Testing for differential abundance in mass cytometry data.

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.

SUBMITTER: Lun ATL 

PROVIDER: S-EPMC6155493 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature