scLAP: A Liver-Adapted Contrastive Shared-Latent Framework for Pseudo-Pairing Single-Cell Transcriptomes and Chromatin Accessibility Profiles
- 1Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003, China
- 2Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
Abstract
Matched single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) profiles from the same cells remain limited in hepatocellular carcinoma (HCC), hindering cell-resolved integration of transcriptional programs and regulatory chromatin states. To address this challenge, we developed single-cell Liver-adapted Alignment and Pseudo-pairing (scLAP), a liver-adapted contrastive shared-latent framework for cross-study RNA-ATAC pseudo-pairing. scLAP was trained on a paired liver single-nucleus multiome reference using 2000 highly variable RNA features and 697 ATAC features, including 647 transcription factor motif activity scores and 50 latent semantic indexing components. On a prespecified cell-level test partition (n = 3235), scLAP achieved an ATAC-to-RNA Top 10 exact-pair retrieval rate of 21.48% and a mean fraction of samples closer than the true match (FOSCTTM) of 0.0431. In six leave-one-sample-out folds, the corresponding macro means were 5.23% and 0.2278, respectively, indicating above-random ranking but limited exact-pair transfer to unseen samples. A validation-selected scButterfly configuration using 20,000 native ATAC peaks achieved 8.93% Top 10 retrieval and a mean FOSCTTM of 0.0811 on the same test cells; comparisons with Con-AAE and scMODAL remained study-specific adaptations. Applying reciprocal retrieval, a validation-derived cosine-similarity threshold, and greedy one-to-one assignment to independent HCC datasets yielded 4007 similarity-filtered candidate RNA-ATAC pseudo-pairs. Downstream analyses identified an NRCAM-associated accessibility candidate and separate exploratory MET-, CAV1-, and AP-1-associated observations.
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BibTeX
@article{li2026sclap,
title = {{scLAP: A Liver-Adapted Contrastive Shared-Latent Framework for Pseudo-Pairing Single-Cell Transcriptomes and Chromatin Accessibility Profiles}},
author = {Hongfei Li and Jiechen Wang and Huan Yang},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = nov,
doi = {10.3390/ijms27219888},
url = {https://www.mdpi.com/1422-0067/27/21/9888},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - scLAP: A Liver-Adapted Contrastive Shared-Latent Framework for Pseudo-Pairing Single-Cell Transcriptomes and Chromatin Accessibility Profiles
AU - Hongfei Li
AU - Jiechen Wang
AU - Huan Yang
PY - 2026
DA - 2026/11/04
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27219888
UR - https://www.mdpi.com/1422-0067/27/21/9888
AB - Matched single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) profiles from the same cells remain limited in hepatocellular carcinoma (HCC), hindering cell-resolved integration of transcriptional programs and regulatory chromatin states. To address this challenge, we developed single-cell Liver-adapted Alignment and Pseudo-pairing (scLAP), a liver-adapted contrastive shared-latent framework for cross-study RNA-ATAC pseudo-pairing. scLAP was trained on a paired liver single-nucleus multiome reference using 2000 highly variable RNA features and 697 ATAC features, including 647 transcription factor motif activity scores and 50 latent semantic indexing components. On a prespecified cell-level test partition (n = 3235), scLAP achieved an ATAC-to-RNA Top 10 exact-pair retrieval rate of 21.48% and a mean fraction of samples closer than the true match (FOSCTTM) of 0.0431. In six leave-one-sample-out folds, the corresponding macro means were 5.23% and 0.2278, respectively, indicating above-random ranking but limited exact-pair transfer to unseen samples. A validation-selected scButterfly configuration using 20,000 native ATAC peaks achieved 8.93% Top 10 retrieval and a mean FOSCTTM of 0.0811 on the same test cells; comparisons with Con-AAE and scMODAL remained study-specific adaptations. Applying reciprocal retrieval, a validation-derived cosine-similarity threshold, and greedy one-to-one assignment to independent HCC datasets yielded 4007 similarity-filtered candidate RNA-ATAC pseudo-pairs. Downstream analyses identified an NRCAM-associated accessibility candidate and separate exploratory MET-, CAV1-, and AP-1-associated observations.
SN - 1422-0067
ER -