School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China.
School of Mathematical Sciences, Fudan University, Shanghai 200433, China.
Bioinformatics. 2023 Feb 3;39(2). doi: 10.1093/bioinformatics/btad054.
The development of single-cell RNA sequencing (scRNA-seq) technology makes it possible to study the cellular dynamic processes such as cell cycle and cell differentiation. Due to the difficulties in generating genuine time-series scRNA-seq data, it is of great importance to computationally infer the pseudotime of the cells along differentiation trajectory based on their gene expression patterns. The existing pseudotime prediction methods often suffer from the high level noise of single-cell data, thus it is still necessary to study the single-cell trajectory inference methods.
In this study, we propose a branched local tangent space alignment (BLTSA) method to infer single-cell pseudotime for multi-furcation trajectories. By assuming that single cells are sampled from a low-dimensional self-intersecting manifold, BLTSA first identifies the tip and branching cells in the trajectory based on cells' local Euclidean neighborhoods. Local coordinates within the tangent spaces are then determined by each cell's local neighborhood after clustering all the cells to different branches iteratively. The global coordinates for all the single cells are finally obtained by aligning the local coordinates based on the tangent spaces. We evaluate the performance of BLTSA on four simulation datasets and five real datasets. The experimental results show that BLTSA has obvious advantages over other comparison methods.
R codes are available at https://github.com/LiminLi-xjtu/BLTSA.
Supplementary data are available at Bioinformatics online.
单细胞 RNA 测序 (scRNA-seq) 技术的发展使得研究细胞周期和细胞分化等细胞动态过程成为可能。由于难以生成真实的时间序列 scRNA-seq 数据，因此根据细胞的基因表达模式推断细胞在分化轨迹上的伪时间是非常重要的。现有的伪时间预测方法往往受到单细胞数据高噪声的影响，因此仍然有必要研究单细胞轨迹推断方法。
在这项研究中，我们提出了一种分支局部切空间对齐 (BLTSA) 方法，用于推断多分叉轨迹的单细胞伪时间。通过假设单细胞是从低维自相交流形中采样的，BLTSA 首先基于细胞的局部欧几里得邻域识别轨迹中的尖端和分支细胞。然后，通过对所有细胞进行迭代聚类到不同分支，确定每个细胞的局部邻域内的局部坐标。最后，通过基于切空间对齐局部坐标，获得所有单细胞的全局坐标。我们在四个模拟数据集和五个真实数据集上评估了 BLTSA 的性能。实验结果表明，BLTSA 明显优于其他比较方法。
R 代码可在 https://github.com/LiminLi-xjtu/BLTSA 上获得。
补充数据可在生物信息学在线获得。
