LISA: Accurate reconstruction of cell trajectory and pseudo-time for massive single cell RNA-seq data
LISA: Accurate reconstruction of cell trajectory and pseudo-time for massive single cell RNA-seq data
复制标题
LISA：海量单细胞RNA-seq数据的细胞轨迹和伪时间的精确重建
DOI：
10.1142/9789813279827_0031
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Z. Ouyang
中科院分区：
文献类型：
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作者：
Yang Chen;Yuping Zhang;Z. Ouyang
基于单细胞RNA测序的细胞轨迹重建对于获得不同细胞类型的景观和发现细胞命运转变具有重要意义。尽管付出了巨大的努力，但分析大量单细胞RNA-seq数据集仍然具有挑战性。我们提出了一种新的方法命名为地标Isomap单细胞分析（丽莎）。丽莎是一种基于测地距离的等距嵌入中的无监督细胞轨迹构建和伪时间计算方法。丽莎的优点包括：（1）利用k-近邻图和层次聚类识别数据低维表示中的细胞簇、峰和谷;（2）基于Landmark Isomap构建细胞谱系的主要几何结构;（3）将细胞投影到主要细胞轨迹的边缘，生成全局伪时间。对模拟和真实的数据集的评估表明，与Monocle 2和TSCAN相比，丽莎在细胞轨迹和伪时间重建方面具有优势。丽莎准确，快速，需要较少的内存使用，允许其应用于从当前实验平台生成的大量单细胞数据集。
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 advantages of LISA on cell trajectory and pseudo-time reconstruction compared to Monocle2 and TSCAN. LISA is accurate, fast, and requires less memory usage, allowing its applications to massive single cell datasets generated from current experimental platforms.