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Cellular deconvolution with continuous transitions
DOI:10.1038/s43588-023-00489-0.png)
摘要
En 中文
A recent work introduces a cellular deconvolution method, MeDuSA, of estimating cell-state abundance along a one-dimensional trajectory from bulk RNA-seq data with fine resolution and high accuracy, enabling the characterization of cell-state transition in various biological processes.
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IF:
18.3
论文数:
3.1K
被引数:
4.0K
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引用论文
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells单细胞的假时间顺序揭示了细胞命运决定的动力学和调节剂
NATURE BIOTECHNOLOGY
IF41.7
Mixed model-based deconvolution of cell-state abundances (MeDuSA) along a one-dimensional trajectory
A benchmark for RNA-seq deconvolution analysis under dynamic testing environments动态测试环境下rna-seq反卷积分析的基准
GENOME BIOLOGY
IF9.4
Determining cell type abundance and expression from bulk tissues with digital cytometry用数字细胞仪确定大块组织的细胞类型丰度和表达
NATURE BIOTECHNOLOGY
IF41.7
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