Searching journal content for articles similar to Slaidina et al. 31 (10): 1938.

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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: 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
    ...constrained by critical challenges including experimental complexity, low detection sensitivity, limited sequencing throughput, significant data noise, and high costs (Yang et al. 2021; Zhang et al. 2022). Because of these technical constraints, most publicly available single-cell data sets remain unimodal...
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  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: 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
    ...given to deciphering the 3D chromatin structure at single-cell resolution, which reveals patterns related to the cell cycle and cell maturation (Nagano et al. 2017). In this work, we present ChromMovie: a comprehensive tool designed for studying 3D chromatin structures at the chromosome level throughout...
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  5. 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
    ...)-expressing fibro-adipogenic progenitor cells. Single-cell regulatory circuit triad reconstruction (transcription factor, chromatin interaction site, regulated gene) also identifies largely distinct gene regulatory circuits modulated by exercise in the three muscle fiber types and LUM-expressing fibro...
  6. 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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  7. 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
    ...atlas studies have become a trend in biological research. When integrating single-cell and spatial data, we require not only high accuracy but also high efficiency of computation. However, existing mapping algorithms cannot efficiently handle millions of cells. Polyomino first maps single cells...
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  8. Research: Single-cell analysis reveals transcriptional dynamics in healthy primary parathyroid tissue
    • Aarthi Venkat,
    • Maximillian J. Carlino,
    • Betty R. Lawton,
    • Manju L. Prasad,
    • Matthew Amodio,
    • Courtney E. Gibson,
    • Caroline J. Zeiss,
    • Scott E. Youlten,
    • Smita Krishnaswamy,
    • and Diane S. Krause
    Genome Res. June 2024 34: 837-850; Published in Advance July 8, 2024, doi:10.1101/gr.278215.123
    ...target genes as identified by the ENCODE data set ENCSR407MOM, including HERC4, RIF1, TEAD1, and STAT5B (Subramanian et al. 2005; Sloan et al. 2016; Kolmykov et al. 2021). Although derived from Drosophila cells, this ChIP-seq data set has 2444 candidate target genes with human or primate orthologs...
  9. Method: TFcomb identifies transcription factor combinations for cellular reprogramming based on single-cell multiomics data
    • Chen Li,
    • Sijie Chen,
    • Yixin Chen,
    • Haiyang Bian,
    • Minsheng Hao,
    • Lei Wei,
    • and Xuegong Zhang
    Genome Res. June 2025 35: 1429-1439; Published in Advance April 10, 2025, doi:10.1101/gr.279955.124
    ...identification for single-cell data sets. To address this, we adopted a single-cell atlas built by Joung et al. (2023) to construct the benchmark for reprogramming TF identification. This atlas profiled human embryonic stem cells (hESCs) infected with a lentivirus library to perform overexpression of a single...
  10. Resource: Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level
    • Wankun Deng,
    • Citu Citu,
    • Andi Liu,
    • and Zhongming Zhao
    Genome Res. October 2024 34: 1687-1699; Published in Advance October 18, 2024, doi:10.1101/gr.279363.124
    ...they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs...
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