AnnSQL: A Python SQL-based package for fast large-scale single-cell genomics analysis using minimal computational resources
This paper introduces AnnSQL, a Python package that stores AnnData-like single-cell/nucleus genomics data in an AnnData-inspired database backed by the in-process DuckDb engine, allowing SQL-based querying with minimal computational resources. The authors benchmark performance on a 4.4 million cell single-nucleus RNA-seq dataset, reporting that AnnSQL operations ran in minutes on a laptop and that equivalent AnnData operations largely failed on an HPC cluster or were up to ~700 times slower. A stated caveat is that the work focuses on demonstrating database construction and runtime improvements rather than providing complete end-to-end single-cell workflows across all analysis stages. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works
Abstract
Full text
1,471 characters
· extracted from
oa-doi-fallback
· click to expand
Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.
My notes (saved in your browser only)
Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.
Source provenance
- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00
- unpaywall
- last seen: 2026-06-13T06:42:57.164913+00:00