Semantic Scholar Open Access 2011 953 sitasi

Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE

P. Qiu Erin F. Simonds S. Bendall Kenneth D. Gibbs R. Bruggner +4 lainnya

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Abstrak

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.

Topik & Kata Kunci

Biology Medicine

Penulis (9)

P. Qiu

Erin F. Simonds

S. Bendall

Kenneth D. Gibbs

R. Bruggner

M. Linderman

K. Sachs

G. Nolan

S. Plevritis

Format Sitasi

APA MLA BibTeX

Qiu, P., Simonds, E.F., Bendall, S., Gibbs, K.D., Bruggner, R., Linderman, M. et al. (2011). Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE. https://doi.org/10.1038/nbt.1991

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Lihat di Sumber doi.org/10.1038/nbt.1991

Informasi Jurnal

Tahun Terbit: 2011
Bahasa: en
Total Sitasi: 953×
Sumber Database: Semantic Scholar
DOI: 10.1038/nbt.1991
Akses: Open Access ✓