Bioinformatics AdvancesBioinformaticsPeer-reviewed journal article
AnnSQL: A Python SQL-based package for fast large-scale single-cell genomics analysis using minimal computational resources
Abstract
As single-cell genomics technologies continue to accelerate biological discovery, software tools that use elegant syntax and minimal computational resources to analyze atlas-scale datasets are increasingly needed. Here we introduce AnnSQL, a Python package that constructs an AnnData-inspired database using the in-process DuckDb engine, enabling orders-of-magnitude performance enhancements for parsing single-cell genomics datasets with the ease of SQL. We highlight AnnSQL functionality and demonstrate transformative runtime improvements by comparing AnnData or AnnSQL operations on a 4.4 million cell single-nucleus RNA-seq dataset: AnnSQL-based operations were executed in minutes on a laptop for which equivalent AnnData operations largely failed (or were [~]700x slower) on a high-performance computing cluster. AnnSQL lowers computational barriers for large-scale single-cell/nucleus RNA-seq analysis on a personal computer, while demonstrating a promising computational infrastructure extendable for complete single-cell workflows across various genome-wide measurements. Availability and ImplementationAnnSQL is a pip installable package that can be found at https://github.com/ArpiarSaundersLab/annsql along with documentation at https://docs.annsql.com.
- assay: scRNA-seq
- research focus: benchmarking
- research focus: software / tool
- research focus: dimensionality reduction
- research focus: clustering
- approach: statistical model
- approach: experimental assay
- Citations
- 1
- FWCI
- 0.14
- Field percentile
- 43th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- cellsnake: a user-friendly tool for single-cell RNA sequencing analysis
Sinan U. Umu, Karoline Rapp Vander-Elst, … Diana Domańska·GigaSciencePeer-reviewed·Dec 28, 2022
- ICARUS v3, a massively scalable web server for single cell RNA-seq analysis of millions of cells.
Andrew Jiang, Russell G. Snell, Klaus Lehnert·BioinformaticsPeer-reviewed·Mar 25, 2024
- User-friendly, scalable tools and workflows for single-cell analysis
Pablo A Moreno, Ni Huang, … Irene Papatheodorou·Nature MethodsPeer-reviewed·Mar 29, 2021
- Scalable high-performance single cell data analysis with BPCells
Benjamin E. Parks, William James Greenleaf·bioRxiv·Mar 27, 2025
- SingleRust: A High-Performance Toolkit for Single-Cell Data Analysis at Scale
Ian Ferenc Diks, Matthias Flotho, Andreas Keller·bioRxiv·Aug 4, 2025
- Cumulus: a cloud-based data analysis framework for large-scale single-cell and single-nucleus RNA-seq
Bo Li, Joshua Gould, … Aviv Regev·Nature MethodsPeer-reviewed·Jul 27, 2020