Searching journal content for articles similar to Trapnell 25 (10): 1491.

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  1. Method: Quantifying pathological progression from single-cell transcriptomic data with scPSS
    • Samin Rahman Khan,
    • M Saifur Rahman,
    • M. Sohel Rahman,
    • and Md Abul Hassan Samee
    Genome Res. February 2026 36: 375-386; Published in Advance January 14, 2026, doi:10.1101/gr.280411.125
    ...and reference atlases has enabled the comparison of cell states across conditions, yet a gap persists in quantifying pathological shifts from healthy cell states. To address this gap, we introduce single-cell Pathological Shift Scoring (scPSS), which provides a statistical measure for how much a “query” cell...
  2. Method: Simultaneous modeling of chromatin conformation changes from multiple single-cell interaction maps with ChromMovie
    • Krzysztof H. Banecki,
    • Haoxi Chai,
    • Yijun Ruan,
    • and Dariusz Plewczynski
    Genome Res. April 8, 2026 ; Published in Advance April 8, 2026, doi:10.1101/gr.280985.125
    ...within cellular genomics, we find significant advances in single-cell analysis. For instance, single-cell RNA sequencing (scRNA-seq) has revolutionized transcriptomics by offering advantages over traditional bulk analysis (Stegle et al. 2015; Bacher and Kendziorski 2016). Single-cell transcriptomics has...
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  3. Method: High-fidelity bidirectional translation between single-cell transcriptomes and DNA methylomes with scBOND
    • Kehan Lang,
    • Chenyang Jia,
    • Siyu Li,
    • Yi Guo,
    • Dingjun Hu,
    • and Shengquan Chen
    Genome Res. April 2026 36: 769-784; Published in Advance March 26, 2026, doi:10.1101/gr.281350.125
    ...technologies, single-cell RNA sequencing (scRNA-seq) has emerged as a fundamental technique for characterizing the functional state of individual cells. Complementary to scRNA-seq, single-cell DNA methylation (scDNAm) sequencing provides -wide maps of epigenetic modifications at single-cell resolution...
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  4. 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
    .... Its flexibility in integrating unpaired data without compromising performance makes it particularly valuable in scenarios in which paired data sets are difficult to obtain, enabling broader applications in genomics and single-cell research.PRISM-GRN achieves robust performance with limited prior...
  5. Method: Label-free selection of marker genes in single-cell and spatial transcriptomics with geneCover
    • An Wang,
    • Stephanie Hicks,
    • Donald Geman,
    • and Laurent Younes
    Genome Res. December 2025 35: 2744-2755; Published in Advance November 12, 2025, doi:10.1101/gr.280539.125
    ...for Imaging Science, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: awang87@jhu.eduAbstractThe selection of marker gene panels is critical for capturing the cellular and spatial heterogeneity in the expanding atlases of single-cell RNA sequencing (scRNA-seq) and spatial...
  6. Method: Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method
    • Quanyou Cai,
    • Lihui Lin,
    • Xin Liu,
    • and Jiekai Chen
    Genome Res. November 2025 35: 2513-2526; Published in Advance October 22, 2025, doi:10.1101/gr.280532.125
    ...and the state-of-the-art (SOTA) algorithms by integrating the simulated spatial cells and the corresponding single cells. Because the spatial position of each cell was known, we evaluated integration accuracy by computing the average Euclidean distance between the mapped and true spatial coordinates...
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  7. Method: Deciphering context-specific gene programs from single-cell and spatial transcriptomics data with DeCEP
    • Lin Li,
    • Xianbin Su,
    • and Ze-Guang Han
    Genome Res. October 2025 35: 2300-2315; Published in Advance August 21, 2025, doi:10.1101/gr.279689.124
    ...cellular contexts in single-cell RNA sequencing (scRNA-seq) data. Based on the topology of these functional networks, DeCEP identifies context-dependent hub genes, calculates DeCEP scores, and determines the states of individual cells. (B) DeCEP anchors cell states to spatial locations in spatial...
  8. 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
    ...developmental pathway differences in tissue development. Other potential usages are comparisons between healthy and disease tissues, using the GIANT embeddings generated for different cell types and cellular states, and multimodal comparisons between large-scale single-cell data sets across different species...
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  9. Method: Batch correction methods used in single-cell RNA sequencing analyses are often poorly calibrated
    • Sindri Emmanúel Antonsson and
    • Páll Melsted
    Genome Res. August 2025 35: 1832-1841; Published in Advance July 7, 2025, doi:10.1101/gr.279886.124
    ..., Miller HW, McElrath MJ, Prlic M, et al. 2015. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol 16: 278. doi:10.1186/s13059-015-0844-5 ↵Haber AL, Biton M, Rogel N, Herbst RH, Shekhar K, Smillie C...
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  10. Resource: Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise
    • Aliza B. Rubenstein,
    • Gregory R. Smith,
    • Zidong Zhang,
    • Xi Chen,
    • Toby L. Chambers,
    • Frederique Ruf-Zamojski,
    • Natalia Mendelev,
    • Wan Sze Cheng,
    • Michel Zamojski,
    • Mary Anne S. Amper,
    • Venugopalan D. Nair,
    • Andrew R. Marderstein,
    • Stephen B. Montgomery,
    • Olga G. Troyanskaya,
    • Elena Zaslavsky,
    • Todd Trappe,
    • Scott Trappe,
    • and Stuart C. Sealfon
    Genome Res. July 2025 35: 1664-1677; Published in Advance May 20, 2025, doi:10.1101/gr.280051.124
    ...following the chromium single-cell multiome ATAC and gene expression reagent kits V1 user guide (10x Genomics). Nuclei were counted (Cellometer K2 counter); transposition was performed in 10 µL for 60 min at 37°C targeting up to 10,000 nuclei, before loading of the Chromium chip J (PN-2000264) for GEM...
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