Principal Investigators


Dr. Ryan Brinkman — PhD

Distinguished Scientist

Research Interest
Lab Members
  • Professor, Medical Genetics, University of British Columbia
  • Associate Faculty Member, Bioinformatics Centre, University of British Columbia
  • Faculty Member, Bioinformatics Training Program, CIHR/MSFHR
  • Associate Faculty Member, British Columbia Genome Sciences Centre
  • Adjunct Faculty, Molecular Biology and Biochemistry, Simon Fraser University
  • Adjunct Faculty, School of Computing Science, Simon Fraser University
  • CEO, Cytapex Bioinformatics Inc.


  • B.SC (Honours), Biology and Biotechnology, Carleton University, 1992
  • PhD, Genetics, University of British Columbia, 2001

Open Positions

Big Data Genome Studies

A graduate student position is available for students interested in pursuing MSc or Phd studies in Bioinformatics at the University of British Columbia. The project is aimed at characterizing the function of every mammalian gene through thorough analysis of every known and predicted gene in the mouse genome via “Big Data” analysis. To address this critical gap in biomedical research, the International Mouse Phenotyping Consortium was created to generate a null mutation for every gene in the mouse genome, to collect phenotypic data for each mutation, and to disseminate the data to the broader scientific community. Immunophenotyping by flow cytometry (FCM), is one of the 30 core phenotyping assays of this global effort. However, the full quantitative potential of the IMPC FCM effort can only be realized with mechanisms to effectively share, analyze and interpret the data.

The selected candidate will develop and use state-of-the-art computational methodologies for supervised and unsupervised clustering and classification to systematically analyze tens of thousands of high-dimensional samples to help understand the function of each gene. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.

Qualifications: The ideal candidate will have a strong background in Computational Biology, Bioinformatics, or equivalent with strong experience in handling high-throughput data sets as well as statistics and programming skills (we love R here). The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.
In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in Vancouver.
Please contact Dr. Brinkman directly at and provide the following information:

– Short cover letter explaining your interest in the lab
– Resume
– Scanned copy of transcript or listing of course grades
– Names and contact information for two individuals who will be willing to provide letters of reference

Flow Cytometry Bioinformatics

My group is focused on applying bioinformatics techniques to flow cytometry data. Flow cytometry is a technique that is widely used within the biomedical community. New high throughput methods can generate up to a thousand flow cytometry data files per day and each data file can consist of millions of multiparametric descriptions of individual cells. However flow cytometry lacks data standards for fully representing both the methods used and the data generated, hindering the handling, exchange and dissemination of scientific research. Consequently, there are a variety of challenges to archiving, analyzing and reporting the results of high throughput flow cytometry experiments. Furthermore, only rudimentary bioinformatics tools exist to manage and mine high throughput data. We are leading an international effort to develop a systemic approach to modeling, capturing, analyzing and disseminating flow cytometry data. Initial work is focused on developing a community-based standard for recording and reporting flow cytometry data. Software implementations of this standard (UML, XML, SQL, Java) and an ontology (Ontology for Biomedical Investigations) being created to facilitate data exchange between both software components and collaborative groups. Statistics packages (e.g., flowCore/flowUtils/flowClust) are also being developed to allow users to implement analyses in a high throughput fashion, as well as exchange these analyses in more meaningful ways then are currently available. We are also testing our high throughput analysis methods to analyze flow cytometry data on datasets from the British Columbia Cancer Agency and the British Children's Hospital including developing methods for the high throughput analysis of lymphoma, Graft versus Host Disease and innate immunity. Some of these data sets are also available as part of the flowCAP project. We are also developing user-friendly software that implements some of the new data analysis and visualization methods we and others have developed.

My research is supported by the NIH, CIHR, Genome Canada, Genome BC, The Michael Smith Foundation for Health Research and the BC Cancer Agency.

See complete Publication List here:   Researcher ID or ORCID


Czechowska K, Lannigan J, Wang L, Arcidiacono J, Ashhurst TM, Barnard RM, Bauer S, Bispo C, Bonilla DL, Brinkman RR, Cabanski M, Chang HD, Chakrabarti L, Chojnowski G, Cotleur B, Degheidy H, Dela Cruz GV, Eck S, Elliott J, Errington R, Filby A, Gagnon D, Gardner R, Green C, Gregory M, Groves CJ, Hall C, Hammes F, Hedrick M, Hoffman R, Icha J, Ivaska J, Jenner DC, Jones D, Kerckhof FM, Kukat C, Lanham D, Leavesley S, Lee M, Lin-Gibson S, Litwin V, Liu Y, Molloy J, Moore JS, Muller S, Nedbal J, Niesner R, Nitta N, Ohlsson-Wilhelm B, Paul NE, Perfetto S, Portat Z, Props R, Radtke S, Rayanki R, Rieger A, Rogers S, Rubbens P, Salomon R, Schiemann M, Sharpe J, Sonder SU, Stewart JJ, Sun Y, Ulrich H, Van Isterdael G, Vitaliti A, van Vreden C, Weber M, Zimmermann J, Vacca G, Wallace P & Tarnok A. Cyt-Geist: Current and Future Challenges in Cytometry: Reports of the CYTO 2018 Conference Workshops. Cytometry A 95:598-644, 2019. View Publication (Free Access)

Wang S, Brinkman RR. Data-Driven Flow Cytometry Analysis. Methods Mol Biol 1989:245-265, 2019. View Abstract

Montante S, Brinkman RR. Flow cytometry data analysis: Recent tools and algorithms International Journal of Laboratory Hematology 41: 56-62, 2019. View Abstract

Conrad VK, Dubay CJ, Malek M, Brinkman RR, Koguchi Y & Redmond WL. Implementation and Validation of an Automated Flow Cytometry Analysis Pipeline for Human Immune Profiling. Cytometry Part A 95:183-191, 2019. View Abstract

Lee AH§, Shannon C§, Amenyogbe N§, Bennike TB§, Diray-Arce J§, Idoko O, Gill EE, Ben-Othman R*, Pomat WS, van Haren S, Lê Cao K-A, Cox M, Darboe A, Falsafi R, Ferrari D, Harbeson D, He D, Bing C, Hinshaw SH, Ndure J, Njie-Jobe J, Pettengill MA, Richmond PC, Ford R, Saleu G, Masiria G, Matlam JP, Kirarock W, Roberts E, Malek M, Sanchez-Schmitz G, Singh A, Angelidou A, Smolen KK, the EPIC Consortium, Brinkman RR, Ozonoff A, Hancock R, van den Biggelaar AHJ, Steen H*, Tebbutt SJ*, Kampmann B*, Levy O* & Kollmann TR*. Dynamic molecular changes during the first week of human life follow a robust developmental trajectory. Nature Communications 10:1092, 2019. View Publication (Free PMC Article)
§ Co-first authors; *Co-senior authors

Tighe RM, Redente EF, Yu Y-R, Herold S, Sperling A, Curtis J, Duggan R, Swaminathan S, Nakano H, Zacharias W, Janssen W, Freeman C, Brinkman R, Singer BD, Jakubzick CV, and Misharin AV on behalf of the ATS Assembly on Allergy Immunology and Inflammation. An Official American Thoracic Society Workshop Report: Improving the Quality and Reproducibility of Flow Cytometry in the Lung. Annals of the American Thoracic Society 2019. (In revision, Mar 2019)


Ivison S, Malek M, Garcia RV, Broady R, Halpin A, Richaud M, Brant RF, Wang SI, Goupil M, Guan Q, Ashton P, Warren J, Rajab A, Urschel S, Kumar D, Streitz M, Sawitzki B, Schlickeiser S, Bijl JJ, Wall DA, Delisle JS, West LJ, Brinkman RR & Levings MK. A standardized immune phenotyping and automated data analysis platform for multicenter biomarker studies. JCI Insight 3(23):e121867, 2018. View Publication (Open Access)

Parks D, Moore W, Brinkman RR, Chen Y, Condello D, El Khettabi F, Molan JP, Perfetto SP, Redelman D, Spidlen J, Van Dyke J, Wang L & Wood JCS. Methodology for evaluating and comparing fluorescence measurement capabilities: Multi-site study of 23 flow cytometers. Cytometry A 93(11):1087-1091, 2018. View Abstract

Rahim A, Meskas J, Drissler S, Yue A, Lorenc A, Laing A, Saran N, White J, Abeler-Dorner L, Hayday A & Brinkman RR. High Throughput Automated Analysis of Big Flow Cytometry Data. Methods 134-135:164-76, 2018. View Publication (Free PMC Article)

Lux M, Brinkman RR, Chauve C, Laing A, Lorenc A, Abeler-Dorner L & Hammer B. flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics 34:2245-53, 2018. View Publication (Free PMC Article)

Brink BG, Meskas J, Brinkman RR. ddPCRclust - An R package and Shiny app for automated analysis of multiplexed ddPCR data. Bioinformatics 34:2687-89, 2018. View Publication (Free PMC Article)

Spidlen J & Brinkman RR. Use FlowRepository to share your clinical data upon study publication. Cytometry B Clinical Cytometry 94(1):196-98, 2018. View Abstract


Cossarizza A, Chang HD, Radbruch A, Andra I, ... Brinkman RR, ... Yue A, Zhang Q, Zhao Y, Ziegler S & Zimmermann J. Guidelines for the use of flow cytometry and cell sorting in immunological studies. Eur J Immunol 47:1584-1797, 2017. View Publication (Free Article)

Parks DR, El Khettabi F, ChaseE, HoffmanRA, Perfetto SP, Spidlen J, Wood JC, 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, 2017 . View Publication (Free PMC Article)

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 65(1):153-159, 2017. View Abstract


Bandrowski A, Brinkman R, Brochhausen M, Brush MH, Bug B, Chibucos MC, Clancy K, Courtot M, Derom D, Dumontier M, Fan L, Fostel J,Fragoso G, Gibson F, Gonzalez-Beltran A, Haendel MA, He Y, Heiskanen M, Hernandez-Boussard T, Jensen M, Lin Y, Lister AL, Lord P, Malone J, Manduchi E, McGee M, Morrison N, Overton JA, Parkinson H, Peters B, Rocca-Serra P, Ruttenberg A, Sansone SA, Scheuermann RH, Schober D, Smith B, Soldatova LN, Stoeckert CJ Jr, Taylor CF, Torniai C, Turner JA, Vita R, Whetzel PL, Zheng J. The Ontology for Biomedical Investigations. PLos One. 1(4):e0154556, 2016. View Publication (Free PMC Article)

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): 461-471,2016 . View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free Article)

O’Neill K, Brinkman RR. Publishing code is essential for reproducible flow cytometry bioinformatics. Cytometry A. 89(1): 10-1, 2016. View Publication (Free Article)


Brinkman RR Aghaeepour N, Finak G, Gottardo R, Mosmann T, Scheuermann RH. State-of-the-Art in the Computational Analysis of Cytometry Data. Cytometry A 87:591-3, 2015. View Publication (Free Full Text)

Spidlen J, Bray C, ISAC Data Standards Task Force & Brinkman RR. ISAC's classification results file format. Cytometry A 87: 86-88, 2015. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)

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. View Publication (Free PMC Article)


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. View Publication (Free PMC Article)

Rothe K, Lin KBL, Lin H, Leung A, Wang HM, Malekesmaeili M, Brinkman RR, Forrest DL, Gorski SM & Jiang X.  The core autophagy protein ATG4B as a potential biomarker and therapeutic target in CML stem/progenitor cells. Blood.123(23) 3622-34, 2014. View Publication (Free Full Text)

Craig F, Brinkman RR, Ten Eyck S, Aghaeepour N. Computational Analysis Optimizes the Flow Cytometric Evaluation for Lymphoma. Cytometry B. 86:18-24, 2014. View Publication (Free Full Text)

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 View Publication (Free PMC Article)

von Rossum A, Enns W, Shi Y, MacEwan G, Malekesmaeli M, Brinkman R, Choy J. Bim Regulates Alloimmune-Mediated Vascular Injury Through Effects on T Cell Activation and Death. Arterioscler Thromb Vasc Biol 34:1290-1297, 2014. View Publication (Free PMC Article)

Courtot M, Brinkman R, Ruttenberg A. The logic of surveillance guidelines: An analysis of vaccine adverse event reports from an ontological perspective. PLoS ONE. 9(3): e92632, 2014 View Publication (Free PMC Article)


O'Neill K, Aghaeepour N, Spidlen J & Brinkman R. Flow cytometry bioinformatics.  PLoS Comput Biol. PLoS Comput Biol (12):e1003365, 2013. View Publication (Free PMC Article)

Craig F, Brinkman R, Ten Eyck S, Aghaeepour N. Computational Analysis Optimizes the Flow Cytometric Evaluation for Lymphoma.Cytometry B. 86:18-24, 2013. View Abstract

Hills M, O'Neill K, Falconer E, Brinkman R & Lansdorp PM. BAIT: Organizing genomes and mapping rearrangements in single cells.Genomic Med. 5:82, 2013. View Publication (Free PMC Article)

Kannan N, Huda N, Tu LR, Droumeva R, Brinkman RR, Emerman J, Abe S, Eaves C, Gilley D. Luminal mammary progenitors are a unique site of telomere dysfunction. Stem Cell Reports 1:28-37, 2013. View Abstract

Spidlen J, Barsky A, Angermann B, Wilkinson P, Breuer K ,Png A, Cortes A,  Carr P, Liefeld T, Reich M, Nazaire, M-D, Eaves CJ,  Mesirov JP , Sekaly RP, Brinkman RR.  GenePattern Flow Cytometry Suite. Source Code for Biology and Medicine. 8:14, 2013. View Publication (Free PMC Article)

Villanovaa F, Di Meglio P, Inokumad  M, Aghaeepour N, Esperanza P, Mollong J, Nomurad L, Hernandez-Fuentesb M, Copeh  A, Prevosti AT, Heck S, Mainod 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. View Publication (Free PMC Article)

Aghaeepour N, Finak G, The FlowCap Consortium, The Dream Consortium, Hoos H, Mosmann TR, Gottardo R, Brinkman RR*, Scheuermann RH. Critical assessment of automated flow cytometry analysis techniques. Nature Methods 10: 228-38, 2013. View Publication (Free PMC Article)

Zare H, Gholamreza Haffari, G, Gupta, A, Brinkman RR. Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis. BMC Genomics 14 Suppl 1: S14, 2013. View Publication (Free PMC Article)

65. 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. View Publication (Free PMC Article)


Streitz M, Fuhrmann S, Thomas D, Cheek E, Nomura L, Maecker H, Martus P, Aghaeepour N, Brinkman RR, Volk H-D, Kern F. The phenotypic distribution and functional profile of Tuberculin-specific CD4 T-cells characterizes different stages of TB infections. Cytometry B Clin Cytom 82: 360-368, 2012. View Abstract

Aghaeepour N, Jalali A, O'Neill K, Chattopadhyay PK, Roederer M, HoosHH,  Brinkman RR. RchyOptimyx: cellular hierarchy optimization for flow cytometry. Cytometry A 81: 1022-1030, 2012. View Publication (Free PMC Article)

Streitz M, Fuhrmann S, Thomas D, Cheek E, Nomura L, Maecker H, Martus P, Aghaeepour N, Brinkman RR, Volk H-D, Kern F. The phenotypic distribution and functional profile of Tuberculin-specific CD4 T-cells characterizes different stages of TB infections. Cytometry B Clin Cytom 82: 360-368, 2012.  View Abstract

Spidlen J, Breuer K, Rosenberg C, Kotecha N, Brinkman RR. FlowRepository: A resource of annotated flow cytometry datasets associated with peer-reviewed publications. Cytometry A 81: 727-731, 2012. View Abstract

Spidlen J, Breuer K & Brinkman R. Preparing a Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) compliant manuscript using the International Society for Advancement of Cytometry (ISAC) FCS file repository ( In: Current Protocols in Cytometry 10:10.18, 2012. View Abstract

Cheung AMS, 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 post-transplant. Blood 119: 3431-3439, 2012. View Abstract

Benz C, Copley MR, Kent DG, Wohrer S, Cortes A,  Aghaeepour N, Ma E, Mader H, Rowe K, Day C, Treloar DD, Brinkman RR & Eaves CJ. Hematopoietic stem cell subtypes expand differentially during development and display distinct lymphopoietic programs. Cell Stem Cell 10: 273-283, 2012. View Abstract

Bray C, Spidlen J & Brinkman RR. FCS 3.1 implementation guidance.Cytometry A 77A: 97100, 201, 2012. View Abstract

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 10: 1009-1016, 2012. View Abstract

Bashashati A, Johnson NA, Khodabakhshi AH, Whiteside MD, Zare H, Scott DW, Lo K, Gottardo R, Brinkman FSL, Connors JM, Slack GW, Gascoyne RD, Weng AP* & Brinkman RR* (*co-senior authors). B-cells with high side scatter parameter by flow cytometry correlate with inferior survival in diffuse large B cell lymphoma. Am J Clin Pathol 137: 705-814, 2012. View Abstract

Zare H, Bashashati A, Kridel R, Aghaeepour N, Haffari G, Connors HM, Gupta A, Gascoyne RD, Brinkman RR* & Weng AP* (*co-senior authors). 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. View Abstract


Spidlen J, Shooshtari P, Kollmann TR, Brinkman RR. Flow cytometry data standards. BMC Res Research Notes. 4: 50, 2011. View Abstract

Aghaeepour N, Nikolic R, Hoos HH, Brinkman RR. Rapid cell population identification in flow cytometry. Cytometry A. 79(1):6-13, 2011. View Abstract


Zare H, Shooshtari P, Gupta A, Brinkman RR. Data reduction for spectral clustering to analyze high throughput flow cytometry data. BMC Bioinformatics. 11(1): 403, 2010. View Abstract

Shooshtari P, Fortuno ES 3rd, Blimkie D, Yu M, Gupta A, Kollmann T,Brinkman RR. Correlation Analysis of Culture Supernatant Response and Functional Response of Antigen Presenting Cells Using the Generalized Integrated Mean Fluorescence Intensity. Cytometry A. 77(9):873-880,2010. View Abstract

Brinkman RR, Courtot M, Derom D, Fostel JM, He Y, Lord P, Malone J, Parkinson H, Peters B, Rocca-Serra P, Ruttenberg A, Sansone SA, Soldatova LN, Stoeckert CJ Jr, Turner JA, Zheng J; OBI consortium. Modeling biomedical experimental processes with OBI. J Biomed Semantics. Jun 22;1 Suppl 1:S7, 2010. View Abstract

Xiang Z., Courtot M, Brinkman RR, Ruttenberg A. and He Y. OntoFox: web-based support for ontology reuse. BMC Research Notes. 3(1): 175, 2010. View Abstract

Jiang X, Forrest D, Nicolini F, Turhan A, Guilhot F, 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. View Abstract

Blimkie D, Fortuno ES 3rd, Thommai F, Xu L, Fernandes E, Crabtree J, Rein-Weston A, Jansen K, , Kollmann TR, Brinkman RR. Identification of B cells through negative gating-An example of the MIFlowCyt standard applied. Cytometry A. 77(6): 546 – 551, 2010. View Abstract

Spidlen J, Moore W, Parks D, Goldberg M, Bierre P, Bray C, Gorombey P, Hyun B, Hubbard M, Lange S, Lefebvre R,  Leif R, Novo D, Ostruszka L,  Treister 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(1): 97-100, 2010. View Abstract

Hahne F, Khodabakhshi AH,  Bashashati A, Wong C-J, Gascoyne RD, . Weng AP, Seifert-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. View Abstract


Strain E, Hahne F, Brinkman RR & Haaland P. Analysis of high throughput flow cytometry data using plateCore.  Adv Bioinformatics 2009: 1-10, 2009. View Abstract

Qian Y*, Tchuvatkina O*, Spidlen J, Wilkinson P, Gasparetto M, Jones AR, Manion FJ, Scheuermann RH,  Sekaly R-P,  Brinkman RR.FuGEFlow: data model and markup language for flow cytometry. BMC Bioinformatics 10:184, 2009. View Abstract

Vercauteren S, Bashashati A; Wu D; Brinkman R; Eaves C, Eaves A, Karsten A. Reduction in multilineage and erythroid progenitors distinguishes myelodysplastic syndromes from non-malignant cytopeniasLeukemia Research 33 (12):1636-42, 2009. View Abstract

Lo K, Hahne F, Brinkman RR, Gottardo R. flowClust: a Bioconductor package for automated gating of flow cytometry data. BMC Bioinformatics10(1): 145, 2009. View Abstract

Forrest DL, Trainor S, Brinkman RR, Barnett MJ, Hogge DE, Nevill TJ, Shepherd JD, Nantel SH, Toze CL, Sutherland HJ, Song KW, Lavoie JC, Power MM, Abou-Mourad Y, & Smith CA. Cytogenetic and molecular responses to standard-dose imatinib in chronic myeloid leukemia are correlated with Sokal risk scores and duration of therapy but not trough imatinib plasma levels. Leuk Res 33(2):271-5, 2009. View Abstract

Forrest DL, Trainor S, Brinkman RR, Barnett MJ, Hogge DE, Nevill TJ, Shepherd JD, Nantel SH, Toze CL, Sutherland HJ, Song KW, Lavoie JC, Power MM, Abou-Mourad Y, Smith CA.  Correlation between trough imatinib plasma concentration and clinical response in chronic myeloid leukemia.  Leukemia Research 33(8):1149-50, 2009. View Abstract

Hahne F, Le Meur N, Brinkman RR, Ellis B, Haaland P, Sarkar D, Spidlen J, Strain E, Gentleman R.  flowCore: a Bioconductor package for high throughput flow cytometry.  BMC Bioinformatics 10(1): 106, 2009.View Abstract


Johnson NA, Boyle M, Bashashati A, Leach S, Brooks-Wilson A, Sehn LH, Chhanabhai M, Brinkman RR, Connors JM, Weng AP, Gascoyne. Diffuse large B cell lymphoma: reduced CD20 expression is associated with an inferior survival. Blood 113(16): 3773-3780 2008.  View Abstract

Lee JA, Spidlen J, Boyce K, Cai J, Crosbie N, Dalphin M, 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, Scheuermann RH, & Brinkman RR. MIFlowCyt: the minimum information about a Flow Cytometry Experiment. Cytometry A 73 (10): 926-30, 2008.View Abstract

Lo K, Brinkman RR, & Gottardo R. Automated gating of flow cytometry data via robust model-based clustering. Cytometry A 73 (4): 321-32, 2008.View Abstract

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, 2008. View Abstract

Spidlen J, Leif RC, Moore W, Roederer M, & Brinkman RR. Gating-ML: XML-based gating descriptions in flow cytometry. Cytometry A, 2008.View Abstract

Taylor CF, Field D, Sansone SA, Aerts J, Apweiler R, Ashburner M, Ball CA, Binz PA, Bogue M, Booth T, Brazma A, Brinkman RR, Michael Clark A, Deutsch EW, Fiehn O, Fostel J, Ghazal P, Gibson F, Gray T, Grimes G, Hancock JM, Hardy NW, Hermjakob H, Julian RK, Jr., Kane M, Kettner C, Kinsinger C, Kolker E, Kuiper M, Novere NL, Leebens-Mack J, Lewis SE, Lord P, Mallon AM, Marthandan N, Masuya H, McNally R, Mehrle A, Morrison N, Orchard S, Quackenbush J, Reecy JM, Robertson DG, Rocca-Serra P, Rodriguez H, Rosenfelder H, Santoyo-Lopez J, Scheuermann RH, Schober D, Smith B, Snape J, Stoeckert CJ, Jr., Tipton K, Sterk P, Untergasser A, Vandesompele J, & Wiemann S. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26 (8): 889-96, 2008.View Abstract


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 (6): 691-700, 2007. View Abstract

Dykstra B, Kent D, Bowie M, McCaffrey L, Hamilton M, Lyons K, Lee SJ,Brinkman R, & Eaves C. Long-term propagation of distinct hematopoietic differentiation programs in vivo. Cell Stem Cell 1 (2): 218-29, 2007. View Abstract

Le Meur N, Rossini A, Gasparetto M, Smith C, Brinkman RR, & Gentleman R. Data quality assessment of ungated flow cytometry data in high throughput experiments. Cytometry A 71 (6): 393-403, 2007. View Abstract


Brinkman RR, Dube MP, Rouleau GA, Orr AC, & Samuels ME. Human monogenic disorders - a source of novel drug targets. Nat Rev Genet 7 (4): 249-60, 2006. View Abstract

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 (2): 209-14, 2006. View Abstract

Stoeckert C, Ball C, Brazma A, Brinkman R, Causton H, Fan L, Fostel J, Fragoso G, Heiskanen M, Holstege F, Morrison N, Parkinson H, Quackenbush J, Rocca-Serra P, Sansone SA, Sarkans U, Sherlock G, Stevens R, Taylor C, Taylor R, Whetzel P, & White J. Wrestling with SUMO and bio-ontologies. Nat Biotechnol 24 (1): 21-2; author reply 23, 2006. View Abstract

Whetzel PL, Brinkman RR, Causton HC, Fan L, Fostel J, Fragoso G, Heiskanen M, Hernandez-Boussard T, Morrison N, Parkinson H, Rocco-Serra P, Sansone SA, Schober D, Smith B, Stevens R, Stoeckert CJ, Jr., Taylor C, White J, & Wood A. Development of FuGO: an ontology for functional genomics investigations. Omics 10 (2): 199-204, 2006. View Abstract


Whetzel PL, Brinkman RR, Causton HC, Fan L, Field D, Fostel J, Fragoso G, Gray T, Heiskanen M, Hernandez-Boussard T, Morrison N, Parkinson H, Rocca-Serra P, Djousse L, Knowlton B, Hayden MR, Almqvist EW, Brinkman RR, Ross CA, Margolis RL, Rosenblatt A, Durr A, Dode C, Morrison PJ, Novelletto A, Frontali M, Trent RJ, McCusker E, Gomez-Tortosa E, Mayo Cabrero D, Jones R, Zanko A, Nance M, Abramson RK, Suchowersky O, Paulsen JS, Harrison MB, Yang Q, Cupples LA, Mysore J, Gusella JF, MacDonald ME, & Myers RH. Evidence for a modifier of onset age in Huntington disease linked to the HD gene in 4p16. Neurogenetics 5 (2): 109-14, 2004. View Abstract

Djousse L, Knowlton B, Hayden M, Almqvist EW, Brinkman R, Ross CA, Margolis R, Rosenblatt A, Durr A, Dode C, Morrison PJ, Novelletto A, Frontali M, Trent RJA, McCusker E, Gomez-Tortosa E, Mayo D, Jones R, Zanko A, Nance M, Abramson R, Suchowersky O, Paulsen J, Harrison M, Yang Q, Cupples LA, Mysore J, Gusella JF, MacDonald ME, and Nyers RH.  Evidence for a Modifier of Onset Age in Huntington’s Disease Linked to the HD Gene in 4p16.  Neurogenetics 5(2): 109-14, 2004. View Abstract

Lafreniere RG, MacDonald ML, Dube MP, MacFarlane J, O’Driscoll M, Brais B, Meilleur S, Brinkman RR, Dadivas O, Pape T, Platon C, Radomski C, Risler J, Thompson J, Guerra-Escobio AM, Davar G, Breakefield XO, Pimstone SN, Green R, Pryse-Phillips W, Goldberg YP, Younghusband HB, Hayden MR, Sherrington R, Rouleau GA, & Samuels ME. Identification of a novel gene (HSN2) causing hereditary sensory and autonomic neuropathy type II through the Study of Canadian Genetic Isolates. Am J Hum Genet 74 (5): 1064-73, 2004. View Abstract

Langbehn DR, Brinkman RR, Falush D, Paulsen JS, & Hayden MR. A new model for prediction of the age of onset and penetrance for Huntington’s disease based on CAG length. Clin Genet 65 (4): 267-77, 2004. View Abstract


Almqvist EW, Brinkman RR, Wiggins S, & Hayden MR. Psychological consequences and predictors of adverse events in the first 5 years after predictive testing for Huntington’s disease. Clin Genet 64 (4): 300-9, 2003.View Abstract

Djousse L, Knowlton B, Hayden M, Almqvist EW, Brinkman R, Ross C, Margolis R, Rosenblatt A, Durr A, Dode C, Morrison PJ, Novelletto A, Frontali M, Trent RJ, McCusker E, Gomez-Tortosa E, Mayo D, Jones R, Zanko A, Nance M, Abramson R, Suchowersky O, Paulsen J, Harrison M, Yang Q, Cupples LA, Gusella JF, MacDonald ME, & Myers RH. Interaction of normal and expanded CAG repeat sizes influences age at onset of Huntington disease. Am J Med Genet A 119A (3): 279-82, 2003.View Abstract

Li JL, Hayden MR, Almqvist EW, Brinkman RR, Durr A, Dode C, Morrison PJ, Suchowersky O, Ross CA, Margolis RL, Rosenblatt A, Gomez-Tortosa E, Cabrero DM, Novelletto A, Frontali M, Nance M, Trent RJ, McCusker E, Jones R, Paulsen JS, Harrison M, Zanko A, Abramson RK, Russ AL, Knowlton B, Djousse L, Mysore JS, Tariot S, Gusella MF, Wheeler VC, Atwood LD, Cupples LA, Saint-Hilaire M, Cha JH, Hersch SM, Koroshetz WJ, Gusella JF, MacDonald ME, & Myers RH. A genome scan for modifiers of age at onset in Huntington disease: The HD MAPSstudy. Am J Hum Genet 73 (3): 682-7, 2003. View Abstract


Paulsen JS, Zhao H, Stout JC, Brinkman RR, Guttman M, Ross CA, Como P, Manning C, Hayden MR, & Shoulson I. Clinical markers of early disease in persons near onset of Huntington’s disease. Neurology 57 (4): 658-62, 2001. View Abstract

Rosenblatt A, Brinkman RR, Liang KY, Almqvist EW, Margolis RL, Huang CY, Sherr M, Franz ML, Abbott MH, Hayden MR, & Ross CA. Familial influence on age of onset among siblings with Huntington disease. Am J Med Genet 105 (5): 399-403, 2001. View Abstract


Almqvist EW, Bloch M, Brinkman R, Craufurd D, & Hayden MR. A worldwide assessment of the frequency of suicide, suicide attempts, or psychiatric hospitalization after predictive testing for Huntington disease. Am J Hum Genet 64 (5): 1293-304, 1999. View Abstract

Hadano S, Nichol K, Brinkman RR, Nasir J, Martindale D, Koop BF, Nicholson DW, Scherer SW, Ikeda JE, & Hayden MR. A yeast artificial chromosome-based physical map of the juvenile amyotrophic lateral sclerosis (ALS2) critical region on human chromosome 2q33-q34. Genomics 55 (1): 106-12, 1999. View Abstract


Brinkman RR, Mezei MM, Theilmann J, Almqvist E, & Hayden MR. The likelihood of being affected with Huntington disease by a particular age, for a specific CAG size. Am J Hum Genet 60 (5): 1202-10, 1997. View Abstract

Chissoe SL, Marra MA, Hillier L, Brinkman R, Wilson RK, & Waterston RH. Representation of cloned genomic sequences in two sequencing vectors: correlation of DNA sequence and subclone distribution. Nucleic Acids Res 25 (15): 2960-6, 1997. View Publication (Free PMC Article)

Wellington CL, Brinkman RR, O’Kusky JR, & Hayden MR. Toward understanding the molecular pathology of Huntington’s disease. Brain Pathol 7 (3): 979-1002, 1997. View Abstract


Vaudin M, Roopra A, Hillier L, Brinkman R, Sulston J, Wilson RK, and Waterson RH.  The Construction and Analysis of M13 Libraries prepared from YAC DNA.  Nucleic Acids Research, 23: 670-674, 1995. View Abstract