scJET: Full-gene Space Single-cell Expression Generation with Patch-based Transformer Modeling

Authors

Liang, Q., Lyu, Q. R.

Abstract

Most single-cell generative models rely on highly variable genes (HVGs) or low-dimensional latent representations, limiting their capacity to capture the complexity of full-gene features. We present scJET, a patch-based Transformer denoising framework that operates in full-gene space. scJET preserves global manifold structure, local neighborhood statistics, and gene-level expression programs. By combining scalable patch tokenization with full-gene denoising, scJET provides an efficient framework for transcriptome-wide single-cell matrix generation.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 10 Jul 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.