scSTEM: clustering pseudotime ordered single-cell data

Qi Song

doi:10.1186/s13059-022-02716-9

2022-07-07

DOI：10.1186/s13059-022-02716-9

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摘要

En 中文

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.

Keyword:

Single cell

Genomics

Gene clustering

Visualization

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期刊

Genome Biology

IF:

9.4

论文数:

6.4K

被引数:

7.3W

机构

Carnegie Mellon University

学者数:

409

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被引数: 0

mcgill university

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论文数: 534

被引数: 0

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