标题： TrajLens：跨样本探索中构建细胞发育轨迹的可视化分析 显示英文标题

标题： TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration

摘要： 构建细胞发育轨迹是单细胞RNA测序(scRNA-seq)分析中的关键任务，能够推断潜在的细胞进展路径。 然而，当前的自动化方法仅限于在单个样本内建立细胞发育轨迹，需要生物学家手动连接不同样本中的细胞，以构建考虑细胞空间动态的完整跨样本进化轨迹。 由于每对样本之间的复杂空间对应关系，这一过程需要大量的人工努力。 为了解决这一挑战，我们首先提出了一种基于图神经网络(GNN)的模型来预测跨样本的细胞发育轨迹。 随后，我们开发了TrajLens，这是一种可视化分析系统，支持生物学家根据预测的连接关系探索和优化细胞发育轨迹。 具体而言，我们设计了整合多个样本中细胞分布和发展方向特征的可视化界面，提供了沿轨迹的细胞群体空间进化模式的概览。 此外，我们在原始细胞分布数据上叠加了等高线图，使生物学家能够直观地进行探索。 为了展示我们系统的性能，我们通过两个案例研究和专家访谈对我们的模型进行了定量评估，以验证其有用性和有效性。 显示英文摘要

摘要： Constructing cell developmental trajectories is a critical task in single-cell RNA sequencing (scRNA-seq) analysis, enabling the inference of potential cellular progression paths. However, current automated methods are limited to establishing cell developmental trajectories within individual samples, necessitating biologists to manually link cells across samples to construct complete cross-sample evolutionary trajectories that consider cellular spatial dynamics. This process demands substantial human effort due to the complex spatial correspondence between each pair of samples. To address this challenge, we first proposed a GNN-based model to predict cross-sample cell developmental trajectories. We then developed TrajLens, a visual analytics system that supports biologists in exploring and refining the cell developmental trajectories based on predicted links. Specifically, we designed the visualization that integrates features on cell distribution and developmental direction across multiple samples, providing an overview of the spatial evolutionary patterns of cell populations along trajectories. Additionally, we included contour maps superimposed on the original cell distribution data, enabling biologists to explore them intuitively. To demonstrate our system's performance, we conducted quantitative evaluations of our model with two case studies and expert interviews to validate its usefulness and effectiveness.