Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
SIB Swiss Institute of Bioinformatics, Zurich, Switzerland.
BMC Bioinformatics. 2021 May 10;22(1):235. doi: 10.1186/s12859-021-04125-4.
Innovations in single cell technologies have lead to a flurry of datasets and computational tools to process and interpret them, including analyses of cell composition changes and transition in cell states. The diffcyt workflow for differential discovery in cytometry data consist of several steps, including preprocessing, cell population identification and differential testing for an association with a binary or continuous covariate. However, the commonly measured quantity of survival time in clinical studies often results in a censored covariate where classical differential testing is inapplicable.
To overcome this limitation, multiple methods to directly include censored covariates in differential abundance analysis were examined with the use of simulation studies and a case study. Results show that multiple imputation based methods offer on-par performance with the Cox proportional hazards model in terms of sensitivity and error control, while offering flexibility to account for covariates. The tested methods are implemented in the R package censcyt as an extension of diffcyt and are available at https://bioconductor.org/packages/censcyt .
Methods for the direct inclusion of a censored variable as a predictor in GLMMs are a valid alternative to classical survival analysis methods, such as the Cox proportional hazard model, while allowing for more flexibility in the differential analysis.
单细胞技术的创新带来了大量的数据集和计算工具来处理和解释这些数据集和工具，包括对细胞组成变化和细胞状态转变的分析。流式细胞术数据中差异发现的 diffcyt 工作流程包括几个步骤，包括预处理、细胞群体识别和与二元或连续协变量相关的差异测试。然而，在临床研究中通常测量的生存时间往往导致协变量被删失，而经典的差异测试在此情况下不适用。
为了克服这一限制，使用模拟研究和案例研究检验了多种将删失协变量直接纳入差异丰度分析的方法。结果表明，基于多重插补的方法在敏感性和误差控制方面与 Cox 比例风险模型表现相当，同时提供了灵活的方法来考虑协变量。测试的方法在 R 包 censcyt 中实现，作为 diffcyt 的扩展，可在 https://bioconductor.org/packages/censcyt 获得。
将删失变量直接作为 GLMMs 的预测因子纳入的方法是经典生存分析方法（如 Cox 比例风险模型）的有效替代方法，同时在差异分析中提供了更大的灵活性。
