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Nat Methods. 2017 Jul;14(7):707-709. doi: 10.1038/nmeth.4295. Epub 2017 May 15.

Testing for differential abundance in mass cytometry data.

Author information

1
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
2
Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
3
EMBL European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK.
4
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK.

Abstract

When comparing biological conditions using mass cytometry data, a key challenge is to identify cellular populations that change in abundance. Here, we present a computational strategy for detecting 'differentially abundant' populations by assigning cells to hyperspheres, testing for significant differences between conditions and controlling the spatial false discovery rate. Our method (http://bioconductor.org/packages/cydar) outperforms other approaches in simulations and finds novel patterns of differential abundance in real data.

PMID:
28504682
PMCID:
PMC6155493
DOI:
10.1038/nmeth.4295
[Indexed for MEDLINE]
Free PMC Article

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