Unveiling Disease-Altered Cell States with Healthy Single-Cell References
Precise identification of cell phenotypes altered in disease can provide valuable insights into pathogenesis, biomarkers, and potential drug targets. The selection of a healthy reference dataset is crucial for accurate analysis. This study compared the use of an atlas dataset and a control dataset as references for identifying disease-associated cell states. The results showed that combining both datasets (ACR design) led to sensitive detection of disease-specific cell states and reduced false positives. The ACR design was robust to variations in the size and composition of the reference datasets. The benefits of using an atlas dataset were demonstrated in the identification of interferon-stimulated states in patients with COVID-19.