Single-cell RNA sequencing (scRNA-Seq) is fast becoming one powerful tool for high-throughput transcriptomic analysis of cell states and dynamics. With the increasing number of scRNASeq data sets, there is need to provide a web resource which curates public single-cell gene expressing profiles for the wider research community. At present, there are two web resources about single cell transcriptome. One is based on one single HPSC transcriptome data set, providing insights into blood stem cell differentiation in mouse (Nestorowa, et al. Blood, 2016), the other is LungGENS, a web resource for one single-cell gene expression data set in the developing lung of mouse (Du et al. Thorax, 2015). However, there is no comprehensive resource or web interface for single cell transcriptome data. Here, a freely accessible online resource which incorporates 36 human single cell transcriptome data sets (174 cell groups and 8910 single cells) analyzed by scRNA-seq is provided. Using the web resource, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different cell groups, or get the differential expression (DE) gene list between cell groups. The characteristics above combined with visual features, including gene tags, heatmap of gene expression, boxplot of gene expression in each cell group, correlation matrix for top up-regulated genes, GO and pathway annotations for DE genes or top up-regulated genes, will make the database a useful and unique reference resource for biology and medicine.