The possibility of studying the phenotypical and molecular characteristics of the cells in a high-throughput manner is changing our understanding of biological systems. However, the analysis of single-cell omics data requires the use of dimensionality reduction techniques that need to be tailored and correctly interpreted. This fine-tuning is a time-consuming process that requires expert curation to extract the most information out of the data. Also, different high-throughput techniques on the same cell or cellular type are often combined, ranging from cytometry to imaging and transcriptomics.

scDAVIS is a web-based tool for the analysis and visualization of different modalities of single-cell omics data:

(1) scRNA-Seq, (2) Imaging data (Imaris), (3) Cytometry, and (4) General tabular data.

Importantly, scDAVIS is also a repository of publicly a,vailable single-cell experiments, allowing further exploration and reuse of public data, in line with the compliance of FAIR principles. Also, it can serve as a repository to share single-cell data with the community and to ease integration of different datasets.