^: co-first author
Hu H, Wang X, Feng S, Xu Z, Liu J, O’Hare E,
Chen Y, Yue M, Zeng L, Rong Z, Chen T, Billiar T, Ding Y, Huang H, Duerr
R, Chen W. A unified model-based framework for doublet or multiplet
detection in single-cell multiomics data. Nature
Communications. 15, 5562 (2024). https://doi.org/10.1038/s41467-024-49448-x
(Selected as a featured article in “Biotechnology and methods”
section)
Wang X, Xu Z, Hu H, Zhou X, Zhang Y, Lafyatis R,
Chen K, Huang H, Ding Y, Duerr R, Chen W. SECANT: a biology-guided
semi-supervised method for clustering, classification, and annotation of
single-cell multi-omics. PNAS Nexus. 2022 Sep; 1(4):
pgab165 https://doi.org/10.1093/pnasnexus/pgac165
Chen Y, Wu X, Ni K, Hu H, Yue M, Chen W, Huang
H. Robust and Accurate Doublet Detection of Single-Cell Sequencing Data
via Maximizing Area Under Precision-Recall Curve. bioRxiv; doi:
https://doi.org/10.1101/2023.10.30.564840
Rong Z^, Hu H^, Duan J, Liu T, Feng S, Zhao C, Duerr, R, Zhou X, Chen W. scDitu: a cluster-free method for identifying isoform-level differential transcript usage in sparse single-cell long-read sequencing data. Under review at RECOMB conference
Yue M, Cai M, Zhao C, Tao S, Liu J, Hu H, Chen Y, Celedon J, Wang J, Huang H, Chen W. Multi-Omics intermediate Fusion Enable Digital White Blood Cells Count Prediction. Submitted to Genome Medicine
Yuan R, Rong Z, Hu H, Liu T, Tao S, Chen W. Harmony-Based Data Integration for Distributed Single-Cell Multi-Omics Data. Submitted to Nature Communications