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  • 标题:Time-variant clustering model for understanding cell fate decisions
  • 本地全文:下载
  • 作者:Wei Huang ; Xiaoyi Cao ; Fernando H. Biase
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2014
  • 卷号:111
  • 期号:44
  • 页码:E4797-E4806
  • DOI:10.1073/pnas.1407388111
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:SignificanceClustering, in essence, was a tool for describing spatial characteristics in the objects of concern. However, from social to biological studies, researchers' interests in temporal characteristics often rival their interests in spatial features. Previous efforts to incorporate time information into clustering primarily relied on coding the time information into similarity metrics, thus reducing the problem into the classical paradigm of spatial clustering. The limitation is that the clustering outcomes are often time invariant. Here, we initiate a class of statistical methods that simultaneously infer spatial and temporal groupings. Such methods explicitly model the time dependencies of clustering indices over time. Our method inferred three genes to be associated with the earliest cell fate decision, which was corroborated by experimental validations. Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development.
  • 关键词:clustering ; time ; branching process ; embryonic development ; cell fate
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