Atacformer: A transformer-based foundation model for analysis and interpretation of ATAC-seq data.

ABSTRACT:

Introduction

Chromatin accessibility profiling is an important tool for understanding gene regulation and cellular function. While public repositories house nearly 10,000 scATAC-seq experiments, unifying this data for meaningful analysis remains challenging. Existing tools struggle with the scale and complexity of scATAC-seq datasets, limiting tasks like clustering, cell-type annotation, and reference mapping. A promising solution is using foundation models adapted to specific tasks via transfer learning. While transfer learning has been applied to scRNA-seq, its potential for scATAC-seq remains underexplored.

Methods

We introduce Atacformer, a transformer-based foundation model for scATAC-seq data analysis. Unlike other models that only produce cell-level representations, A

SUBMITTER: LeRoy NJ 

PROVIDER: S-EPMC12637716 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature