Searching journal content for articles similar to Feng et al. 34 (6): 822.

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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 .False discovery rate control using Storey's q-valuesWe identify significant pathological shifts at the single-cell level by performing separate hypothesis testing for each cell. To control for false discoveries from multiple hypothesis testing, we apply the q-value method developed by Storey...
  2. 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
    ...signatures from rare sources of variability. To facilitate the discovery of genes associated with all sources of transcriptomic variability, we introduce geneCover, a label-free correlation-based marker gene selection method designed for single-cell RNA sequencing and spatial transcriptomics data. gene...
  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: Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications
    • Dayea Park and
    • Can Cenik
    Genome Res. April 2025 35: 999-1011; Published in Advance October 29, 2024, doi:10.1101/gr.279270.124
    ...). This method enabled us to pinpoint mRNA positions showing significant ASM (Fig. 3A). Among detected 14,609 and 13,542 candidate m6A sites in the replicate experiments, we identified 57 ASM sites (false discovery rate [FDR] < 0.1) with an average modification difference between the two alleles of 0.32.View...
  5. 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...
  6. 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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  7. Review: Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics
    • Natan Belchikov,
    • Justine Hsu,
    • Xiang Jennie Li,
    • Julien Jarroux,
    • Wen Hu,
    • Anoushka Joglekar,
    • and Hagen U. Tilgner
    Genome Res. November 2024 34: 1735-1746; doi:10.1101/gr.279640.124
    ...of adenosine (m6A) being the most common.View larger version: In this window In a new window Figure 1. Multiple RNA variables contribute to the production of distinct isoforms from the same gene. In alternative exon inclusion, an exon can be either included or spliced out of a transcript. In alternative TSS...
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  8. 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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  9. 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
    ...of intermediate fibers that typically transition to a pure fast or slow fiber with exercise training (Klitgaard et al. 1990; Williamson et al. 2001; Harber and Trappe 2008). ATAC-seq data are distributed differently than RNA-seq data, and loci are more abundant, making DARs more sensitive to false-discovery rate...
  10. Method: A versatile type VI CRISPR-based approach for targeted m6A demethylation in mRNAs
    • Panagiotis G. Adamopoulos,
    • Konstantina Athanasopoulou,
    • and Andreas Scorilas
    Genome Res. January 2026 36: 169-182; Published in Advance December 11, 2025, doi:10.1101/gr.280476.125
    ...: padamopoulos@biol.uoa.grAbstractEpitranscriptomics, a rapidly evolving field mainly driven by massive parallel sequencing technologies, explores post-transcriptional RNA modifications. N6-methyladenosine (m6A) has emerged as the most prominent and dynamically regulated modification in human mRNAs, being...
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