Target-oriented Reference Construction for supervised cell type identification in scRNA-seq

Cell type identification is a crucial step in single-cell RNA-seq (scRNA-seq) data analysis. The supervised cell type identification method is a preferred solution due to its accuracy and efficiency. The performance of such methods highly depends on the quality of the reference data. Although there are many supervised cell type identification tools, no method currently exists for constructing reference data. Here, we develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing references based on target datasets in scRNA-seq supervised cell type identification. TORC focuses on alleviating differences in cell type composition between the reference and target sets. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell type identification with TORC.