Automated single-cell omics end-to-end framework with data-driven batch inference.

Cell systems Pub Date : 2024-10-16 Epub Date: 2024-10-03 DOI:10.1016/j.cels.2024.09.003
Yuan Wang, William Thistlethwaite, Alicja Tadych, Frederique Ruf-Zamojski, Daniel J Bernard, Antonio Cappuccio, Elena Zaslavsky, Xi Chen, Stuart C Sealfon, Olga G Troyanskaya
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Abstract

To facilitate single-cell multi-omics analysis and improve reproducibility, we present single-cell pipeline for end-to-end data integration (SPEEDI), a fully automated end-to-end framework for batch inference, data integration, and cell-type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices obtained from different samples into a uniformly annotated and integrated dataset. Without requiring user input, it automatically selects parameters and executes pre-processing, sample integration, and cell-type mapping. It can also perform downstream analyses of differential signals between treatment conditions and gene functional modules. SPEEDI's data-driven batch-inference method works with widely used integration and cell-typing tools. By developing data-driven batch inference, providing full end-to-end automation, and eliminating parameter selection, SPEEDI improves reproducibility and lowers the barrier to obtaining biological insight from these valuable single-cell datasets. The SPEEDI interactive web application can be accessed at https://speedi.princeton.edu/. A record of this paper's transparent peer review process is included in the supplemental information.

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采用数据驱动批量推理的自动化单细胞全息端到端框架。
为了促进单细胞多组学分析并提高可重复性,我们提出了端到端数据整合单细胞管道(Single-cell pipeline for end-to-end data integration,SPEEDI),这是一个用于批量推断、数据整合和细胞类型标记的全自动端到端框架。SPEEDI 引入了数据驱动的批量推断,并将从不同样本获得的异构数据矩阵转化为统一注释和整合的数据集。无需用户输入,它就能自动选择参数并执行预处理、样本整合和细胞类型映射。它还能对处理条件和基因功能模块之间的差异信号进行下游分析。SPEEDI 的数据驱动批量推断方法可与广泛使用的整合和细胞类型工具配合使用。SPEEDI 通过开发数据驱动的批量推断、提供全端到端自动化以及取消参数选择,提高了可重复性,降低了从这些宝贵的单细胞数据集获得生物学见解的门槛。SPEEDI 交互式网络应用程序可通过 https://speedi.princeton.edu/ 访问。本论文的透明同行评审过程记录见补充信息。
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