| 项目编号 | PRJCA016296 | ||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 项目标题 | Single-cell RNA-seq of peripheral blood mono nuclear cells (PBMCs) from 26 donors and 5 NSCLC cell lines | ||||||||||||||||||||||||||||||||||||
| 涉及领域 | Medical | ||||||||||||||||||||||||||||||||||||
| 数据类型 | Single cell sequencing | ||||||||||||||||||||||||||||||||||||
| 物种名称 | Homo sapiens | ||||||||||||||||||||||||||||||||||||
| 描述信息 | Single-cell RNA-seq (scRNA-seq) analysis of multiple samples separately is expensive and may cause batch effect. Multiplexing several samples for one experiment using exogenous barcodes or demultiplexing scRNA-seq data based on genome-wide RNA mutations is experimentally or computationally challenging and scale-limited, respectively. Mitochondria is a smaller genome set that can provide concise information for individual genotypes. In this study, we developed a computational algorithm "mitoSpliter" that enables sample demultiplexing based on somatic mutations in mitochondrial RNA (mtRNA). We demonstrated that mtRNA variants are computationally capable of demultiplexing large-scale scRNA-seq data. The analysis of peripheral blood mononuclear cells (PBMCs) revealed that mitoSpliter can accurately analyze up to 10 samples and 60K cells in a single experiment in ~6 hours on affordable computational resources. Further application of mitoSpliter to non-small cell lung cancer (NSCLC) cells uncovered the synthetic lethality of TOP2A inhibition and BET chemical degradation in the BET inhibitor-resistant cells, indicating that mitoSpliter will accelerate the application of scRNA-seq assay in biomedical research. | ||||||||||||||||||||||||||||||||||||
| 样品范围 | Single cell | ||||||||||||||||||||||||||||||||||||
| 发布日期 | 2023-04-17 | ||||||||||||||||||||||||||||||||||||
| 项目资金来源 |
|
||||||||||||||||||||||||||||||||||||
| 提交者 | Xinrui Lin (linxinrui@renji.com) | ||||||||||||||||||||||||||||||||||||
| 提交单位 | Shanghai Jiaotong University School of Medicine | ||||||||||||||||||||||||||||||||||||
| 提交日期 | 2023-04-17 |
| 资源名称 | 描述 |
|---|---|
| BioSample (35) show | - |