scSorter: assigning cells to known cell types according to marker genes.

scSorter: assigning cells to known cell types according to marker genes.
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DOI:
10.1186/s13059-021-02281-7
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发表时间:
2021-02-22
期刊:
影响因子:
12.3
通讯作者:
Li J
Li J
中科院分区:
生物学1区
文献类型:
--
作者:
Guo H;Li J

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在单细胞 RNA 测序数据上,我们考虑将细胞分配给已知细胞类型的问题,假设细胞类型特异性标记基因的身份已给出,但其确切表达水平不可用,即不使用参考数据集。基于观察到标记基因的预期过度表达通常在不可忽略的细胞比例中不存在,我们开发了一种称为 scSorter 的方法。 scSorter 允许标记基因以低水平表达,并从非标记基因的表达中借用信息。与现有方法相比,scSorter 在模拟数据和实际数据上都显示出更高的功效。在线版本包含可在 (10.1186/s13059-021-02281-7) 获取的补充材料。
On single-cell RNA-sequencing data, we consider the problem of assigning cells to known cell types, assuming that the identities of cell-type-specific marker genes are given but their exact expression levels are unavailable, that is, without using a reference dataset. Based on an observation that the expected over-expression of marker genes is often absent in a nonnegligible proportion of cells, we develop a method called scSorter. scSorter allows marker genes to express at a low level and borrows information from the expression of non-marker genes. On both simulated and real data, scSorter shows much higher power compared to existing methods. The online version contains supplementary material available at (10.1186/s13059-021-02281-7).
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