scSTEM: clustering pseudotime ordered single-cell data.

scSTEM: clustering pseudotime ordered single-cell data.
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DOI:
10.1186/s13059-022-02716-9
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发表时间:
2022-07-07
期刊:
影响因子:
12.3
通讯作者:
--
中科院分区:
生物学1区
文献类型:
--
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我们开发了scSTEM,单细胞STEM,一种根据单细胞RNA-seq(scRNA-seq)数据的伪时间排序(scRNA-seq)数据推断的轨迹中基因动态图谱的聚类方法。ScSTEM使用几种度量中的一种来总结基因的表达,并将p值分配给集群,从而能够识别重要的图谱并比较不同路径上的图谱。将scSTEM应用于几个scRNA-seq数据集,证明了其在改进生物过程下游分析方面的有效性和能力。SCSTEM可在https://github.com/alexQiSong/scSTEM.上获得。网上版载有补充材料,可在10.1186/s13059-022-02716-9查阅。
We develop scSTEM, single-cell STEM, a method for clustering dynamic profiles of genes in trajectories inferred from pseudotime ordering of single-cell RNA-seq (scRNA-seq) data. scSTEM uses one of several metrics to summarize the expression of genes and assigns a p-value to clusters enabling the identification of significant profiles and comparison of profiles across different paths. Application of scSTEM to several scRNA-seq datasets demonstrates its usefulness and ability to improve downstream analysis of biological processes. scSTEM is available at https://github.com/alexQiSong/scSTEM. The online version contains supplementary material available at 10.1186/s13059-022-02716-9.
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