AnnSQL: A Python SQL-based package for fast large-scale single-cell genomics analysis using minimal computational resources.

Kenny Pavan, Arpiar Saunders
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引用次数: 0

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 implementation: AnnSQL is a pip installable package that can be found at https://github.com/ArpiarSaundersLab/annsql along with documentation at https://docs.annsql.com .

AnnSQL:一个基于Python sql的包,用于笔记本电脑上的大规模单细胞基因组分析。
随着单细胞基因组学技术不断加速生物发现,越来越需要使用优雅语法和最小计算资源来分析atlas规模数据集的软件工具。在这里,我们介绍一个Python包AnnSQL,它使用进程内DuckDb引擎构建了一个受anndata启发的数据库,通过SQL的易用性实现了数量级的性能增强,可以解析单细胞基因组数据集。我们强调了AnnSQL的功能,并通过比较440万细胞单核RNA-seq数据集上的AnnData或AnnSQL操作来展示变换器运行时的改进:在笔记本电脑上,基于AnnSQL的操作在几分钟内执行,而在高性能计算集群上,等效的AnnData操作基本上失败(或慢约700倍)。AnnSQL降低了在个人计算机上进行大规模单细胞/细胞核RNA-seq分析的计算障碍,同时展示了一个有前途的计算基础设施,可扩展到跨各种全基因组测量的完整单细胞工作流程。可用性和实现:AnnSQL是一个pip可安装包,可以通过使用文档访问:https://github.com/ArpiarSaundersLab/annsql。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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