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Method: Unified integration of spatial transcriptomics across platforms with LLOKI
- Ellie Haber,
- Ajinkya Deshpande,
- Jian Ma,
- and Spencer Krieger
Genome Res. December 2025 35: 2722-2733; Published in Advance November 13, 2025, doi:10.1101/gr.280803.125
...types across these technologies (Fig. 5B), yielding a biological conservation score of 0.47 and a batch correction score of 0.23 when evaluated on nonmalignant cells. Malignant cells remained largely distinct between data sets, reflecting tumor-specific transcriptional differences from diverse origins...
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Method: Joint imputation and deconvolution of gene expression across spatial transcriptomics platforms
- Hongyu Zheng,
- Hirak Sarkar,
- and Benjamin J. Raphael
Genome Res. December 2025 35: 2734-2743; Published in Advance November 17, 2025, doi:10.1101/gr.280555.125
...) to model SRT data, taking into account the spatial information. However, these methods are only applicable to a single data set and therefore are not suitable for imputation across multiple SRT modalities.All of the above mentioned tools used for imputation implicitly assume at least one of the modalities...
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Research: Autism spectrum disorder risk genes have convergent effects on transcription and neuronal firing patterns in primary neurons
- Alekh Paranjapye,
- Rili Ahmad,
- Steven Su,
- Abraham J. Waldman,
- Jennifer E. Phillips-Cremins,
- Shuo Zhang,
- and Erica Korb
Genome Res. November 2025 35: 2433-2444; Published in Advance October 20, 2025, doi:10.1101/gr.280698.125
...@pennmedicine.upenn.eduAbstractAutism spectrum disorder (ASD) is a highly heterogenous neurodevelopmental disorder with numerous genetic risk factors. Notably, a disproportionate number of risk genes encode transcription regulators including transcription factors and proteins that regulate chromatin. Here, we test the function of nine such ASD...
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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
...), and first and third quartiles (bounds of boxes). (D) Line plots of TIS comparison across 18 target states.We compared TFcomb with several baseline methods. Because of the high data requirements, such as the need for time-series data (Ronquist et al. 2017), we did not include dynamic model–based methods. GRN...
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Research: Aberrant homeodomain–DNA cooperative dimerization underlies distinct developmental defects in two dominant CRX retinopathy models
- Yiqiao Zheng,
- Gary D. Stormo,
- and Shiming Chen
Genome Res. February 2025 35: 242-256; Published in Advance December 23, 2024, doi:10.1101/gr.279340.124
...functional domains: the N-terminal DNA-binding domain (HD) and the C-terminal transcription effector domain. Disease-associated mutations are distributed across both domains, with amino acid substitutions primarily observed in the CRX HD (Tran and Chen 2014; Zheng and Chen 2024). To understand how HD...
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Method: Long-read Ribo-STAMP simultaneously measures transcription and translation with isoform resolution
- Pratibha Jagannatha,
- Alexandra T. Tankka,
- Daniel A. Lorenz,
- Tao Yu,
- Brian A. Yee,
- Kristopher W. Brannan,
- Cathy J. Zhou,
- Jason G. Underwood,
- and Gene W. Yeo
Genome Res. November 2024 34: 2012-2024; Published in Advance June 21, 2024, doi:10.1101/gr.279176.124
...to isoforms (Methods), identification and filtering of edited sites, and calculation of the ratio of edited to total cytosines across a gene's or isoform's exons (EditsC) (Fig. 1B). We developed the EditsC metric to capitalize on the single-molecule, full-length transcript information provided by long...
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Method: Single-nucleus CUT&RUN elucidates the function of intrinsic and genomics-driven epigenetic heterogeneity in head and neck cancer progression
- Howard J. Womersley,
- Daniel Muliaditan,
- Ramanuj DasGupta,
- and Lih Feng Cheow
Genome Res. January 2025 35: 162-177; Published in Advance December 2, 2024, doi:10.1101/gr.279105.124
.... Epigenomic changes during HNSCC progression suggest distinct, patient-specific epigenetic drivers of tumor evolution. (A) UMAP embedding for H3K4me3 (left) and H3K27ac (right) for HN120 and HN137 single-cells. (B) Enriched transcription factor (TF) motifs for HN137Pri derived from H3K27ac peaks. (C) Coverage...
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Method: Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data
- Kaixuan Luo,
- Jianling Zhong,
- Alexias Safi,
- Linda K. Hong,
- Alok K. Tewari,
- Lingyun Song,
- Timothy E. Reddy,
- Li Ma,
- Gregory E. Crawford,
- and Alexander J. Hartemink
Genome Res. June 2022 32: 1183-1198; Published in Advance May 24, 2022, doi:10.1101/gr.272203.120
...in a specific cell type using Duke DNase-seq data, with dots representing the candidate binding sites across the . Model performance differs among TFs, as seen in the two examples. (B) Separately for ATAC-seq and DNase-seq data from Duke and UW protocols, violin plots show distribution of Pearson's correlations...
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Method: Characterizing tandem repeat complexities across long-read sequencing platforms with TREAT and otter
- Niccoló Tesi,
- Alex Salazar,
- Yaran Zhang,
- Sven van der Lee,
- Marc Hulsman,
- Lydian Knoop,
- Sanduni Wijesekera,
- Jana Krizova,
- Anne-Fleur Schneider,
- Maartje Pennings,
- Kristel Sleegers,
- Erik-Jan Kamsteeg,
- Marcel Reinders,
- and Henne Holstege
Genome Res. November 2024 34: 1942-1953; Published in Advance October 15, 2024, doi:10.1101/gr.279351.124
...with at least 90% read quality) to improve throughput and accuracy via DeepConsensus (Baid et al. 2023), we performed this analysis only for Sequel II data. We found that non-HiFi data improved accuracy across all TR lengths. Specifically, when integrating non-HiFi reads of at least 85%–90% read quality...
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Research: Enhanced detection of RNA modifications and read mapping with high-accuracy nanopore RNA basecalling models
- Gregor Diensthuber,
- Leszek P. Pryszcz,
- Laia Llovera,
- Morghan C. Lucas,
- Anna Delgado-Tejedor,
- Sonia Cruciani,
- Jean-Yves Roignant,
- Oguzhan Begik,
- and Eva Maria Novoa
Genome Res. November 2024 34: 1865-1877; Published in Advance September 13, 2024, doi:10.1101/gr.278849.123
...models, available through the Guppy basecalling software, are not specifically trained to predict RNA modifications. Therefore, when the model encounters a modified RNA nucleotide, it may call the wrong base (mismatch error), not call any base (deletion error), or insert a small piece of sequence...

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