The number of single-cell sequencing experiments has been constantly growing over the last few years. At the same time, a plethora of new methods and tools were developed for the analysis of single-cell sequencing data. In 2009, Tang and colleagues proposed an unbiased research method for mRNA based on high-throughput sequencing in a single cell for the first time. After that, single-cell sequencing is widely used for the analysis of gene expression levels and/or genomic mutations within individual cells. With the rapid accumulation of sequencing data and processing softwares, a major challenge for researchers is to choose appropriate tools and parameters to perform data analysis. We provide the database, SingleScan, which focuses on the integration of single-cell transcriptome/genome analysis tools, and also integrates the key information in the publications to facilitate researchers to select the appropriate tools. SingleScan also provides valuable information on the current development trends of single-cell analysis such as cancers, immunity.

The functions of SingleScan include: 1) Search by publications. Users can obtain an overview of the tools, R packages and parameters used in each publication, and also can get the information of number of cells, sequencing platform and patients’ information in each publication. 2) Search by tools. Users can search tools by key words (e.g. Clustering, quality control). 3) Search by functions. SingleScan classifies all tools according to their analysis tasks. Users can search tools by function. 4) Single-cell Workflow. SingleScan summarizes the basic process of single-cell analysis from all the publications that we collected. For each step, we provide the list of available tools. 5) Statistics. Users can get insights into the current single-cell development trends, and get a quick overview of the characters of each tool.