Searching journal content for articles similar to Qin et al. 34 (3): 514.

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  1. Method: A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data
    • Fei Qin,
    • Guoshuai Cai,
    • Christopher I. Amos,
    • and Feifei Xiao
    Genome Res. January 2024 34: 85-93; Published in Advance January 30, 2024, doi:10.1101/gr.278098.123
    ...identification within a large, complex cell population. In this study, we developed a subclone clustering method based on a fused lasso model, referred to as FLCNA, which can simultaneously detect CNAs in single-cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering...
  2. 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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  3. 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...
  4. Research: Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotypes and phenotypes in chronic lymphocytic leukemia
    • Gage S. Black,
    • Xiaomeng Huang,
    • Yi Qiao,
    • Philip Moos,
    • Deepa Sampath,
    • Deborah M. Stephens,
    • Jennifer A. Woyach,
    • and Gabor T. Marth
    Genome Res. April 2025 35: 686-697; Published in Advance February 18, 2025, doi:10.1101/gr.279049.124
    ...of single-cell genotypes to identify subclone structures. (A) The subclone structure of patient 1 was identified in the bulk DNA sequencing data. Subclones are depicted by the colored circles, with representative variant clusters inside each circle. The fishplot shows the prevalence of each subclone...
  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: 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...
  7. 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
    ...Laboratory, Guangdong 510005, China Corresponding author: r.thijssen@amsterdamumc.nlAbstractSingle-cell long-read sequencing has transformed our understanding of isoform usage and the mutation heterogeneity between cells. Despite unbiased in-depth analysis, the low sequencing throughput often results...
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  8. 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...
  9. 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
    .... Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies have empowered the comprehensive characterization of gene programs at both single-cell and spatial resolutions. Here, we present DeCEP, a computational framework designed to characterize context...
  10. 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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