AUTHOR=Schuyler Ronald P. , Jackson Conner , Garcia-Perez Josselyn E. , Baxter Ryan M. , Ogolla Sidney , Rochford Rosemary , Ghosh Debashis , Rudra Pratyaydipta , Hsieh Elena W. Y. TITLE=Minimizing Batch Effects in Mass Cytometry Data JOURNAL=Frontiers in Immunology VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2019.02367 DOI=10.3389/fimmu.2019.02367 ISSN=1664-3224 ABSTRACT=

Cytometry by Time-Of-Flight (CyTOF) uses antibodies conjugated to isotopically pure metals to identify and quantify a large number of cellular features with single-cell resolution. A barcoding approach allows for 20 unique samples to be pooled and processed together in one tube, reducing the intra-barcode technical variability. However, with only 20 samples per barcode, multiple barcode sets (batches) are required to address questions in robustly powered study designs. A batch adjustment procedure is required to reduce variability across batches and to facilitate direct comparison of runs performed across multiple barcodes run over weeks, months, or years. We describe a method using technical replicates that are included in each run to determine and apply an appropriate adjustment per batch without manual intervention. The use of technical replicate samples (i.e., anchors or reference samples) avoids assumptions of sample homogeneity among batches, and allows direct estimation of batch effects and appropriate adjustment parameters applicable to all samples within a batch. Quantification of cell subpopulations and mean signal intensity pre- and post-adjustment using both manual gating and unsupervised clustering demonstrate substantial mitigation of batch effects in the anchor samples used for this adjustment calculation, and in a second validation set of technical replicates.