蒲公英R:单细胞免疫库轨迹分析。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-06-30 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.06.047
Jiawei Yu, Xiaohan Xu, Nicholas Borcherding, Zewen Kelvin Tuong
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引用次数: 0

摘要

单细胞rna测序(scRNA-seq)和适应性免疫受体(AIR)测序(scVDJ-seq)的整合在研究淋巴细胞发育方面是非常强大的。基于python的软件包Dandelion引入了vdj特征空间方法,该方法解决了将单细胞AIR数据与基因表达数据集成的挑战,并增强了轨迹分析结果。然而,目前还没有基于r的等效或类似的方法。为了填补这一空白,我们提出了蒲公英R,这是蒲公英轨迹分析工作流程的一个R实现,将VDJ特征空间构建和使用扩散图和吸收马尔可夫链的轨迹分析引入R,为R用户提供了scRNA-seq和scVDJ-seq分析的新选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
dandelionR: Single-cell immune repertoire trajectory analysis in R.

Integration of single-cell RNA-sequencing (scRNA-seq) and adaptive immune receptor (AIR) sequencing (scVDJ-seq) is extremely powerful in studying lymphocyte development. A python-based package, Dandelion, introduced the VDJ-feature space method, which addresses the challenge of integrating single-cell AIR data with gene expression data and enhances trajectory analysis results. However, no R-based equivalent or similar methods currently exist. To fill this gap, we present dandelionR, an R implementation of Dandelion's trajectory analysis workflow, bringing the VDJ feature space construction and trajectory analysis using diffusion maps and absorbing Markov chains to R, offering a new option for scRNA-seq and scVDJ-seq analysis to R users.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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