Introduction

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.

Publications

  1. Testing for differential abundance in mass cytometry data.
    Cite this
    Lun ATL, Richard AC, Marioni JC, 2017-07-01 - Nature methods

Credits

  1. Aaron T L Lun
    Developer

    Cancer Research UK Cambridge Institute, University of Cambridge, United Kingdom of Great Britain and Northern Ireland

  2. Arianne C Richard
    Developer

    Cambridge Institute for Medical Research, University of Cambridge

  3. John C Marioni
    Investigator

    Wellcome Trust Sanger Institute, Wellcome Genome Campus

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Summary
AccessionBT001241
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByJohn C Marioni