Journal article

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Marie Trussart, Charis E Teh, Tania Tan, Lawrence Leong, Daniel HD Gray, Terence P Speed



Mass cytometry (CyTOF) is a technology that has revolutionised single-cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However, most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches, which includes an R-Shiny application with diagnostic plots. CytofRUV can correct for batc..

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Awarded by National Health and Medical Research Council

Awarded by Cancer Council Victoria

Awarded by Perpetual Impact Philanthropy

Funding Acknowledgements

National Health and Medical Research Council 1054618 Marie Trussart Terence P SpeedNational Health and Medical Research Council 1158024 Daniel HD GrayCancer Council Victoria 1146518 Tania Tan Daniel HD GrayNational Health and Medical Research Council 1089072 Charis E TehPerpetual Impact Philanthropy IPAP2019/1437 Charis E TehUROP Fellowship Lawrence LeongThe funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.