Visual quality control with CytoMDS, a Bioconductor package for low dimensional representation of cytometry sample distances

Abstract

Quality Control (QC) of samples is an essential preliminary step in cytometry data analysis. Notably, identification of potential batch effects and outlying samples is paramount, to avoid mistaking these effects for true biological signal in downstream analyses. However, this task can prove to be delicate and tedious, especially for datasets with many samples. Here, we present CytoMDS, a Bioconductor package implementing a dedicated method for low dimensional representation of cytometry samples composed of marker expressions for up to millions of single cells. This method allows a global representation of all samples of a study, with one single point per sample, in such a way that projected distances can be visually interpreted. It uses Earth Mover's Distance for assessing dissimilarities between multi-dimensional distributions of marker expression, and Multi Dimensional Scaling for low dimensional projection of distances. Some additional visualization tools, both for projection quality diagnosis and for user interpretation of the projection coordinates, are also provided in the package. We demonstrate the strengths and advantages of CytoMDS for QC of cytometry data on three real biological datasets, revealing the presence of low quality samples, batch effects and biological signal between sample groups.

Competing Interest Statement

S.D., S.T., and D.L. are employees of the GSK group of companies and report ownership of GSK shares. S.T. is listed as inventor on patents owned by the GSK group of companies. P.H. is a student at the de Duve Institute (UCLouvain) and participates in a post graduate studentship program at GSK. L.G. reports no competing interest.

Footnotes

* New 'CytoMDS can be used at different stages of the data analysis pipeline' section, new paragraph about computational time, and minor rephrasing.

* https://github.com/UCLouvain-CBIO/2024-cytoMDS-code