Single-cell RNA-seq (scRNA-seq) allows researchers to define cell types on the basis of unsupervised clustering of the transcriptome. However, differences in experimental methods and computational analyses make it challenging to compare data across experiments. Here we present scmap (http://bioconductor.org/packages/scmap; web version at http://www.sanger.ac.uk/science/tools/scmap), a method for projecting cells from an scRNA-seq data set onto cell types or individual cells from other experiments.

中文翻译：

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scmap：跨数据集的单细胞RNA-seq数据投影

单细胞RNA序列（scRNA-seq）使研究人员可以在转录组的无监督聚类的基础上定义细胞类型。但是，实验方法和计算分析的差异使得在整个实验中比较数据具有挑战性。在这里，我们介绍了scmap（http://bioconductor.org/packages/scmap；网络版本位于http://www.sanger.ac.uk/science/tools/scmap），这是一种从scRNA-seq数据投射细胞的方法设置其他实验中的细胞类型或单个细胞。