Cell type identification for single cell RNA data by bulk data reference projection.

Single cell RNA sequencing enables high resolution biological data that can be used for refined biological analyses. Many of these analyses require identification of biological cell types in the data. Some existing methods use bulk data with known cell type labels to identify cell types in the single cell data. In this work, we propose a novel approach that is using bulk data as well. Compared to the existing approaches mapping single cell data into the space of the bulk data, our method does the opposite: it maps the bulk observations to the space of the denoised single cell observations. Our numerical results illustrate that our approach generally leads to more accurate annotations, especially when other methods struggle to find a clear separation between the cell types. In particular, our method was able to separate between CD4+ and CD8+T-cells that other approaches could not achieve by using given bulk data.