Benchmark of cellular deconvolution methods using a multi-assay dataset from postmortem human prefrontal cortex

IF 10.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Genome Biology Pub Date : 2025-04-07 DOI:10.1186/s13059-025-03552-3

Louise A. Huuki-Myers, Kelsey D. Montgomery, Sang Ho Kwon, Sophia Cinquemani, Nicholas J. Eagles, Daianna Gonzalez-Padilla, Sean K. Maden, Joel E. Kleinman, Thomas M. Hyde, Stephanie C. Hicks, Kristen R. Maynard, Leonardo Collado-Torres

引用次数: 0

Abstract

Cellular deconvolution of bulk RNA-sequencing data using single cell/nuclei RNA-seq reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as the human brain. Here, we generate a multi-assay dataset in postmortem human dorsolateral prefrontal cortex from 22 tissue blocks, including bulk RNA-seq, reference snRNA-seq, and orthogonal measurement of cell type proportions with RNAScope/ImmunoFluorescence. We use this dataset to evaluate six deconvolution algorithms. Bisque and hspe were the most accurate methods. The dataset, as well as the Mean Ratio gene marker finding method, is made available in the DeconvoBuddies R/Bioconductor package.

查看原文本刊更多论文

使用来自死后人类前额皮质的多测定数据集的细胞反褶积方法的基准

使用单细胞/细胞核RNA-seq参考数据对大量rna测序数据进行细胞反褶积是估计异质组织（如人脑）中细胞类型组成的重要策略。在这里，我们从22个组织块中生成了死后人类背外侧前额皮质的多分析数据集，包括大量RNA-seq，参考snRNA-seq，以及使用RNAScope/免疫荧光正交测量细胞类型比例。我们使用这个数据集来评估六种反卷积算法。Bisque和hspe是最准确的方法。该数据集以及Mean Ratio基因标记查找方法可在DeconvoBuddies R/Bioconductor软件包中获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

21.00

自引率

3.30%

发文量

241

审稿时长

2 months

期刊介绍： Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens. With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category. Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.