Alignment of single-cell RNA-seq samples without overcorrection using kernel density matching.
Alignment of single-cell RNA-seq samples without overcorrection using kernel density matching.
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DOI：
10.1101/gr.261115.120
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发表时间：
2021-04
期刊：
影响因子：
7
通讯作者：
Li YI
中科院分区：
文献类型：
--
作者：
Chen M;Zhan Q;Mu Z;Wang L;Zheng Z;Miao J;Zhu P;Li YI
单细胞RNA测序（scRNA-seq）技术有望在许多生物和医学应用中取代大细胞RNA测序，因为它允许用户以特定细胞类型的方式测量基因表达水平。然而，scRNA-seq产生的数据通常表现出特定于细胞类型、样品或实验的批处理效应，这阻碍了多个实验之间的整合或比较。在这里，我们提出了Dmatch，一种利用人类原代细胞的外部表达图谱和核密度匹配来对齐多个scRNA-seq实验以进行下游生物学分析的方法。Dmatch有助于将scRNA-seq数据集与可能仅部分重叠的细胞类型进行比对，从而允许整合多个不同的scRNA-seq实验以提取生物学见解。在模拟中，Dmatch在减少样本特定聚类和避免过度校正方面优于其他对齐方法。当应用于从健康个体和5名自身免疫性疾病患者的临床样本中收集的scRNA-seq数据时，Dmatch实现了跨活检部位和疾病状况的细胞类型特异性差异基因表达比较，并揭示了RA患者跨活检部位的促炎单核细胞共享群。我们进一步表明，Dmatch增加了从群体scRNA-seq数据中映射的eqtl的数量。Dmatch快速，可扩展，并在几个重要应用中提高了scRNA-seq的实用性。Dmatch在网上是免费的。
Single-cell RNA sequencing (scRNA-seq) technology is poised to replace bulk cell RNA sequencing for many biological and medical applications as it allows users to measure gene expression levels in a cell type–specific manner. However, data produced by scRNA-seq often exhibit batch effects that can be specific to a cell type, to a sample, or to an experiment, which prevent integration or comparisons across multiple experiments. Here, we present Dmatch, a method that leverages an external expression atlas of human primary cells and kernel density matching to align multiple scRNA-seq experiments for downstream biological analysis. Dmatch facilitates alignment of scRNA-seq data sets with cell types that may overlap only partially and thus allows integration of multiple distinct scRNA-seq experiments to extract biological insights. In simulation, Dmatch compares favorably to other alignment methods, both in terms of reducing sample-specific clustering and in terms of avoiding overcorrection. When applied to scRNA-seq data collected from clinical samples in a healthy individual and five autoimmune disease patients, Dmatch enabled cell type–specific differential gene expression comparisons across biopsy sites and disease conditions and uncovered a shared population of pro-inflammatory monocytes across biopsy sites in RA patients. We further show that Dmatch increases the number of eQTLs mapped from population scRNA-seq data. Dmatch is fast, scalable, and improves the utility of scRNA-seq for several important applications. Dmatch is freely available online.
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影响因子：
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