FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data

Cytometry Part A

Volumn 87, Issue 7, 2015, Pages 636-645

  Van Gassen, Sofie ^a,b,c   Callebaut, Britt ^a   Van Helden, Mary J ^b,c   Lambrecht, Bart N ^b,c   Demeester, Piet ^a   Dhaene, Tom ^a   Saeys, Yvan ^b,c  

^a GHENT UNIVERSITY   (Belgium)

^b DEPARTMENT OF PLANT SYSTEMS BIOLOGY   (Belgium)

^c GHENT UNIVERSITY HOSPITAL   (Belgium)

Author keywords

Bioinformatics; Exploratory data analysis; Key terms: polychromatic flow cytometry; Mass cytometry; Self organizing map; Visualization method

Indexed keywords

BIOLOGICAL MARKER;

ALGORITHM; BIOLOGY; CLUSTER ANALYSIS; FLOW CYTOMETRY; GRAFT VS HOST DISEASE; HEMATOPOIETIC STEM CELL TRANSPLANTATION; HUMAN; LYMPHOMA, B-CELL; PROCEDURES; WEST NILE FEVER;

ALGORITHMS; BIOMARKERS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; FLOW CYTOMETRY; GRAFT VS HOST DISEASE; HEMATOPOIETIC STEM CELL TRANSPLANTATION; HUMANS; LYMPHOMA, B-CELL; WEST NILE FEVER;

EID: 84932198501     PISSN: 15524922     EISSN: 15524930     Source Type: Journal    
DOI: 10.1002/cyto.a.22625     Document Type: Article

References (18)

1. Amir ED, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe'er D. Visne enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 2013;31:545-552.
2. Qiu P, Simonds EF, Bendall SC, Gibbs KD Jr, Bruggner RV, Linderman MD, Sachs K, Nolan GP, Plevritis SK. Extracting a cellular hierarchy from high-dimensional cytometry data with spade. Nat Biotechnol 2011;29:886-891.
3. Lo K, Brinkman R, Gottardo R. Automated gating of flow cytometry data via robust model-based clustering. Cytometry A 2008;73A:321-332.
4. Pyne S, Hu X, Wang K, Rossin E, Lin TI, Maier LM, Baecher-Allan C, McLachlan GJ, Tamayo P, Hafler DA, De Jager PL, Mesirov JP. Automated high-dimensional flow cytometric data analysis. Proc Natl Acad Sci USA 2009;106:8519.
5. Lo K, Hahne F, Brinkman R, Gottardo R. FlowClust: A bioconductor package for automated gating of flow cytometry data. BMC Bioinform 2009;10:145.
6. Finak G, Bashashati A, Brinkman R, Gottardo R. Merging mixture components for cell population identification in flow cytometry. Adv Bioinform 2009;2009:247646.
7. Aghaeepour N, Nikolic R, Hoos HH, Brinkman RR. Rapid cell population identification in flow cytometry data. Cytometry A 2011;79A:6-13.
8. Naim I, Datta S, Rebhahn J, Cavenaugh JS, Mosmann TR Sharma G. Swift: Scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 1: Algorithm design. Cytometry A 2014;85.5:408-421.
9. Cron A, Gouttefangeas C, Frelinger J, Lin L, Singh SK, Britten CM, Chan C. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples. PLoS Comput Biol 2013;9:e1003130.
10. Pyne S, Wang K, Irish J, Tamayo P, Nazaire MD, Duong T, McLachlan GJ. Joint modeling and registration of cell populations in cohorts of High-dimensional flow cytometric data. Plos One 2014;9:e100334.
11. Aghaeepour N, Finak G, FlowCAP Consortium, DREAM Consortium, Hoos HH, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH. Critical assessment of automated flow cytometry data analysis techniques. Nat Methods 2013;10:228-238.
12. Kohonen T. The self-organizing map. Proc IEEE 1990;78:1464-1480.
13. Wehrens R, Buydens LMC. Self- and super-organising maps in r: The kohonen package. J Stat Softw 2007;21.5:1-19.
14. Whitney VKM. Algorithm 422: Minimal spanning tree. Commun ACM 1972;15:273-274.
15. Csardi G, Nepusz T. The igraph software package for complex network research. Int J Complex Syst 2006;1695.
16. Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inform Process Lett 1989;31:7-15.
17. Wilkerson M, Waltman P. ConsensusClusterPlus: ConsensusClusterPlus, 2013. R package version 1.18.0.
18. Bendall SC, Simonds EF, Qiu P, Amir ED, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 2011;332:687-696.