Searching journal content for articles similar to Wang and Liu 35 (2): 340.

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  1. Method: scSHEFT enables multiomics label transfer from scRNA-seq to scATAC-seq through dual alignment
    • Zhitao Huang,
    • Ruiqing Zheng,
    • Pengzhen Jia,
    • Xuhua Yan,
    • Jinmiao Chen,
    • and Min Li
    Genome Res. February 2026 36: 387-396; Published in Advance January 20, 2026, doi:10.1101/gr.280410.125
    ...can be divided into two types. Their major difference lies in the way to process the raw omics features. The first type of methods directly uses gene expression count data from scRNA-seq and peak count data from scATAC-seq as input to the model, and uses omics-specific neural networks to embed them...
  2. Method: Recovering gene regulatory networks in single-cell multi-omics data with PRISM-GRN
    • Wenhao Zhang,
    • Lan Cao,
    • Xiaoxuan Gu,
    • Yongyu Long,
    • and Ying Wang
    Genome Res. January 2026 36: 142-158; Published in Advance October 9, 2025, doi:10.1101/gr.280757.125
    ...) for supervised link prediction in GRN inference, leveraging scRNA-seq data and existing regulatory information to predict latent TF–gene interactions. Similarly, Grace (Wang et al. 2024a) integrates structural causal models with graph neural networks to infer both GRNs and gene causality from scRNA-seq data...
  3. Method: Debiased personalized gene coexpression networks for population-scale scRNA-seq data
    • Shan Lu and
    • Sunduz Keles
    Genome Res. June 9, 2023 gr.277363.122; Published in Advance June 9, 2023, doi:10.1101/gr.277363.122
    ...individuals at the gene coexpression network level. Estimation of coexpression networks is well-established for bulk RNA-seq; however, single-cell measurements pose novel challenges due to technical limitations and noise levels of this technology. Gene-gene correlation estimates from scRNA-seq tend...
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  4. Method: Scalable cell-specific coexpression networks for granular regulatory pattern discovery with NeighbourNet
    • Yidi Deng,
    • Jiadong Mao,
    • Jarny Choi,
    • and Kim-Anh Le Cao
    Genome Res. March 5, 2026 gr.281171.125; Published in Advance March 5, 2026, doi:10.1101/gr.281171.125
    ...Gene networks provide a fundamental framework for understanding the molecular mechanisms 13 that govern gene expression. Advances in single-cell RNA sequencing (scRNA-seq) have enabled 14 network inference at cellular resolution; however, most existing approaches rely on predefined 15 clusters or cell...
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  5. Method: Systematic mapping of TF-mediated cell fate changes by a pooled induction coupled with scRNA-seq and multi-omics approaches
    • Muyoung Lee,
    • Qingqing Guo,
    • Mijeong Kim,
    • Joonhyuk Choi,
    • Alia Segura,
    • Alper Genceroglu,
    • Lucy LeBlanc,
    • Nereida Ramirez,
    • Yu Jin Jang,
    • Yeejin Jang,
    • Bum-Kyu Lee,
    • Edward M. Marcotte,
    • and Jonghwan Kim
    Genome Res. March 2024 34: 484-497; Published in Advance April 5, 2024, doi:10.1101/gr.277926.123
    ...clusters (Supplemental Table S3). The high efficiency of cell fate changes by inducing TFs was also observed in a few validation cases in the recent scRNA-seq-based single TF overexpression screen (>80% efficiency confirmed through testing reporter gene expression) (Ng et al. 2021). We found many...
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  6. Method: Benchmarking bulk and single-cell variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries
    • Matthew Wiens,
    • Hossein Farahani,
    • R. Wilder Scott,
    • T. Michael Underhill,
    • and Ali Bashashati
    Genome Res. August 2024 34: 1196-1210; Published in Advance August 15, 2024, doi:10.1101/gr.277066.122
    ..., this is not because of differences in expression levels, as the gene on which the edit is located (Htra1) is expressed in all involved clusters.Overall, this constitutes evidence that RNA-editing events may be seen in Chromium scRNA-seq libraries and used to infer heterogeneous presentation of RNA editing. Although...
  7. Resource: Cell type–specific gene regulatory atlas prioritizes drug targets and repurposable medicines in Alzheimer's disease
    • Yunxiao Ren,
    • Ming Hu,
    • Yang E. Li,
    • Andrew A. Pieper,
    • Jeffrey Cummings,
    • and Feixiong Cheng
    Genome Res. March 2026 36: 645-659; Published in Advance January 21, 2026, doi:10.1101/gr.280436.125
    ...–specific cis-regulatory DNA elements (CREs), we pinpoint 141 ADNC-associated genes. Using gene set enrichment analysis (GSEA) and network proximity analysis, we further identify nine candidate repurposable drugs that were associated with these ADNC-related genes. In summary, this cell type–specific multiomic...
    OPEN ACCESS ARTICLE
  8. Method: A scalable computational framework for predicting gene expression from candidate cis-regulatory elements
    • Qinhu Zhang,
    • Siguo Wang,
    • Zhipeng Li,
    • Wenzheng Bao,
    • Wenjian Liu,
    • and De-Shuang Huang
    Genome Res. February 2026 36: 361-374; Published in Advance January 16, 2026, doi:10.1101/gr.281219.125
    ...@eitech.edu.cnAbstractDeciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular biology, and the dynamics of CREs in different cell types make this problem more challenging. To address this challenge, we propose a scalable computational framework...
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  9. Method: Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks
    • Prashanthi Ravichandran,
    • Princy Parsana,
    • Rebecca Keener,
    • Kasper D. Hansen,
    • and Alexis Battle
    Genome Res. September 2025 35: 2087-2103; Published in Advance July 17, 2025, doi:10.1101/gr.280808.125
    ...-transformed along with gene-specific and sample-specific filters. Based on the data source, normalized gene expression was processed to merge replicates and exclude miRNA and scRNA-seq samples. (B) Number of samples which were annotated to be noncancerous and cancerous based on available metadata across GTEx, SRA...
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  10. Research: Oxygen-induced stress reveals context-specific gene regulatory effects in human brain organoids
    • Benjamin D. Umans and
    • Yoav Gilad
    Genome Res. August 2025 35: 1689-1700; Published in Advance June 2, 2025, doi:10.1101/gr.280219.124
    ...between genetic variants and environmental stressors is key to understanding the mechanisms underlying neurological diseases. In this study, we use human brain organoids to explore how varying oxygen levels expose context-dependent gene regulatory effects. By subjecting a genetically diverse panel of 21...
    OPEN ACCESS ARTICLE
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