Mixed-effects association of single cells identifies an expanded effector CD4+ T cell subset in rheumatoid arthritis

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Science Translational Medicine  17 Oct 2018:
Vol. 10, Issue 463, eaaq0305
DOI: 10.1126/scitranslmed.aaq0305

Pinpointing culprits in single-cell data

New techniques analyzing single cells are being applied to clinical samples. These techniques generate large datasets, and it can be challenging to identify rare cell types associated with disease. Fonseka et al. developed a simple statistical method to do just that while simultaneously controlling for confounding biological and technical variation. Using their method on single-cell mass and flow cytometry data revealed an expanded CD4+ T cell subset in the blood of rheumatoid arthritis patients that was later seen to contract upon treatment. The authors’ method performed better than the current gold standard and could be a potentially widely applied tool for the analysis of high-dimensional single-cell data.

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