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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
...of one modality from another. However, existing methods for cross-modality translation between single-cell RNA sequencing (scRNA-seq) and single-cell DNA methylation (scDNAm) data face limitations, including unidirectionality, inadequate modeling of context-specific DNA methylation...
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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
...GFN (Atanackovic et al. 2023) incorporates a Bayesian dynamic structure to model the posterior distribution over cyclic GRNs from single-cell data, effectively capturing complex structural uncertainties in single-cell data. Additionally, the integration of prior biological knowledge has substantially improved GRN...
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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
...(negative pairs). ContrastiveVI is a contrastive deep generative model that adapts this principle to single-cell data by separating condition-specific variation from shared biological variation through two distinct sets of latent features: one shared across all cells and another specific to the condition...
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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...
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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
...-adipogenic progenitor cells, involving a total of 328 transcription factors acting at chromatin sites regulating 2025 genes. This web-accessible single-cell data set and regulatory circuitry map serve as a resource for understanding the molecular underpinnings of the metabolic and physiological effects of exercise...
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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...
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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
...reprogramming TF identification, current methods often fail to put the real effective reprogramming TFs at the top. To address these challenges, we developed TFcomb, a computational method that leverages single-cell multiomics data to identify reprogramming TFs and TF combinations. We modeled the task...
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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
...methods that can also generate gene embeddings from single-cell data. These include GLUE (Cao and Gao 2022), DeepMAPS (Ma et al. 2023), SIMBA (Chen et al. 2024), and GSDensity (Liang et al. 2023). For example, GSDensity can associate genes with cells based on their distances within the same embedding...
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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
...expression and 10x Genomics multiome combines transcriptome with chromatin accessibility data (Stoeckius et al. 2017). Our single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) method enables the capture of multiple transcripts from preindexed and stored cDNA independent of the 10x Genomics kit...
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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
.... Corresponding authors: chen_jiekai@gibh.ac.cn, lin_lihui@gibh.ac.cnAbstractIntegration of single-cell and spatial transcriptomes represents a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale data sets...
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