Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data

PLoS ONE

Volumn 9, Issue 7, 2014, Pages

  Pyne, Saumyadipta ^a   Lee, Sharon X ^b   Wang, Kui ^b   Irish, Jonathan ^c,d   Tamayo, Pablo ^e   Nazaire, Marc Danie ^e   Duong, Tarn ^f   Ng, Shu Kay ^g   Hafler, David ^h   Levy, Ronald ^c   Nolan, Garry P ^c   Mesirov, Jill ^e   McLachlan, Geoffrey J ^b  

^a UNIVERSITY OF HYDERABAD   (India)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e HARVARD UNIVERSITY   (United States)

^f CNRS   (France)

^g GRIFFITH UNIVERSITY   (Australia)

^h YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BREAKPOINT CLUSTER REGION PROTEIN; T LYMPHOCYTE RECEPTOR;

ARTICLE; B LYMPHOCYTE; CLASSIFICATION; COHORT ANALYSIS; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; FLOW CYTOMETRY; FOLLICULAR LYMPHOMA; HUMAN; HUMAN CELL; JOINT CLUSTERING AND MATCHING; LARGE CELL LYMPHOMA; MEMORY T LYMPHOCYTE; MISCLASSIFICATION RATE; PARAMETRIC TEST; SIGNAL TRANSDUCTION; SIMULATION; T LYMPHOCYTE SUBPOPULATION; ALGORITHM; BIOLOGY; CLUSTER ANALYSIS; COMPUTER SIMULATION; PROCEDURES; SOFTWARE;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; FLOW CYTOMETRY; HUMANS; SOFTWARE;

EID: 84903722445     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0100334     Document Type: Article

References (29)

1. Irish JM, Kotecha N, Nolan GP (2006) Mapping normal and cancer cell signalling networks: towards single-cell proteomics. Nat Rev Cancer 6: 146-155. (Pubitemid 43361547)
2. Perfetto SP, Chattopadhyay PK, Roederer M (2004) Seventeen-colour flow cytometry: unravelling the immune system. Nat Rev Immunol 4: 648-655. (Pubitemid 39025050)
3. Lugli E, Roederer M, Cossarizza A (2010) Data analysis in flow cytometry: the future just started. Cytometry A 77: 705-713.
4. Krutzik PO, Nolan GP (2006) Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nat Methods 3: 361-368.
5. Tanner SD, Bandura DR, Ornatsky O, Baranov VI, Nitz M, et al. (2008) Flow cytometer with mass spectrometer detection for massively multiplexed single-cell biomarker assay. Pure Appl Chem 80: 2627-2641.
6. Bendall SC, Simonds EF, Qiu P, Amir EaD, Krutzik PO, et al. (2011) Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332: 687-696.
7. Pyne S, Hu X, Wang K, Rossin E, Lin TI, et al. (2009) Automated high-dimensional flow cytometric data analysis. Proc Natl Acad Sci U S A 106: 8519-8524.
8. Kotecha N, Flores NJ, Irish JM, Simonds EF, Sakai DS, et al. (2008) Single-cell profiling identifies aberrant stat5 activation in myeloid malignancies with specific clinical and biologic correlates. Cancer Cell 14: 335-343.
9. Irish JM, Myklebust JH, Alizadeh AA, Houot R, Sharman JP, et al. (2010) B-cell signaling networks reveal a negative prognostic human lymphoma cell subset that emerges during tumor progression. Proc Natl Acad Sci U S A 107: 12747-1275.
10. Oved K, Eden E, Akerman M, Noy R, Wolchinsky R, et al. (2009) Predicting and controlling the reactivity of immune cell populations against cancer. Mol Syst Biol 5: 265.
11. Lo K, Hahne F, Brinkman RR, Gottardo R (2009) flowclust: a bioconductor package for automated gating of flow cytometry data. BMC Bioinformatics 10: 145.
12. Naim I, Datta S, Sharma G, Cavenaugh JS, Mosmann TR (2010) Swift: Scalable weighted iterative sampling for flow cytometry clustering. In: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP). pp. 509-512.
13. Pyne S, Wang K, Irish J, Tamayo P, Nazaire MD, et al. (2013) Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data. Preprint arXiv:13057344.
14. Aghaeepour N, Finak G, The FLOWCAP Consortium, The DREAM Consortium, Hoos H, et al. (2013) Critical assessment of automated flow cytometry analysis techniques. Nature Methods 10: 228-238.
15. Cron A, Gouttefangeas C, Frelinger J, Lin L, Singh SK, et al. (2013) Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples. PLoS Computational Biology 9.
16. Maier LM, Anderson DE, De Jager PL, Wicker LS, Hafler DA (2007) Allelic variant in ctla4 alters t cell phosphorylation patterns. Proc Natl Acad Sci U S A 104: 18607-18612. (Pubitemid 350210744)
17. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102: 15545-15550. (Pubitemid 41528093)
18. Tamayo P, Cho YJ, Tsherniak A, Greulich H, Ambrogio L, et al. (2011) Predicting relapse in patients with medulloblastoma by integrating evidence from clinical and genomic features. J Clin Oncol 29: 1415-1423.
19. Demers S, Kim J, Legendre P, Legendre L (1992) Analyzing multivariate flow cytometric data in aquatic sciences. Cytometry 13: 291-298.
20. Lo K, Gottardo R (2009) Automated gating of flow cytometry data via robust model-based clus-tering. Cytometry A 73: 321-332. (Pubitemid 351522115)
21. Frühwirth-Schnatter S, Pyne S (2010) Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions. Biostatistics 11: 317-336.
22. Baudry JP, Raftery AE, Celeux G, Lo K, Gottardo R (332-353) Combining mixture components for clustering. Journal of Computational and Graphical Statistics 19: 2010.
23. Liu X, Yang M (2009) Simultaneous curve registration and clustering for functional data. Computational Statistics and Data Analysis 53: 1361-1376.
24. Gaffney SJ, Robertson AW, Smyth P, Camargo SJ, Ghil M (2007) Probabilistic clustering of extratropical cyclones using regression mixture models. Climate Dynamics 29: 423-440. (Pubitemid 47022891)
25. McLachlan GJ, Krishnan T (2008) The EM Algorithm and Extensions. Hokoben, N. J.: Wiley- Interscience, 2nd edition.
26. Ng SK, McLachlan GJ, Wang K, Ben-Tovim L, Ng SW(2006) A mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinformatics 22: 1745-1752. (Pubitemid 44288337)
27. Hahne F, Khodabakhshi AH, Bashashati A, Wong CJ, Gascoyne RD, et al. (2010) Per-channel basis normalization methods for flow cytometry data. Cytometry A 77: 121-131.
28. McLachlan GJ, Peel D (1998) Robust cluster analysis via mixtures of multivariate t-distributions. In: Lecture Notes in Computer Science. Springer-Verlag, pp. 658-666.
29. Sahu SK, Dey DK, Branco MD (2003) A new class of multivariate skew distributions with applications to bayesian regression models. Can J Stat 31: 129-150. (Pubitemid 37395671)