Searching journal content for articles similar to Pamp et al. 22 (6): 1107.

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  1. 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
    ..., cell segmentation errors can lead to distortion of spatial-cell gene expression and confound cell identity (Fu et al. 2024). Even for spatial transcriptome and single-cell sequencing data from the same tissue source, the proportions of cell types are not the same (Choi et al. 2023; Garrido-Trigo et al...
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  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
    ...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...
  3. 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
    ...and target genes (Gao et al. 2023).Single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at the individual cell level, revealing cellular heterogeneity with single-cell resolution and significantly enhancing the understanding of cell type–specific gene regulation (Chen and Liu 2022; Kartha...
  4. 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
    ..., Illinois 60607, USA; 3Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA Corresponding author: zivbj@cs.cmu.eduAbstractRecent efforts to generate atlas-scale single-cell data provide opportunities for joint analysis across tissues...
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  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
    ...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...
  6. 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
    ...a systematic comparison between single-cell long-read and conventional short-read RNA sequencing techniques. The transcriptome of approximately 30,000 mouse retina cells was profiled using 1.54 billion Illumina short reads and 1.40 billion Oxford Nanopore Technologies long reads. Consequently, we identify 44...
  7. 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...
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  8. Method: Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics
    • Vishvak Raghavan,
    • Yumin Zheng,
    • Yue Li,
    • and Jun Ding
    Genome Res. July 2025 35: 1646-1663; Published in Advance May 2, 2025, doi:10.1101/gr.279771.124
    .... This makes them insensitive in complex environments where the detailed dynamics of cell interactions matter. We introduce CellAgentChat, an agent-based model (ABM) designed to decipher CCIs from single-cell RNA sequencing and spatial transcriptomics data. This approach models biological systems...
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  9. 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
    ....beerenwinkel@bsse.ethz.chAbstractIn cancer, genetic and transcriptomic variations generate clonal heterogeneity, leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging...
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  10. Method: Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes
    • Hongke Peng,
    • Jafar S. Jabbari,
    • Luyi Tian,
    • Changqing Wang,
    • Yupei You,
    • Chong Chyn Chua,
    • Natasha S. Anstee,
    • Noorul Amin,
    • Andrew H. Wei,
    • Nadia M. Davidson,
    • Andrew W. Roberts,
    • David C.S. Huang,
    • Matthew E. Ritchie,
    • and Rachel Thijssen
    Genome Res. April 2025 35: 942-955; Published in Advance January 10, 2025, doi:10.1101/gr.279322.124
    .... While single-cell DNA sequencing, such as Mission Bio Tapestri, provides insight into clonality upon drug resistance (Thompson et al. 2022), it lacks transcriptome profiling per cell. In contrast, scRaCH-seq offers short-read whole transcriptomic data and mutation status if the mRNA of the targeted gene...
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