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Related Experiment Video

Updated: May 26, 2026

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

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

This summary is machine-generated.

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.

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Last Updated: May 26, 2026

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Analysis of Multidimensional Microscopy Data Using Cell-ACDC

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Published on: November 7, 2025

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.