CATD:用于选择跨组织细胞类型解卷积方法的可重复管道。

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-03-23 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae048
Anna Vathrakokoili Pournara, Zhichao Miao, Ozgur Yilimaz Beker, Nadja Nolte, Alvis Brazma, Irene Papatheodorou
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引用次数: 0

摘要

动机细胞类型解卷积方法旨在从大量转录组数据中推断细胞组成。已开发的方法层出不穷,但在许多情况下得到的结果并不一致,这突出表明在选择适当方法时迫切需要指导。此外,单细胞 RNA 测序数据集的可获取性越来越高,通常还伴随着相关样本的大量表达,这使得现有方法的基准得以确立:在这项研究中,我们利用来自不同人类和小鼠组织的单细胞 RNA 测序数据,对 31 种方法进行了全面评估。通过各种模拟场景,我们揭示了基于回归的去卷积方法的功效,并强调了这些方法对参照物选择的敏感性。我们结合样本、研究和技术等变量,研究了批量参考差异的影响。我们使用来自单核细胞的金标准数据集进行了验证,并提出了在无法获得地面实况时的比例共识预测方法。我们在胃部数据上验证了共识方法,并研究了其溢出效应。重要的是,我们建议使用转录组去卷积关键评估(CATD)管道,该管道包含生成参考和伪大量以及运行已实施的去卷积方法的功能。CATD 简化了大量样本的同步解卷积,为加快评估新开发的方法提供了实用的解决方案。可用性和实施:https://github.com/Papatheodorou-Group/CATD_snakemake。
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CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues.

Motivation: Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Results: In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

Availability and implementation: https://github.com/Papatheodorou-Group/CATD_snakemake.

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