ChromFound: Towards A Universal Foundation Model for Single-Cell Chromatin Accessibiltiy Data
Yifeng Jiao, Yuchen Liu, Yu Zhang, Xin Guo, Yushuai Wu, Chen Jiang, Jiyang Li, Hongwei Zhang, LIMEI HAN, Xin Gao, Yuan Qi, Yuan Cheng
The advent of single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) offers an innovative perspective for deciphering regulatory mechanisms by assembling a vast repository of single-cell chromatin accessibility data. While foundation models have achieved significant success in single-cell transcriptomics, there is currently no foundation model for scATAC-seq that supports zero-shot high-quality cell identification and comprehensive multi-omics analysis simultaneously. Key challenges lie in the high dimensionality and sparsity of scATAC-seq data, as well as the lack of a standardized schema for representing open chromatin regions (OCRs). Here, we present ChromFound, the pioneering foundation model tailored for scATAC-seq. ChromFound utilizes a hybrid architecture and genome-aware tokenization to effectively capture genome-wide long contexts and dynamic chromatin landscapes. Pretrained on a dataset of 1.97 million cells across 30 human tissue types and 6 disease categories, ChromFound showcases its versatility by excelling in 6 diverse tasks. Notably, it demonstrates robust zero-shot performance in generating universal cell representations and exhibits excellent transferability in cell-type annotation and cross-omics prediction. By accurately predicting gene-enhancer connections, ChromFound paves the way for interpreting the functions of various disease risk in the noncoding genome.