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Method: Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes
- Philipp Rentzsch,
- Aaron Kollotzek,
- Kaushik Ram Ganapathy,
- Pejman Mohammadi,
- and Tuuli Lappalainen
Genome Res. October 2025 35: 2316-2325; Published in Advance September 17, 2025, doi:10.1101/gr.280360.124
...a prioritization of functionally relevant driver genes. Tissue-specific recalibration increases detection of known disease-relevant processes. Altogether, our method provides a novel view on DE and contributes toward bridging the existing gap between statistical and biological significance. We believe...
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Method: Deep structural clustering reveals hidden systematic biases in RNA sequencing data
- Qiang Su,
- Yi Long,
- Deming Gou,
- Junmin Quan,
- Xiaoming Zhou,
- and Qizhou Lian
Genome Res. November 2025 35: 2563-2577; Published in Advance September 19, 2025, doi:10.1101/gr.280713.125
...biological functions (Le and Maizel 1997; Cheng et al. 2001). The VAE-GMM k-mer clustering model, by combining deep neural networks with probabilistic clustering and dimensionality reduction techniques, offers a promising framework for decoding high-dimensional RNA sequence structures and uncovering latent...
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Method: Inferring ancestry with the hierarchical soft clustering approach tangleGen
- Klara Elisabeth Burger,
- Solveig Klepper,
- Ulrike von Luxburg,
- and Franz Baumdicker
Genome Res. December 2024 34: 2244-2255; Published in Advance October 21, 2024, doi:10.1101/gr.279399.124
...interpretability by providing a hierarchical perspective on the composition and structure of populations, but also adds a new level of explainability to the clustering by disentangling the individual contributions of relevant SNPs. In addition, tangleGen is deterministic and identifies the number of related...
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Method: STCC enhances spatial domain detection through consensus clustering of spatial transcriptomics data
- Congcong Hu,
- Nana Wei,
- Jiyuan Yang,
- Hua-Jun Wu,
- and Xiaoqi Zheng
Genome Res. June 2025 35: 1415-1428; Published in Advance May 12, 2025, doi:10.1101/gr.280031.124
...algorithms, namely, hypergraph partitioning algorithm (HGPA), metaclustering algorithm (MCLA), and cluster-based similarity partitioning algorithm (CSPA). In detail, HGPA uses the weight of cutting hyperedges as the objective function to assess the partitioning quality of the hypergraph. MCLA first...
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Resource: Cell type–specific gene regulatory atlas prioritizes drug targets and repurposable medicines in Alzheimer's disease
- Yunxiao Ren,
- Ming Hu,
- Yang E. Li,
- Andrew A. Pieper,
- Jeffrey Cummings,
- and Feixiong Cheng
Genome Res. March 2026 36: 645-659; Published in Advance January 21, 2026, doi:10.1101/gr.280436.125
...investigated the functions of upregulated genes from the inter to high stage using Gene Ontology (GO) analysis (Fig. 3C). For each cell type, we identified the DEGs contributing to the enriched GO terms (Fig. 3D). Our results revealed that upregulated genes in excitatory and inhibitory neurons were...
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Method: Kernel-bounded clustering for spatial transcriptomics enables scalable discovery of complex spatial domains
- Hang Zhang,
- Yi Zhang,
- Kai Ming Ting,
- Jie Zhang,
- and Qiuran Zhao
Genome Res. February 2025 35: 355-367; Published in Advance February 5, 2025, doi:10.1101/gr.278983.124
...simultaneously (Marx 2021). They have greatly accelerated biological and biomedical researches (Asp et al. 2020), allowing for the characterization of transcriptional patterns and regulation in tissues, as well as the identification of tissue neighborhoods and local features that contribute to diseases...
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Resource: Single-nucleus multiomic profiling of the aging mouse substantia nigra reveals conserved gene alterations linked to Parkinson's disease
- Kangli Wang,
- Weikun Xia,
- Yingli Gu,
- Songpeng Zu,
- Qian Yang,
- Maria Luisa Amaral,
- Yaozhi Wang,
- Allen Wang,
- Xiang-Dong Fu,
- William C. Mobley,
- and Bing Ren
Genome Res. March 4, 2026 gr.281113.125; Published in Advance March 4, 2026, doi:10.1101/gr.281113.125
..., we performed clustering 187 analysis of DEGs, identifying distinct groups with varied functions. In oligodendrocytes, for 188 example, we identified four DEG groups: early-upregulated, late-upregulated, early-189 downregulated, and late-downregulated (Fig. 2F,G). Some genes, such as Cldn11, showed...
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Method: Accurate estimation of pathway activity in single cells for clustering and differential analysis
- Daniel Davis,
- Avishai Wizel,
- and Yotam Drier
Genome Res. June 2024 34: 925-936; Published in Advance July 9, 2024, doi:10.1101/gr.278431.123
...with findings reported in previous studies in many cases, but SiPSiC also reveals the differential activity of novel pathways, enabling us to suggest new mechanisms underlying the pathophysiology of these diseases and demonstrating SiPSiC's high accuracy and sensitivity in detecting biological function...
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Mini-Review: The paradox of R-loops: guardians of the genome or drivers of disease?
- Shachinthaka D. Dissanayaka Mudiyanselage,
- Phillip Wulfridge,
- and Kavitha Sarma
Genome Res. September 2025 35: 1919-1928; Published in Advance August 6, 2025, doi:10.1101/gr.278992.124
...helicases function together in cells and on how they are regulated will yield valuable information on how their mutations contribute to various diseases.The dual role of R-loops in DNA damage induction and repair mechanismsAlthough R-loops have been implicated in instability through their ability to cause...
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Method: A novel multislice framework for precision 3D spatial domain reconstruction and disease pathology analysis
- Daijun Zhang,
- Ren Qi,
- Xun Lan,
- and Bin Liu
Genome Res. August 2025 35: 1794-1808; Published in Advance July 14, 2025, doi:10.1101/gr.280281.124
...-precision gene expression analysis techniques across different brain regions can deepen our understanding of how genes regulate brain development and disease processes on structural and functional levels.To assess the impact of the microenvironmental deconstruction module on spatial domain identification...

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