Novartis Institutes for Biomedical Research, Basel, Switzerland.
Present Address: Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Genome Biol. 2019 Jul 17;20(1):142. doi: 10.1186/s13059-019-1739-7.
We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.
我们开发了 CellSIUS（基于上调基因集的细胞亚型识别），以填补 scRNA-seq 数据中稀有细胞群体识别方法学上的空白。CellSIUS 在稀有细胞类型及其转录组特征识别的特异性和选择性方面优于现有的算法，在合成和复杂的生物学数据中也是如此。使用 CellSIUS 对一个重现深层皮质发生的人类多能干细胞分化方案进行特征描述，揭示了人类干细胞衍生细胞群体中以前未被认识到的复杂性。CellSIUS 能够识别新的稀有细胞群体及其特征基因，为研究这些群体在健康和疾病中的作用提供了在体外研究这些群体的方法。
