Publications

You can download our core technologies and expertise in presentation format with links (blue text) to primary literature.

Peer-reviewed literature describing the technologies we developed for high throughput flow cytometry data analysis and datasets we have applied them to:

  1. Spidlen J, Gentleman RC, Haaland PD, Langille M, Le Meur N, Ochs MF, Schmitt C, Smith CA, Treister AS & Brinkman RR. Data standards for flow cytometry. OMICS 10: 209-214, 2006.
  2. Brinkman RR, Gasparetto M, Lee SJ, Ribickas AJ, Perkins J, Janssen W, Smiley R & Smith C. High-content flow cytometry and temporal data analysis for defining a cellular signature of graft-versus-host disease. Biol Blood Marrow Transplant 13: 691-700, 2007.
  3. Dykstra B, Kent D, Bowie M, McCaffrey L, Hamilton M, Lyons K, Lee S, Brinkman R & Eaves C. Long-term propagation of distinct hematopoietic differentiation programs in vivo. Cell Stem Cell 1: 218-229, 2007.
  4. Le Meur N, Rossini A, Gasparetto M, Smith C & Brinkman RR. Data quality assessment of ungated flow cytometry data in high throughput experiments. Cytometry A 71: 393-403, 2007.
  5. Lee JA, Spidlen J, Boyce K, Cai J, Crosbie N, Dalphin D, Furlong J, Gasparetto M, Goldberg M, Goralczyk EM, Hyun B, Jansen K, Kollmann T, Kong M, Leif R,  McWeeney S, Moloshok TD, Moore W, Nolan G, Nolan J, Nikolich-Zugich J, Parrish D, Purcell B, Qian Y, Selvaraj B, Smith C, Tchuvatkina O,  Wertheimer A, Wilkinson P,  Wilson C, Wood J, Zigon R, International Society for Advancement of Cytometry Data Standards Task Force, Scheuermann RH, Brinkman RR. MIFlowCyt: The Minimum Information about a Flow Cytometry experiment. Cytometry A 73: 926-930, 2008.
  6. Lo K, Brinkman RR & Gottardo R. Automated gating of flow cytometry data via robust model-based clustering. Cytometry A 73: 321-332, 2008.
  7. Ramadan KM, Connors JM, Al Tourah AJ, Song KW, Gascoyne RD, Barnett MJ, Nevill TJ, Shepherd JD, Nantel SH, Sutherland HJ, Forrest DL, Hogge DE, Lavoie JC, Abou-Mourad YR, Chhanabhai M, Voss NJ, Brinkman RR, Smith CA & Toze CL. Allogeneic SCT for relapsed composite and transformed lymphoma using related and unrelated donors: long-term results. Bone Marrow Transplant 42: 601-608, 2008.
  8. Spidlen J, Leif RC, Moore W, Roederer M, International Society for Analytical Cytology Data Standards Task Force, Brinkman RR. Gating-ML: XML-based gating descriptions in flow cytometry. Cytometry A 73A: 1151-1157,
  9. Bashashati A & Brinkman RR. A survey of flow cytometry data analysis methods. Adv Bioinformatics 2009: 584603, 2009.
  10. Bashashati A, Lo K, Gottardo R, Gascoyne RD, Weng A, & Brinkman R. A pipeline for automated analysis of flow cytometry data: preliminary results on lymphoma sub-type diagnosis. Conf Proc IEE Eng Med Biol Soc 2009: 4945-8, 2009.
  11. Finak G, Bashashati A, Brinkman R & Gottardo R. Merging mixture components for cell population identification in flow cytometry. Adv Bioinformatics 2009: 1-12, 2009.
  12. Hahne F, LeMeur N, Brinkman RR, Ellis B, Haaland PD, Sarkar D, Spidlen J, Strain E & Gentleman R. flowCore: a bioConductor package for high throughput flow cytometry.  BMC Bioinformatics 10: 106 2009.
  13. Johnson NA, Boyle M, Bashashati A, Leach S, Brooks-Wilson A, Sehn LH, Chhanabhai M, Brinkman RR, Connors JM, Weng AP & Gascoyne RD. Diffuse large B-cell lymphoma: reduced CD20 expression is associated with an inferior survival. Blood 113: 3773-80, 2009.
  14. Lo K, Hahne F, Brinkman RR & Gottardo R. flowClust: a Bioconductor package for automated gating of flow cytometry data. BMC Bioinformatics 10: 145 2009.
  15. Strain E, Hahne F, Brinkman RR & Haaland P. Analysis of high throughput flow cytometry data using plateCore. Adv Bioinformatics 2009: 1-10, 2009.Vercauteren SM, Bashashati A, Wu D, Brinkman RR, Eaves C, Eaves A & Karsan A. Reduction in multilineage and erythroid progenitors distinguishes myelodysplastic syndromes from non-malignant cytopenias. Leuk Res 33: 1636-1642, 2009.
  16. Blimkie D, Fortuno ES III, Thommai F, Xu L, Fernandes E, Crabtree J, Rein-Weston A, Jansen K, Brinkman RR* & Kollmann TR*. Identification of B cells through negative gating-An example of the MIFlowCyt standard applied. Cytometry A 77: 546-551, 2010.
  17. Hahne F*, Khodabakhshi AH*, Bashashati A, Wong CJ, Gascoyne RD, Weng AP, Seyfert-Margolis S, Bourcier K, Asare A, Lumley T, Gentleman R & Brinkman RR. Per-channel basis normalization methods for flow cytometry data. Cytometry A 77: 121-131, 2010.
  18. Jiang X, Forrest D, Nicolini F, Turhan A, Guilhot J, Yip C, Holyoake T, Jorgensen H, Lambie K, Saw KM, Pang E, Vukovic R, Lehn P, Ringrose A, Yu M, Brinkman RR, Smith C, Eaves A & Eaves C. Properties of CD34+ CML stem/progenitor cells that correlate with different clinical responses to imatinib mesylate. Blood 116: 2112-2121, 2010.
  19. Shooshtari P, Fortuno ES III, Blimkie D, Yu M, Gupta A, Kollmann TR & Brinkman RR. Correlation analysis of intracellular and secreted cytokines via the generalized integrated mean fluorescence intensity. Cytometry A 77: 873-880, 2010.
  20. Spidlen J, Moore W, Parks D, Goldberg M, Bray C, Bierre P, Gorombey P, Hyun B, Hubbard M, Lange S, Lefebvre R, Leif R, Novo D, Ostruszka L, Triester A, Wood J, Murphy RF, Roederer M, Sudar D, Zigon R & Brinkman RR. Data file standard for flow cytometry, version FCS 3.1. Cytometry A 77: 97-100, 2010.
  21. Zare H, Shooshtari P, Gupta A & Brinkman RR. Data reduction for spectral clustering to analyze high throughput flow cytometry data. BMC Bioinformatics 11: 403, 2010.
  22. Aghaeepour N, Nikolic R, Hoos HH & Brinkman RR. Rapid cell population identification in flow cytometry data. Cytometry A 79: 6-13, 2011.
  23. Spidlen J, Shooshtari P, Kollmann TR & Brinkman RR. Flow cytometry data standards. BMC Res Notes 4: 50 2011.
  24. Zare H, Bashashati A, Kridel R, Aghaeepour N, Haffari G, Connors JM, Gascoyne RD, Gupta A, *Brinkman RR, *Weng AP. Automated analysis of multidimensional flow cytometry data improves diagnostic accuracy between mantle cell lymphoma and small lymphocytic lymphoma. American Journal of Clinical Pathology 137: 75-85, 2012.
  25. Bashashati A, Johnson, NA, Khodabakhshi AH, Whiteside MD, Scott DW, Lo K, Gottardo R, Brinkman FSL, Connors JM, Slack GW, Gascoyne RD,  Weng AP*, Brinkman RR*. B-cells with high side scatter parameter by flow cytometry correlate with inferior survival in diffuse large B cell lymphoma. American Journal of Clinical Pathology 137:805-814, 2012.
  26. Aghaeepour N, Chattopadhyay PK, Gansesan A, O’Neill K, Zare H, Jalali A, Hoos HH, Roederer M & Brinkman RR. Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays. Bioinformatics 28: 1009-1016, 2012.
  27. Aghaeepour N, Jalali A, O’Neill K, Chattopadhyay PK, Roederer M, Hoos HH & Brinkman RR. RchyOptimyx: cellular hierarchy optimization for flow cytometry. Cytometry A 81: 1022-1030, 2012.
  28. Benz C, Copley MR, Kent DG, Wohrer S, Cortes A, Aghaeepour N, Ma E, Mader H, Rowe K, Day C, Treloar D, Brinkman RR & Eaves CJ. Hematopoietic stem cell subtypes expand differentially during development and display distinct lymphopoietic programs.  Cell Stem Cell 10: 273-283, 2012.
  29. Bray C, Spidlen J & Brinkman RR. FCS 3.1 Implementation guidance.  Cytometry A 81: 523-526, 2012.
  30. Cheung AM, Leung D, Rostamirad S, Dhillon K, Miller PH, Droumeva R, Brinkman RR, Hogge D, Roy DC & Eaves CJ. Distinct but phenotypically heterogeneous human cell populations produce rapid recovery of platelets and neutrophils after transplantation.  Blood 119: 3431-3439, 2012.
  31. Spidlen J, Breuer K, Rosenburg C, Kotecha N & Brinkman RR. FlowRepository: a resource of annotated flow cytometry datasets associated with peer-reviewed publications.  Cytometry A 81: 727-731, 2012.
  32. Streitz M, Fuhrmann S, Thomas D, Cheek E, Nomura L, Maecker H, Martus P, Aghaeepour N, Brinkman RR, Volk HD & Kern F. The phenotypic distribution and functional profile of tuberculin-specific CD4 T-cells characterizes different stages of TB infection.  Cytometry B Clin Cytom 82: 360-368, 2012.
  33.  Zare H*, Bashashati A*, Kridel R, Aghaeepour N, Haffari G, Connors JM, Gascoyne RD, Gupta A, Brinkman RR & Weng AP. Automated analysis of multidimensional flow cytometry data improves diagnostic accuracy between mantle cell lymphoma and small lymphocytic lymphoma.  Am J Clin Pathol 137: 75-85, 2012.
  34. Aghaeepour N, Finak G, FlowCAP Consortium, DREAM Consortium, Hoos H, Mosmann TR, Brinkman R*, Gottardo R* & Scheuermann RH*. Critical assessment of automated flow cytometry data analysis techniques.  Nat Methods 10: 228-238, 2013.
  35. Kannan N, Huda N, Tu L, Droumeva R, Aubert G, Chavez E, Brinkman RR, Lansdorp P, Emerman J, Abe S, Eaves C & Gilley D. The luminal progenitor compartment of the normal human mammary gland constitutes a unique site of telomere dysfunction.  Stem Cell Reports 1: 28-37, 2013.
  36. O’Neill K, Aghaeepour N, Spidlen J & Brinkman R. Flow cytometry bioinformatics. PLoS Comput Biol 9: e1003365 2013.
  37. Spidlen J, Barsky A, Breuer K, Carr P, Nazaire MD, Hill BA, Qian Y, Liefeld T, Reich M, Mesirov JP, Wilkinson P, Scheuermann RH, Sekaly RP & Brinkman RR. GenePattern flow cytometry suite. Source Code Biol Med 8: 14 2013.
  38. Villanova F, Di Meglio P, Inokuma M, Aghaeepour N, Perucha E, Mollon J, Nomura L, Hernandez-Fuentes M, Cope A, Prevost AT, Heck S, Maino V, Lord G, Brinkman RR & Nestle FO. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery. PLoS One 8: e65485 2013.
  39. Zare H, Haffari G, Gupta A & Brinkman RR. Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis. BMC Genomics 14: doi: 10.1186/1471-2164-14-S1-S14 2013.
  40. Craig FE, Brinkman R, Ten Eyck S & Aghaeepour N. Computational analysis optimizes the flow cytometric evaluation for lymphoma. Cytometry B Clin Cytom 86: 18-24, 2014.
  41. Johnstone J, Parsons R, Botelho F, Millar J, McNeil S, Fulop T, McElhaney J, Andrew MK, Walter SD, Devereaux PJ, Malekesmaeili M, Brinkman RR, Mahony J, Bramson J & Loeb M. Immune biomarkers predictive of respiratory viral infection in elderly nursing home residents. PLoS One 9: e108481 2014.
  42. O’Neill K, Jalali A, Aghaeepour N, Hoos H & Brinkman RR. Enhanced flowType/RchyOptimyx: A BioConductor pipeline for discovery in high-dimensional cytometry data. Bioinformatics 30: 1329-1330, 2014.
  43. Von Rossum A, Enns W, Shi YP, MacEwan GE, Malekesmaeili M, Brinkman R & Choy JC. Bim regulates alloimmune-mediated vascular injury through effects on T-cell activation and death. Arterioscler Thromb Vasc Biol 34: 1290-1297, 2014.
  44. Spidlen J, Bray C, ISAC Data Standards Task Force & Brinkman RR. ISAC’s classification results file format. Cytometry A 87: 86-88, 2015.
  45. Malek M, Taghiyar MJ, Chong L, Finak G, Gottardo R & Brinkman RR. flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification. Bioinformatics 31: 606-7, 2015.
  46. Courtot M, Meskas J, Diehl AD, Droumeva R, Gottardo R, Jalali A, Taghiyar MJ, Maecker HT, McCoy JP, Ruttenberg A, Scheuermann RH & Brinkman RR. flowCL: ontology-based cell population labeling in flow cytometry. Bioinformatics 31:1337-9, 2015.
  47. Kvistborg P, Gouttefangeas C, Aghaeepour N, Cazaly A, Chattopadhyay PK, Eckl J, Ferrari G, Finak G, Hadrup SR, Maecker HT, Maurer D, Mosman, T, Qiu P, Scheuermann RH, Marij JPM, Brinkman RR*, Britten CM*. Thinking Outside the Gate: Immune assessments in multiple dimensions. Immunity. 42:591-2, 2015.
  48. O’Neill K, Aghaeepour N, Hogge D, Karsan A, Dalal B, Brinkman R. Deep profiling of multitube flow cytometry data. Bioinformatics 31:1623-31, 2015
  49. Spidlen J, Moore W, ISAC Data Standards Task Force and Brinkman RR. ISAC’s Gating-ML 2.0 data exchange standard for gating description. Cytometry A. 87(7):683-7, 2015.
  50. Aghaeepour N, Chattopadhyay P, Chikina M, Dhaene T,Van Gassen S, Kursa M, Lambrecht BN, Malek M, Qian Y, Qiu P, Saeys Y, Stanton S, Tong D, Vens C, Walkowiak S, Wang S, Finak G, Gottardo R, Mosmann T, Nolan G, Scheuermann RH, Brinkman RR.  A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes. Cytometry A. 89 (1): 16-21, 2016.
  51. Finak G, Langweiller M, Jaimes M, Malek M, Taghiyar J, Korin Y, Raddassi K, Devine L, Obermoser G, Pekalski ML, Pontikos N, Diaz A, Heck S, Villanova F, Terrazzini N, Kern F, Qian Y, Stanton R, Wang K, Brandes A, Ramey J, Aghaeepour N, Mosmann T,  Scheuermann RH, Reed E, Palucka K, Pascual V, Blomberg BB, Nestle F, Nussenblatt RB, Brinkman RR, Gottardo R, Maecker H, McCoy JP. Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium. Sci Rep. 10;6:20686, 2016.
  52. Brinkman RR,Aghaeepour N, Finak G, Gottardo R, Mosmann T, Scheuermann RH. Automated analysis of flow cytometry data comes of age. Cytometry A. 89(1):13-5, 2016.
  53. O’Neill K, Brinkman RR. Publishing code is essential for reproducible flow cytometry bioinformatics. Cytometry A. 89(1): 10-1, 2016.
  54. Fletez-Brant K, Spidlen J, Brinkman RR, Roederer M, Chattopadhyay PK. flowClean: Automated identification and removal of fluorescence anomalies in flow cytometry data. Cytometry A. 89(5):461-71, 2016.
  55. Johnstone J, Parsons R, Botelho F, Millar J, McNeil S, Fulop T, McElhaney J, Andrew MK, Walter SD, Devereaux PJ, Malek M, Brinkman R, Bramson J, Loeb M.  T-cell Phenotypes Predictive of Frailty and Mortality in Elderly Nursing Home Residents.  J Am Geriatr Soc Jan;65(1):153-159, 2017.
  56. Parks  DR, El Khettabi F, Chase  E , Hoffman RA, Perfetto SP, Spidlen J, Wood JCS , Moore WA, Brinkman RR. Evaluating Flow Cytometer Performance With Weighted Quadratic Least Squares Analysis of LED and Multi-Level Bead Data. Cytometry A 91 (3), 232-249.
  57. Cossarizza A, Chang HD, Radbruch A, Andrä I, Annunziato F, Bacher P, Barnaba V, Battistini L, Bauer WM, Baumgart S, Becher B1, Beisker W, Berek C, Blanco A, Borsellino G, Boulais PE, Brinkman RR, Büscher M, Busch DH, Bushnell TP, Cao X, Cavani A, Chattopadhyay PK, Cheng Q, Chow S, Clerici M, Cooke A, Cosma A, Cosmi L, Cumano A, Dang VD, Davies D, De Biasi S, Del Zotto G, Della Bella S,, Dellabona P, Deniz G, Dessing M, Diefenbach A, Di Santo J, Dieli F, Dolf A, Donnenberg VS, Dörner T, Ehrhardt GRA, Endl E, Engel P, Engelhardt B, Esser C, Everts B, Falk CS,, Fehniger TA, Filby A, Fillatreau S,,, Follo M, Förster I, Foster J, Foulds GA, Frenette PS,, Galbraith D, Garbi N,, García-Godoy MD, Ghoreschi K, Gibellini L, Goettlinger C, Goodyear CS, Gori A, Grogan J, Gross M, Grützkau A, Grummitt D, Hahn J, Hammer Q, Hauser AE,, Haviland DL, Hedley D, Herrera G, Herrmann M, Hiepe F, Holland T, Hombrink P, Houston JP, Hoyer BF, Huang B,,, Hunter CA, Iannone A, Jäck HM, Jávega B, Jonjic S,, Juelke K, Jung S, Kaiser T, Kalina T, Keller B, Khan S, Kienhöfer D, Kroneis T, Kunkel D, Kurts C, Kvistborg P, Lannigan J, Lantz O,,, Larbi A,,,, LeibundGut-Landmann S, Leipold MD, Levings MK, Litwin V, Liu Y, Lohoff M, Lombardi G, Lopez L, Lovett-Racke A, Lubberts E, Ludewig B, Lugli E,, Maecker HT, Martrus G, Matarese G, Maueröder C, McGrath M, McInnes I, Mei HE, Melchers F, Melzer S, Mielenz D, Mills K, Mjösberg J,, Moore J, Moran B, Moretta A,, Moretta L, Mosmann TR, Müller S, Müller W, Münz C, Multhoff G,, Munoz LE, Murphy KM,, Nakayama T, Nasi M, Neudörfl C, Nolan J, Nourshargh S, O’Connor JE, Ouyang W, Oxenius A, Palankar R, Panse I, Peterson P, Peth C, Petriz J, Philips D, Pickl W, Piconese S,, Pinti M, Pockley AG,, Podolska MJ, Pucillo C, Quataert SA, Radstake TRDJ, Rajwa B, Rebhahn JA, Recktenwald D, Remmerswaal EBM, Rezvani K, Rico LG, Robinson JP, Romagnani C, Rubartelli A, Ruland J,,, Sakaguchi S,, Sala-de-Oyanguren F, Samstag Y, Sanderson S, Sawitzki B,, Scheffold A,, Schiemann M, Schildberg F, Schimisky E, Schmid SA, Schmitt S, Schober K, Schüler T, Schulz AR, Schumacher T, Scotta C, Shankey TV, Shemer A, Simon AK, Spidlen J, Stall AM, Stark R, Stehle C, Stein M, Steinmetz T, Stockinger H, Takahama Y, Tarnok A,, Tian Z,, Toldi G, Tornack J, Traggiai E, Trotter J, Ulrich H, van der Braber M, van Lier RAW, Veldhoen M, Vento-Asturias S, Vieira P, Voehringer D, Volk HD, von Volkmann K, Waisman A, Walker R, Ward MD, Warnatz K, Warth S, Watson JV, Watzl C, Wegener L, Wiedemann A, Wienands J, Willimsky G, Wing J,, Wurst P, Yu L, Yue A, Zhang Q, Zhao Y, Ziegler S, Zimmermann J. Guidelines for the use of flow cytometry and cell sorting in immunological studies.  2017 Oct;47(10):1584-1797.