Baker Colin, Pham Tuan, Demetci Pinar, Tran Quang Huy, Redko Ievgen, Sandstede Bjorn, Singh Ritambhara
Center for Computational Molecular Biology, Brown University, Providence, RI.
Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA.
bioRxiv. 2025 May 27:2025.05.21.655322. doi: 10.1101/2025.05.21.655322.
New advances in single-cell multi-omics experiments have allowed biologists to examine how various biological factors regulate processes in concert on the cellular level. However, measuring multiple cellular features for a single cell can be quite resource-intensive or impossible with the current technology. By using optimal transport (OT) to align cells and features across disparate datasets produced by separate assays, Single Cell alignment using Optimal Transport+ (SCOT+), our unsupervised single-cell alignment software suite, allows biologists to align their data without the need for any correspondence. SCOT+ has a generic optimal transport solution that can be reduced to multiple different OT optimization procedures, each of which provide state-of-the-art single-cell alignment performance. With our user-friendly website and tutorials, this new package will help improve biological analyses by allowing for more accurate downstream analyses on multi-omics single-cell measurements.
Our algorithm is implemented in Pytorch and available on PyPI and GitHub (https://github.com/scotplus/scotplus). Additionally, we have many tutorials available in a separate GitHub repository (https://github.com/scotplus/book_source) and on our website (https://scotplus.github.io/).
单细胞多组学实验的新进展使生物学家能够在细胞水平上研究各种生物因素如何协同调节生物学过程。然而,使用当前技术对单个细胞测量多种细胞特征可能相当耗费资源甚至无法实现。通过使用最优传输(OT)来对齐由单独检测产生的不同数据集中的细胞和特征,我们的无监督单细胞对齐软件套件——使用最优传输的单细胞对齐工具(SCOT+),使生物学家能够在无需任何对应关系的情况下对齐他们的数据。SCOT+具有通用的最优传输解决方案,可简化为多种不同的OT优化程序,每个程序都能提供最先进的单细胞对齐性能。借助我们用户友好的网站和教程,这个新软件包将通过允许对多组学单细胞测量进行更准确的下游分析来帮助改进生物学分析。
我们的算法在Pytorch中实现,可在PyPI和GitHub(https://github.com/scotplus/scotplus)上获取。此外,我们在一个单独的GitHub仓库(https://github.com/scotplus/book_source)和我们网站(https://scotplus.github.io/)上有许多教程。