Searching journal content for articles similar to Kimmel et al. 30 (1): 153_1.

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Method: A gene regulatory network–aware graph learning method for cell identity annotation in single-cell RNA-seq data
- Mengyuan Zhao,
- Jiawei Li,
- Xiaoyi Liu,
- Ke Ma,
- Jijun Tang,
- and Fei Guo
Genome Res. July 2024 34: 1036-1051; Published in Advance August 12, 2024, doi:10.1101/gr.278439.123
...not only effectively identify cell types with expression characteristics but also distinguish similar cell types.scHGR identifies novel subtypes based on scRNA-seq of PBMCscHGR not only automatically assigns cell identities but also reveals novel subpopulations by taking abundantly annotated atlases...
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Method: Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks
- Prashanthi Ravichandran,
- Princy Parsana,
- Rebecca Keener,
- Kasper D. Hansen,
- and Alexis Battle
Genome Res. September 2025 35: 2087-2103; Published in Advance July 17, 2025, doi:10.1101/gr.280808.125
...and AI Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: ajbattle@jhu.eduAbstractGene coexpression networks (GCNs) describe relationships among genes that maintain cellular identity and homeostasis. However, typical RNA-seq experiments often lack sufficient sample...
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Resource: Murine single-cell RNA-seq reveals cell-identity- and tissue-specific trajectories of aging
- Jacob C. Kimmel,
- Lolita Penland,
- Nimrod D. Rubinstein,
- David G. Hendrickson,
- David R. Kelley,
- and Adam Z. Rosenthal
Genome Res. December 2019 29: 2088-2103; Published in Advance November 21, 2019, doi:10.1101/gr.253880.119
...of the organismal building blocks—individual cells. Here, we used single-cell RNA-seq to investigate aging across a diverse set of murine cell identities in three tissues.We found that cell identities differentially express unique genes with aging, consistent with previous reports of cell-identity-specific aging...
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Method: A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures
- Shulin Mao,
- Jiayu Su,
- Longteng Wang,
- Xiaochen Bo,
- Cheng Li,
- and Hebing Chen
Genome Res. August 2023 33: 1381-1394; Published in Advance July 31, 2023, doi:10.1101/gr.277491.122
...the features learned from single-cell omics data can capture other dimensions of biological aging.Here, we developed single-cell aging-level estimator (SCALE), a tissue-specific measure that quantifies aging in individual cells using single-cell RNA-sequencing (scRNA-seq) data (Fig. 1). Unlike other clocks...
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Resource: Multitissue single-nucleus RNA-seq reveals cell type–specific regulatory patterns of alternative polyadenylation in pigs
- Qiuhan Wen,
- Zhen Wang,
- Qi Bao,
- Tianli Ding,
- Haihan Zhang,
- Jianbo Li,
- Zhuang Liu,
- Jieping Huang,
- and Guoqiang Yi
Genome Res. September 2025 35: 2116-2129; Published in Advance June 16, 2025, doi:10.1101/gr.280095.124
...polyadenylation (APA) plays a crucial role in gene regulation and phenotypic diversity. Whereas extensive studies have explored the global APA landscape using bulk RNA-seq data, in-depth analyses of APA events at the single-cell level remain limited—particularly in farm animals. In this study, we construct...
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Method: Tree-based differential testing using inferential uncertainty for RNA-seq
- Noor Pratap Singh,
- Euphy Y. Wu,
- Jason Fan,
- Michael I. Love,
- and Rob Patro
Genome Res. October 2025 35: 2326-2338; Published in Advance August 21, 2025, doi:10.1101/gr.279981.124
...also be explored in the future.Finally, it would be intriguing to explore the development of a TreeTerminus- and mehenDi-like approach in the context of single-cell RNA-seq analysis, where there are quite distinct but related opportunities for data-driven aggregation to increase the power...
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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
...in muscle using same-cell RNA-seq/ATAC-seq multiome assays. High-quality data were obtained from 37,154 nuclei comprising 14 cell types in vastus lateralis samples collected before and 3.5 h after either 40 min cycling exercise at 70% VO2max or 40 min supine rest. Both shared and cell...
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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
...of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh; 4Department of Integrative Physiology, Baylor College of Medicine, Houston, Texas 77030, USA Corresponding authors: msrahman@cse.buet.ac.bd, samee@bcm.eduAbstractThe surge in single-cell data sets...
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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
...is robust against spatial data noiseTo validate the noise tolerance of Polyomino, we simulated ground-truth ST data by substituting each spatial cell of seqFISH+ data by the single cell from snRNA-seq data of the same tissue (Fig. 2E; Tasic et al. 2018). Stringent comparison was performed between Polyomino...
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Research: Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments
- John T. Chamberlin,
- Younghee Lee,
- Gabor T. Marth,
- and Aaron R. Quinlan
Genome Res. February 2024 34: 179-188; Published in Advance February 14, 2024, doi:10.1101/gr.278253.123
...in pre-mRNA capture. Here, we reanalyze public data sets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and single-nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell...
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