Sign in
BioinformaticsbioRxiv
Preprint

ImmuneLens: linking transcriptional states and TCR clonotypes through disentangled multimodal learning

Zhijian Duan, Yi WangiD, Cuiping LiiD, Guochao Li, Yongrong CaoiD, Xue Bai, Fei YangiD, Shuhui SongiD

Abstract

Single-cell multi-omics technologies simultaneously capture the transcriptome and TCR sequence of T cells, providing an opportunity to study the relationship between transcriptional states and clonal architectures. However, jointly modeling the relationships between transcriptional states and TCR sequences while preserving modality-specific information remains challenging. Here, we present ImmuneLens, an interpretable multimodal representation learning framework designed for paired single-cell transcriptome and TCR sequence data. ImmuneLens supports the construction of a transferable multi-cohort immune reference atlas and enables unsupervised mapping of external query data. The complementarity between GEX and TCR information improves the stability of antigen-specificity prediction. In neoadjuvant immunotherapy cohorts, ImmuneLens resolves response-associated T cell heterogeneity and reveals links between clonal expansion and CD8 T cell functional states. Overall, ImmuneLens provides a

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISDrost '24Mullan '24Shorer '26Gao '23Lai '25Stubbington '16
68% semantic matchBioinformatics
Felix Drost, Yang An, Irene Bonafonte-Pardàs+7 more·Nature Communications·Jul 2, 2024· 53 citations