A Single-Cell Transcriptomic Atlas of Acute Myeloid Leukemia

Applications of single-cell technologies to studying leukemia biology is an ever-expanding field, with a range of emerging datasets coming from different labs using different single cell protocols/technologies. We collate publicly available datasets to create a single-cell transcriptomic atlas of AML (AML scAtlas). For full details on the data, including the studies used, please refer to the related manuscript (https://doi.org/10.1101/2024.10.29.620871).This dataset consists of 748,679 cells, from 159 AML patients and 44 healthy donors from 20 different studies. Attached is a harmonised AnnData object which is compatible with scverse/Scanpy single-cell tools. The complete analysis code can be found at https://github.com/jesswhitts/AML-scAtlas

将单细胞技术应用于研究白血病生物学领域正日益拓展，众多新兴数据集源源不断地涌现，这些数据集源自不同实验室，采用不同的单细胞实验方案/技术。本团队搜集了公开可用的数据集，构建了急性髓系白血病（AML）的单细胞转录组图谱（AML scAtlas）。有关数据的详细信息，包括所使用的实验研究，请参阅相关论文（https://doi.org/10.1101/2024.10.29.620871）。本数据集包含748,679个细胞，来自159名AML患者和44名健康捐献者，涉及20项不同的研究。附带的AnnData对象已实现与scverse/Scanpy单细胞工具的兼容性。完整的分析代码可在https://github.com/jesswhitts/AML-scAtlas找到。