Searching journal content for articles similar to Zhao et al. 34 (7): 1036.

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  1. Method: Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network
    • Xingyan Liu,
    • Qunlun Shen,
    • and Shihua Zhang
    Genome Res. January 2023 33: 96-111; Published in Advance December 16, 2022, doi:10.1101/gr.276868.122
    ...-type assignment is a crucial step to achieve that. However, the poorly annotated and limited known biomarkers hinder us from assigning cell identities for nonmodel species. Here, we design a heterogeneous graph neural network model, CAME, to learn aligned and interpretable cell and gene embeddings for cross...
  2. Method: A unified analysis of atlas single-cell data
    • Hao Chen,
    • Nam D. Nguyen,
    • Matthew Ruffalo,
    • and Ziv Bar-Joseph
    Genome Res. May 2025 35: 1219-1233; Published in Advance February 18, 2025, doi:10.1101/gr.279631.124
    ...intestine, spleen, and thymus, and three different data modalities, which include single-cell RNA-seq (scRNA-seq), single-cell ATAC-seq (scATAC-seq), and spatial transcriptomics (Slide-seq). Figure 1, A through C, presents an overview of GIANT. We first construct gene graphs for cell clusters from each...
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  3. Review: A systematic guide for identifying transcription factors that directly regulate the expression of a gene of interest
    • Andrew D. Bates,
    • Dawid Grzela,
    • Maciej Studzian,
    • Louise Brennan,
    • Moli Williams,
    • Conor Fawcett,
    • Beth Hammond,
    • Manreen Grewal,
    • Marcin Ratajewski,
    • Lukasz Pulaski,
    • and Urszula L. McClurg
    Genome Res. March 2026 36: 433-459; Published in Advance February 17, 2026, doi:10.1101/gr.281154.125
    ...), making it a versatile tool in single-cell genomics.Traditionally, steady-state mRNA levels have been assessed using qPCR or RNA-seq, but these approaches capture both primary and secondary responses and are influenced by RNA stability. To address this limitation, a variety of nascent RNA profiling...
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  4. Resource: The accessible chromatin landscape of the murine hippocampus at single-cell resolution
    • John R. Sinnamon,
    • Kristof A. Torkenczy,
    • Michael W. Linhoff,
    • Sarah A. Vitak,
    • Ryan M. Mulqueen,
    • Hannah A. Pliner,
    • Cole Trapnell,
    • Frank J. Steemers,
    • Gail Mandel,
    • and Andrew C. Adey
    Genome Res. May 2019 29: 857-869; Published in Advance April 1, 2019, doi:10.1101/gr.243725.118
    ...-SNE space is observed between the fresh or frozen starting material. (C) LSI-t-SNE projection of cells colored by assigned cluster and cell type. (D) Enrichment of accessibility of proximal regulatory elements for marker genes as identified by single-cell RNA-seq (Smart-seq protocol [S]) (Zeisel et al. 2015...
  5. Mini-Review: A Hitchhiker's Guide to long-read genomic analysis
    • Medhat Mahmoud,
    • Daniel P. Agustinho,
    • and Fritz J. Sedlazeck
    Genome Res. April 2025 35: 545-558; doi:10.1101/gr.279975.124
    ...associations. Tools such as ANNOVAR (Wang et al. 2010), SnpEff (Cingolani et al. 2012), and Ensembl Variant Effect Predictor (VEP; Hunt et al. 2022) are commonly used, enabling researchers to systematically annotate variants with known functional effects or potential impacts on genes and regulatory elements...
  6. Perspective: Challenges in identifying mRNA transcript starts and ends from long-read sequencing data
    • Ezequiel Calvo-Roitberg,
    • Rachel F. Daniels,
    • and Athma A. Pai
    Genome Res. November 2024 34: 1719-1734; doi:10.1101/gr.279559.124
    .... Such characterization is crucial for completely delineating full mRNA molecules and regulatory consequences. However, there are substantial inconsistencies in both start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal...
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  7. Method: Multicondition and multimodal temporal profile inference during mouse embryonic development
    • Ran Zhang,
    • Chengxiang Qiu,
    • Galina N. Filippova,
    • Gang Li,
    • Jay Shendure,
    • Jean-Philippe Vert,
    • Xinxian Deng,
    • William Stafford Noble,
    • and Christine M. Disteche
    Genome Res. October 2025 35: 2339-2351; Published in Advance August 14, 2025, doi:10.1101/gr.279997.124
    .... control) and data types (e.g., scRNA-seq, scATAC-seq), as well as limited sample availability. Consequently, a method capable of accurately imputing unobserved single-cell measurements—essentially answering questions such as, “what would the gene expression of this particular cell be if we had measured...
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