cyCombine allows for robust integration of single-cell cytometry datasets within and across technologies

• Published in: Nature communications Vol. 13; no. 1; pp. 1698 - 12
• Main Authors: Pedersen, Christina Bligaard, Dam, Søren Helweg, Barnkob, Mike Bogetofte, Leipold, Michael D., Purroy, Noelia, Rassenti, Laura Z., Kipps, Thomas J., Nguyen, Jennifer, Lederer, James Arthur, Gohil, Satyen Harish, Wu, Catherine J., Olsen, Lars Rønn
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 31.03.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/2401; 631/114/2784; 631/114/794; 82/1; 82/80; Data analysis; Datasets; Flexibility; Flow cytometry; Flow Cytometry - methods; Humanities and Social Sciences; Integration; Massive data points; multidisciplinary; Robustness; Science; Science (multidisciplinary); Statistics; Technology; Variance

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a...