A simple strategy for sample annotation error detection in cytometry datasets
M. Smithmyer, A. E. Wiedeman, D. A. G. Skibinski, A. K. Savage, C. Acosta-Vega, S. Scheiding, V. H. Gersuk, S. A. Long, J. H. Buckner, C. Speake
The paper detects sample annotation errors in cytometry data by comparing HLA allele expression with longitudinal and qPCR data, identifying mismatches in 2.4% of samples.
bioRxiv · Oct 26, 2021Immunology