","orcid":"0000-0002-2419-1943","position":2,"is_corresponding":false},{"id":3570,"name":"Philipp Angerer","orcid":"0000-0002-0369-2888","position":3,"is_corresponding":false},{"id":3587,"name":"Francesca Finotello","orcid":"0000-0003-0712-4658","position":4,"is_corresponding":false},{"id":3582,"name":"Valeh Valiollah Pour Amiri","orcid":"0000-0002-2008-5297","position":0,"is_corresponding":true}],"reference_count":24,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}