Searching journal content for articles similar to Bao et al. 24 (11): 1765.

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  1. Method: Tree-based differential testing using inferential uncertainty for RNA-seq
    • Noor Pratap Singh,
    • Euphy Y. Wu,
    • Jason Fan,
    • Michael I. Love,
    • and Rob Patro
    Genome Res. October 2025 35: 2326-2338; Published in Advance August 21, 2025, doi:10.1101/gr.279981.124
    ...estimates of certain transcripts which, if ignored, can lead to the exaggeration of false positives and, if included, may lead to reduced power. Here, we introduce a data-driven differential testing method that maximizes biological resolution while retaining statistical power. Given a set of RNA-seq samples...
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  2. Method: Evaluation of strategies for evidence-driven genome annotation using long-read RNA-seq
    • Alejandro Paniagua,
    • Cristina Agustín-García,
    • Francisco J. Pardo-Palacios,
    • Thomas Brown,
    • Maite De Maria,
    • Nancy D. Denslow,
    • Camila J. Mazzoni,
    • and Ana Conesa
    Genome Res. April 2025 35: 1053-1064; Published in Advance December 23, 2024, doi:10.1101/gr.279864.124
    ...(Scalzitti et al. 2020). Recently, long-read RNA sequencing (lrRNA-seq) has started to be used for this purpose (Peng et al. 2022; Zhang et al. 2022). lrRNA-seq has the potential to capture full-length transcripts and reveal the complexity of the transcriptomes. However, lrRNA-seq data also contain...
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  3. Method: Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution
    • Qian Qin,
    • Victoria Popic,
    • Kirsty Wienand,
    • Houlin Yu,
    • Emily White,
    • Akanksha Khorgade,
    • Asa Shin,
    • Christophe Georgescu,
    • Catarina D. Campbell,
    • Arthur Dondi,
    • Niko Beerenwinkel,
    • Francisca Vazquez,
    • Aziz M. Al'Khafaji,
    • and Brian J. Haas
    Genome Res. April 2025 35: 967-986; Published in Advance March 14, 2025, doi:10.1101/gr.279200.124
    ...in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics and prognostics and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate...
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  4. Method: Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks
    • Prashanthi Ravichandran,
    • Princy Parsana,
    • Rebecca Keener,
    • Kasper D. Hansen,
    • and Alexis Battle
    Genome Res. September 2025 35: 2087-2103; Published in Advance July 17, 2025, doi:10.1101/gr.280808.125
    ...and AI Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: ajbattle@jhu.eduAbstractGene coexpression networks (GCNs) describe relationships among genes that maintain cellular identity and homeostasis. However, typical RNA-seq experiments often lack sufficient sample...
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  5. Resource: Multitissue single-nucleus RNA-seq reveals cell type–specific regulatory patterns of alternative polyadenylation in pigs
    • Qiuhan Wen,
    • Zhen Wang,
    • Qi Bao,
    • Tianli Ding,
    • Haihan Zhang,
    • Jianbo Li,
    • Zhuang Liu,
    • Jieping Huang,
    • and Guoqiang Yi
    Genome Res. September 2025 35: 2116-2129; Published in Advance June 16, 2025, doi:10.1101/gr.280095.124
    ...introduces constraints due to potential incompleteness in the data set. Third, the use of snRNA-seq data primarily captures nuclear transcripts whereas most mature RNAs are processed in the cytoplasm, which might not fully reflect the final state of RNA processing. Fourth, cell number disparities across...
  6. Method: TransMeta simultaneously assembles multisample RNA-seq reads
    • Ting Yu,
    • Xiaoyu Zhao,
    • and Guojun Li
    Genome Res. July 2022 32: 1398-1407; Published in Advance July 20, 2022, doi:10.1101/gr.276434.121
    ...252000, China ↵4 These authors contributed equally to this work. Corresponding author: guojunsdu@gmail.comAbstractAssembling RNA-seq reads into full-length transcripts is crucial in transcriptomic studies and poses computational challenges. Here we present TransMeta, a simple and robust algorithm...
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  7. RECOMB 2022 Special/Methods: Unsupervised cell functional annotation for single-cell RNA-seq
    • Dongshunyi Li,
    • Jun Ding,
    • and Ziv Bar-Joseph
    Genome Res. September 2022 32: 1765-1775; Published in Advance June 28, 2022, doi:10.1101/gr.276609.122
    ...; 3Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA Corresponding author: zivbj@cs.cmu.eduAbstractOne of the first steps in the analysis of single-cell RNA sequencing (scRNA-seq) data is the assignment of cell types. Although...
  8. Method: RNA-seq as a tool for evaluating human embryo competence
    • Abigail F. Groff,
    • Nina Resetkova,
    • Francesca DiDomenico,
    • Denny Sakkas,
    • Alan Penzias,
    • John L. Rinn,
    • and Kevin Eggan
    Genome Res. October 2019 29: 1705-1718; Published in Advance September 23, 2019, doi:10.1101/gr.252981.119
    ...the discrepancies among current selection criteria. Recent advances enabling the production of RNA-seq libraries from single cells have facilitated the application of this technique to the study of transcriptional events in early human development. However, these studies have not assessed the quality...
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  9. Method: Mapping and quantifying nascent transcript start sites using TT-TSS-seq
    • Eleanor Elgood Hunt,
    • Claudia Vivori,
    • Richard Mitter,
    • Vedis Agnadottir,
    • and Folkert J. van Werven
    Genome Res. March 2026 36: 600-610; Published in Advance February 17, 2026, doi:10.1101/gr.280726.125
    ...). Short-capped RNA sequencing (scaRNA-seq) selectively captures short, capped transcripts to identify sites of transcription initiation (Larke et al. 2021). Limitations of some of these approaches include the need for complex biochemical purifications or fractionations and the risk of contamination...
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  10. Method: Accurate integration of multiple heterogeneous single-cell RNA-seq data sets by learning contrastive biological variation
    • Yang Zhou,
    • Qiongyu Sheng,
    • Jing Qi,
    • Jiao Hua,
    • Bo Yang,
    • Lei Wan,
    • and Shuilin Jin
    Genome Res. May 2023 33: 750-762; Published in Advance June 12, 2023, doi:10.1101/gr.277522.122
    ..., an integrative study of multiple heterogeneous single-cell RNA sequencing (scRNA-seq) data sets is crucial. However, present approaches are unable to integrate diverse data sets from various biological conditions effectively because of the confounding effects of biological and technical differences. We introduce...
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