作者
Yang Chen, Yuping Zhang, Zhengqing Ouyang
发表日期
2019
期刊
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
卷号
24
页码范围
338-349
简介
Cell trajectory reconstruction based on single cell RNA sequencing is important for obtaining the landscape of different cell types and discovering cell fate transitions. Despite intense effort, analyzing massive single cell RNA-seq datasets is still challenging. We propose a new method named Landmark Isomap for Single-cell Analysis (LISA). LISA is an unsupervised approach to build cell trajectory and compute pseudo-time in the isometric embedding based on geodesic distances. The advantages of LISA include:(1) It utilizes k-nearest-neighbor graph and hierarchical clustering to identify cell clusters, peaks and valleys in low-dimension representation of the data;(2) Based on Landmark Isomap, it constructs the main geometric structure of cell lineages;(3) It projects cells to the edges of the main cell trajectory to generate the global pseudo-time. Assessments on simulated and real datasets demonstrate the …
引用总数
2020202120222023202414121
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