A Single-Cell Transcriptomic Atlas of Acute Myeloid Leukemia
<p dir="ltr">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. Here, we collated publicly available datasets to create a si...
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2025
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| Summary: | <p dir="ltr">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. Here, we collated 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/10.7554/eLife.104978.2</p><p dir="ltr">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 <a href="https://github.com/jesswhitts/AML-scAtlas" rel="noreferrer" target="_blank">https://github.com/jesswhitts/AML-scAtlas</a></p> |
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