Searching journal content for articles similar to Heiser et al. 31 (10): 1742.

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  1. 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
    ...-world GRN reconstruction from multi-omics single-cell data. The relatively poor performance of the unsupervised methods observed here, especially those based on multi-omics data, may be attributed to their sensitivity to input data quality and the lack of task-specific supervision; we further analyze...
  2. 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
    ...methods. Whereas these preprocessing steps are critical for ensuring and assessing data quality, they are well-established in the single-cell analysis community and have not been further discussed in this study. scPSS requires a mapping of cell type labels between the reference and query data sets...
  3. 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
    ...interactions. The IFNB single-cell RNA sequencing data set (Kang et al. 2018) is a multiplexed droplet-based transcriptomic analysis of peripheral blood mononuclear cells, in which cells were either stimulated with interferon beta or left untreated. The following sections present an experimental evaluation...
  4. Method: De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data
    • Arthur Dondi,
    • Nico Borgsmüller,
    • Pedro F. Ferreira,
    • Brian J. Haas,
    • Francis Jacob,
    • Viola Heinzelmann-Schwarz,
    • Tumor Profiler Consortium,
    • and Niko Beerenwinkel
    Genome Res. April 2025 35: 900-913; Published in Advance March 19, 2025, doi:10.1101/gr.279281.124
    ..., to examine these interlinked features jointly (Foord et al. 2023) by capturing genetic and transcriptomic variants at the single-cell level (Mansoori et al. 2017; Dagogo-Jack and Shaw 2018; Marine et al. 2020).Droplet-based scRNA-seq (e.g., 10x Genomics Chromium) can detect same-cell genetic...
    OPEN ACCESS ARTICLE
  5. Method: Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution
    • Qian Qin,
    • Victoria Popic,
    • Kirsty Wienand,
    • Houlin Yu,
    • Emily White,
    • Akanksha Khorgade,
    • Asa Shin,
    • Christophe Georgescu,
    • Catarina D. Campbell,
    • Arthur Dondi,
    • Niko Beerenwinkel,
    • Francisca Vazquez,
    • Aziz M. Al'Khafaji,
    • and Brian J. Haas
    Genome Res. April 2025 35: 967-986; Published in Advance March 14, 2025, doi:10.1101/gr.279200.124
    ...short-read sequences. Recent advances in long-read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single-cell samples. Here, we developed a new computational tool, CTAT-LR-Fusion, to detect fusion transcripts from long-read RNA-seq with or without...
    OPEN ACCESS ARTICLE
  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
    .... Corresponding authors: chen_jiekai@gibh.ac.cn, lin_lihui@gibh.ac.cnAbstractIntegration of single-cell and spatial transcriptomes represents a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale data sets...
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  7. 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
    ...assumption of these technologies.The rapid expansion of single-cell technologies has introduced various sequencing platforms that produce data with different qualities. For example, in contrast to transcript end sequencing technologies, full-length scRNA-seq covers the entire sequence of RNA molecules...
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  8. Method: Inferring disease progression stages in single-cell transcriptomics using a weakly supervised deep learning approach
    • Fabien Wehbe,
    • Levi Adams,
    • Jordan Babadoudou,
    • Samantha Yuen,
    • Yoon-Seong Kim,
    • and Yoshiaki Tanaka
    Genome Res. January 2025 35: 135-146; Published in Advance December 2, 2024, doi:10.1101/gr.278812.123
    ...problem (LeCun et al. 2015). Deep learning has been widely implemented in various single-cell data analyses, including data imputation (Arisdakessian et al. 2019), doublet identification (Bernstein et al. 2020), dimensionality reduction (Deng et al. 2019), batch effect corrections (Xu et al. 2022...
    OPEN ACCESS ARTICLE
  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
    ...Sindri Emmanúel Antonsson and Páll Melsted Faculty of Industrial Engineering, Mechanical Engineering, and Computer Science, University of Iceland, 102 Reykjavík, Iceland Corresponding author: pmelsted@hi.isAbstractAs the number of experiments that employ single-cell RNA sequencing (scRNA-seq) grows...
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  10. Research: Integrating short-read and long-read single-cell RNA sequencing for comprehensive transcriptome profiling in mouse retina
    • Meng Wang,
    • Yumei Li,
    • Jun Wang,
    • Soo Hwan Oh,
    • Yexuan Cao,
    • and Rui Chen
    Genome Res. April 2025 35: 740-754; Published in Advance March 6, 2025, doi:10.1101/gr.279167.124
    ...of ISM detected in bulk data suggested that significant ISMs were likely artifacts. However, the substantial amount of NIC confirmed by bulk (3317 out of 15,894) indicated that the identification of much of the NIC was accurate. Additionally, 10 out of 38 NNCs in the single-cell data set were validated...
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