We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE.
- Authors
Qiu, Peng; Simonds, Erin F; Bendall, Sean C; Gibbs, Kenneth D, Jr; Bruggner, Robert V; Linderman, Michael D; Sachs, Karen; Nolan, Garry P; Plevritis, Sylvia K
- Abstract
The ability to analyze multiple single-cell parameters is critical for understanding cellular heterogeneity. Despite recent advances in measurement technology, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system. To objectively uncover cellular heterogeneity from single-cell measurements, we present a versatile computational approach, spanning-tree progression analysis of density-normalized events (SPADE). We applied SPADE to flow cytometry data of mouse bone marrow and to mass cytometry data of human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. We demonstrate that SPADE is robust to measurement noise and to the choice of cellular markers. SPADE facilitates the analysis of cellular heterogeneity, the identification of cell types and comparison of functional markers in response to perturbations.
- Publication
Nature biotechnology, 2011, Vol 29, Issue 10, p886
- ISSN
1546-1696
- Publication type
Journal Article
- DOI
10.1038/nbt.1991