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Method: Characterization of meiotic recombination intermediates through gene knockouts in founder hybrid mice
- Benjamin Davies,
- Gang Zhang,
- Daniela Moralli,
- Samy Alghadban,
- Daniel Biggs,
- Chris Preece,
- Peter Donnelly,
- and Anjali Gupta Hinch
Genome Res. November 2023 33: 2018-2027; Published in Advance November 17, 2023, doi:10.1101/gr.278024.123
...of generating a knockout allele. We redesigned the mutagenesis strategy and tested an alternative 3′ CRISPR-Cas9 sgRNA (sgRNA-F), which binds within exon 8 with an aim of increasing the likelihood of mutagenesis (Supplemental Fig. S1). This sgRNA showed a high rate of mutagenesis in vitro, as assessed by a high...
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Corrigendum: Corrigendum: Cre-dependent Cas9-expressing pigs enable efficient in vivo genome editing
- Kepin Wang,
- Qin Jin,
- Degong Ruan,
- Yi Yang,
- Qishuai Liu,
- Han Wu,
- Zhiwei Zhou,
- Zhen Ouyang,
- Zhaoming Liu,
- Yu Zhao,
- Bentian Zhao,
- Quanjun Zhang,
- Jiangyun Peng,
- Chengdan Lai,
- Nana Fan,
- Yanhui Liang,
- Ting Lan,
- Nan Li,
- Xiaoshan Wang,
- Xinlu Wang,
- Yong Fan,
- Pieter A. Doevendans,
- Joost P.G. Sluijter,
- Pentao Liu,
- Xiaoping Li,
- and Liangxue Lai
Genome Res. June 2025 35: 1472-2; doi:10.1101/gr.280849.125
...Corrigendum: Cre-dependent Cas9-expressing pigs enable efficient in vivo editing Kepin Wang, Qin Jin, Degong Ruan, Yi Yang, Qishuai Liu, Han Wu, Zhiwei Zhou, Zhen Ouyang, Zhaoming Liu, Yu Zhao, Bentian Zhao, Quanjun Zhang, Jiangyun Peng, Chengdan Lai, Nana Fan, Yanhui Liang, Ting Lan, Nan Li...
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Method: Statistically rigorous and computationally efficient chromatin stripe detection with Quagga
- Fan Feng,
- Sean Moran,
- Anders S. Hansen,
- Xiaotian Zhang,
- and Jie Liu
Genome Res. January 2026 36: 159-168; Published in Advance November 12, 2025, doi:10.1101/gr.280132.124
...regulation, and cell differentiation. Nevertheless, StripeDiff does not provide a user-friendly package to directly call all stripes with common contact map files.Here we introduce Quagga, a statistically rigorous, algorithmically efficient, and interpretable tool to identify stripes. Quagga's biggest...
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Method: Robust and efficient annotation of cell states through gene signature scoring
- Laure Ciernik,
- Agnieszka Kraft,
- Florian Barkmann,
- Josephine Yates,
- and Valentina Boeva
Genome Res. March 2026 36: 630-644; Published in Advance February 18, 2026, doi:10.1101/gr.280926.125
..., UCell, and JASMINE—across nine healthy and cancer scRNA-seq data sets demonstrates their insufficiency in fulfilling this requirement. To address this limitation, we present Adjusted Neighborhood Scoring (ANS), a deterministic algorithm with enhanced control gene selection that significantly improves...
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Research: Characterization of the role of spatial proximity of DNA double-strand breaks in the formation of CRISPR-Cas9-induced large structural variations
- Mikkel Dahl-Jessen,
- Thorkild Terkelsen,
- Rasmus O. Bak,
- and Uffe Birk Jensen
Genome Res. February 2025 35: 231-241; Published in Advance January 13, 2025, doi:10.1101/gr.278575.123
...be an unreliable indicator of sgRNA efficiency in H9 hESCs owing to the limited sensitivity of this analysis (Fig. 2D).Notably, the CRISPR-Cas9 targets in the proximity group had significantly lower Hi-C scores in hESCs compared to in K562 cells (P = 0.004) (Supplemental Fig. S13), possibly suggesting...
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Method: ScisTree2 enables large-scale inference of cell lineage trees and genotype calling using efficient local search
- Haotian Zhang,
- Yiming Zhang,
- Teng Gao,
- and Yufeng Wu
Genome Res. December 2025 35: 2781-2791; Published in Advance September 3, 2025, doi:10.1101/gr.280542.125
...is increasing rapidly. Accurate inference of cell lineage tree from large single-cell data is computationally challenging. In this paper, we present ScisTree2, a fast and accurate cell lineage tree inference and genotype calling approach based on the infinite-sites model. ScisTree2 relies on an efficient local...
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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
...or subtle spatial patterns, and they frequently fail to scale efficiently with large data sets. Here, we introduce geneCover, a label-free combinatorial method that selects an optimal panel of minimally redundant marker genes based on gene-gene correlations. Our method demonstrates excellent scalability...
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Method: Efficient integration of spatial omics data for joint domain detection, matching, and alignment with stMSA
- Han Shu,
- Jing Chen,
- Chang Xu,
- Jialu Hu,
- Yongtian Wang,
- Jiajie Peng,
- Qinghua Jiang,
- Xuequn Shang,
- and Tao Wang
Genome Res. October 2025 35: 2285-2299; Published in Advance August 14, 2025, doi:10.1101/gr.280584.125
...observed in the 10x Visium data set. This trend continued in the Stereo-seq data set, confirming successful integration across donors. Additionally, we evaluated computational efficiency. stMSA processed up to 20 slices with <12 GB of GPU memory, whereas Stitch3D, SPACEL, and SEDR struggled to handle...
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Method: Highly accurate reference and method selection for universal cross–data set cell type annotation with CAMUS
- Qunlun Shen,
- Shuqin Zhang,
- and Shihua Zhang
Genome Res. November 2025 35: 2527-2538; Published in Advance October 1, 2025, doi:10.1101/gr.280821.125
.... To this end, we present a cross–data set cell type annotation methodology with a universal reference data and method selection strategy (CAMUS) to achieve highly accurate and efficient annotations. We demonstrate the advantages of CAMUS by conducting comprehensive analyses on 672 pairs of cross-species sc...
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Research: Sequence determinants of improved CRISPR sgRNA design
- Han Xu,
- Tengfei Xiao,
- Chen-Hao Chen,
- Wei Li,
- Clifford A. Meyer,
- Qiu Wu,
- Di Wu,
- Le Cong,
- Feng Zhang,
- Jun S. Liu,
- Myles Brown,
- and X. Shirley Liu
Genome Res. August 2015 25: 1147-1157; Published in Advance June 10, 2015, doi:10.1101/gr.191452.115
...-based screens.View this table: In this window In a new window Table 1. A collection of CRISPR screening data sets used in the studyResultsSelection of the efficient and inefficient sgRNAs in CRISPR/Cas9 knockout screensTo construct a predictive model, we took two steps to identify efficient and inefficient sgRNAs...

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