Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering

被引：0
|
作者：
Zhijin Wu
Hao Wu
机构：
[1] Department of Biostatistics,
[2] Brown University,undefined
[3] Department of Biostatistics and Bioinformatics,undefined
[4] Rollins School of Public Health,undefined
[5] Emory University,undefined
来源：
Genome Biology | / 21卷
关键词：
Gene expression; Single cell RNA-seq; Clustering;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Cell clustering is one of the most common routines in single cell RNA-seq data analyses, for which a number of specialized methods are available. The evaluation of these methods ignores an important biological characteristic that the structure for a population of cells is hierarchical, which could result in misleading evaluation results. In this work, we develop two new metrics that take into account the hierarchical structure of cell types. We illustrate the application of the new metrics in constructed examples as well as several real single cell datasets and show that they provide more biologically plausible results.
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