Quantifying Cell-Type-Specific Differences of Single-Cell Datasets Using Uniform Manifold Approximation and Projection for Dimension Reduction and Shapley Additive exPlanations
Quantifying Cell-Type-Specific Differences of Single-Cell Datasets Using Uniform Manifold Approximation and Projection for Dimension Reduction and Shapley Additive exPlanations
复制标题
使用统一流形近似和投影进行降维和 Shapley 加法解释来量化单细胞数据集的细胞类型特异性差异
DOI：
10.1089/cmb.2022.0366
复制
发表时间：
2023
影响因子：
1.7
通讯作者：
Qiu, Peng
中科院分区：
文献类型：
--
作者：
Lim, Hong Seo;Qiu, Peng
随着单细胞分析技术的快速发展，需要对多个单细胞数据集进行比较的大规模研究可能会产生新的发现。具体来说，通过单细胞数据集对不同条件下的细胞类型特异性反应进行量化，可能有助于理解条件差异是如何在细胞水平上诱导的。在这项研究中，我们提出了一个计算管道，量化细胞类型特异性差异，并确定负责差异的基因。我们量化了在降维空间的低维均匀流形近似和投影中观察到的差异，作为高维空间中存在差异的代理，并使用SHapley加性解释来量化驱动差异的基因。在这项研究中，我们将我们的算法应用于鸢尾花数据集、单细胞RNA测序数据集和大量细胞计数数据集，并证明它可以稳健地量化细胞类型特异性差异，并且还可以识别导致差异的基因。
With rapid advances in single-cell profiling technologies, larger-scale investigations that require comparisons of multiple single-cell datasets can lead to novel findings. Specifically, quantifying cell-type-specific responses to different conditions across single-cell datasets could be useful in understanding how the difference in conditions is induced at a cellular level. In this study, we present a computational pipeline that quantifies cell-type-specific differences and identifies genes responsible for the differences. We quantify differences observed in a low-dimensional uniform manifold approximation and projection for dimension reduction space as a proxy for the difference present in the high-dimensional space and use SHapley Additive exPlanations to quantify genes driving the differences. In this study, we applied our algorithm to the Iris flower dataset, single-cell RNA sequencing dataset, and mass cytometry dataset and demonstrate that it can robustly quantify cell-type-specific differences and it can also identify genes that are responsible for the differences.
单细胞RNA-Seq揭示了新型的人类血液树突状细胞，单核细胞和祖细胞。
DOI：
10.1126/science.aah4573
发表时间：
2017-04-21
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Villani AC;Satija R;Reynolds G;Sarkizova S;Shekhar K;Fletcher J;Griesbeck M;Butler A;Zheng S;Lazo S;Jardine L;Dixon D;Stephenson E;Nilsson E;Grundberg I;McDonald D;Filby A;Li W;De Jager PL;Rozenblatt-Rosen O;Lane AA;Haniffa M;Regev A;Hacohen N
通讯作者：
Hacohen N
影响因子：
23.8
作者：
Lundberg, Scott M.;Erion, Gabriel;Lee, Su-In
通讯作者：
Lee, Su-In