Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, Cambridgeshire, UK.
Genome Biol. 2024 Aug 1;25(1):205. doi: 10.1186/s13059-024-03349-w.
Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.
许多由联盟产生的数据集旨在以单细胞分辨率描绘健康和疾病组织。虽然经常捕获生物样本和实验信息，但目前缺乏与数据矩阵和分析工作流程相关的详细元数据标准。为了解决这个问题，我们开发了矩阵和分析元数据标准（MAMS），作为数据中心、存储库和工具开发人员的资源。我们定义了分析工作流程中常用的矩阵和参数的元数据字段，并开发了 rmams 包来从单细胞对象中提取 MAMS。总的来说，MAMS 促进了跨平台单细胞数据的协调、集成和可重复性。
