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SCOT+: a comprehensive software suite for single-cell alignment using optimal transport
Colin Baker1, Tuan Pham1, Pinar Demetci2
1Center for Computational Molecular Biology, Brown University, Providence, RI 02906, United States.
Bioinformatics Advances
|May 25, 2026
Summary
Single Cell alignment using Optimal Transport+ (SCOT+) is a new software suite for aligning single-cell multi-omics data. It enables accurate downstream analyses by integrating disparate datasets without requiring cell correspondence.
Area of Science:
- Computational Biology
- Genomics
- Bioinformatics
Background:
- Single-cell multi-omics experiments offer insights into cellular processes but face challenges with resource-intensive measurements.
- Current technologies limit the ability to measure multiple cellular features simultaneously for a single cell.
Purpose of the Study:
- To develop an unsupervised single-cell alignment software suite, SCOT+, to integrate data from disparate single-cell multi-omics experiments.
- To provide a unified framework for existing optimal transport (OT) formulations and introduce novel OT-based methods.
Main Methods:
- Utilizes optimal transport (OT) to align cells and features across datasets from separate assays.
- Implements a generic OT solution that encompasses prior methods like SCOT, SCOTv2, SCOOTR, and AGW.
- Introduces a new OT loss, Unbalanced Augmented Gromov-Wasserstein (UAGW), and its optimizer.
Main Results:
- SCOT+ allows for data alignment without the need for cell correspondence.
- The software suite provides state-of-the-art single-cell alignment performance.
- Offers a unified framework for various OT-based single-cell alignment strategies.
Conclusions:
- SCOT+ enhances biological analyses by enabling more accurate downstream analyses on multi-omics single-cell measurements.
- The user-friendly website and tutorials facilitate the adoption of SCOT+ in biological research.
- The developed software improves the integration and analysis of complex single-cell data.
