使用 Jaccard 相似性指数评估单细胞聚类稳定性。
Evaluating single-cell cluster stability using the Jaccard similarity index.
机构信息
FAS Informatics Group, Harvard University, Cambridge, MA, USA.
Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, MA, USA.
出版信息
Bioinformatics. 2021 Aug 9;37(15):2212-2214. doi: 10.1093/bioinformatics/btaa956.
MOTIVATION
One major goal of single-cell RNA sequencing (scRNAseq) experiments is to identify novel cell types. With increasingly large scRNAseq datasets, unsupervised clustering methods can now produce detailed catalogues of transcriptionally distinct groups of cells in a sample. However, the interpretation of these clusters is challenging for both technical and biological reasons. Popular clustering algorithms are sensitive to parameter choices, and can produce different clustering solutions with even small changes in the number of principal components used, the k nearest neighbor and the resolution parameters, among others.
RESULTS
Here, we present a set of tools to evaluate cluster stability by subsampling, which can guide parameter choice and aid in biological interpretation. The R package scclusteval and the accompanying Snakemake workflow implement all steps of the pipeline: subsampling the cells, repeating the clustering with Seurat and estimation of cluster stability using the Jaccard similarity index and providing rich visualizations.
AVAILABILITYAND IMPLEMENTATION
R package scclusteval: https://github.com/crazyhottommy/scclusteval Snakemake workflow: https://github.com/crazyhottommy/pyflow_seuratv3_parameter Tutorial: https://crazyhottommy.github.io/EvaluateSingleCellClustering/.
动机
单细胞 RNA 测序（scRNAseq）实验的主要目标之一是鉴定新的细胞类型。随着越来越大的 scRNAseq 数据集，无监督聚类方法现在可以在样本中产生转录上不同的细胞群的详细目录。然而，由于技术和生物学原因，这些聚类的解释具有挑战性。流行的聚类算法对参数选择敏感，即使在用于主成分数量、最近邻 k 和分辨率参数等的微小变化下，也可以产生不同的聚类解决方案。
结果
在这里，我们提出了一套通过抽样评估聚类稳定性的工具，这可以指导参数选择并有助于生物学解释。R 包 scclusteval 和随附的 Snakemake 工作流程实现了该管道的所有步骤：对细胞进行抽样、使用 Seurat 重复聚类以及使用 Jaccard 相似性指数估计聚类稳定性，并提供丰富的可视化效果。
可用性和实现
R 包 scclusteval：https://github.com/crazyhottommy/scclusteval Snakemake 工作流程：https://github.com/crazyhottommy/pyflow_seuratv3_parameter 教程：https://crazyhottommy.github.io/EvaluateSingleCellClustering/。
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