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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: 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: 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
.... 2021). Even though high-resolution spatial transcriptome technologies have been developed, such technologies show significantly lower cell segmentation resolution and the number of detected genes compared with single-cell transcriptome data. Therefore, integrating single-cell and spatial transcriptomic...
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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
...)-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...
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Method: A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data
- Cameron Park,
- Shouvik Mani,
- Nicolas Beltran-Velez,
- Katie Maurer,
- Teddy Huang,
- Shuqiang Li,
- Satyen Gohil,
- Kenneth J. Livak,
- David A. Knowles,
- Catherine J. Wu,
- and Elham Azizi
Genome Res. September 2024 34: 1384-1396; Published in Advance September 5, 2024, doi:10.1101/gr.279126.124
...on databases compiled from limited contexts. We introduce DIISCO, a Bayesian framework designed to characterize the temporal dynamics of cellular interactions using single-cell RNA-sequencing data from multiple time points. Our method utilizes structured Gaussian process regression to unveil time...
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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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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
...are assigned to genomic subclones based on the presence or absence of subclone-defining mutations. By combining subclone identity with single-cell gene expression information, this approach enables a subclone-specific gene expression analysis.Until recently, scRNA-seq has been carried out almost exclusively...
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Method: A Bayesian framework to study tumor subclone–specific expression by combining bulk DNA and single-cell RNA sequencing data
- Yi Qiao,
- Xiaomeng Huang,
- Philip J. Moos,
- Jonathan M. Ahmann,
- Anthony D. Pomicter,
- Michael W. Deininger,
- John C. Byrd,
- Jennifer A. Woyach,
- Deborah M. Stephens,
- and Gabor T. Marth
Genome Res. January 2024 34: 94-105; Published in Advance January 9, 2024, doi:10.1101/gr.278234.123
...A Bayesian framework to study tumor subclone–specific expression by combining bulk DNA and single-cell RNA sequencing data Yi Qiao1,6, Xiaomeng Huang1,6, Philip J. Moos2, Jonathan M. Ahmann3, Anthony D. Pomicter3, Michael W. Deininger3,4, John C. Byrd5, Jennifer A. Woyach5, Deborah M. Stephens3...
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Method: BayesRVAT enhances rare-variant association testing through Bayesian aggregation of functional annotations
- Antonio Nappi,
- Liubov Shilova,
- Theofanis Karaletsos,
- Na Cai,
- and Francesco Paolo Casale
Genome Res. December 2025 35: 2682-2690; Published in Advance October 24, 2025, doi:10.1101/gr.280689.125
...between the gene burden score and the phenotype is assessed by testing whether β ≠ 0.Bayesian formulationIn BayesRVAT, we parameterize the aggregation function gφ(X, A) with parameters ϕ and introduce a prior distribution p(ϕ) that incorporates our prior beliefs on how to aggregate variants into a burden...
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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
...cluster. (E) A subset from the original data set representing primate PT cells (cluster 1) was re-embedded with PHATE and colored by sample origin. (F) PHATE embeddings colored by expression level of PT-relevant genes in PHATE plots.Single-cell cDNA libraries were generated for each sample using the 10x...

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