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Cytapex Bioinformatics Inc.

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Burnaby, British Columbia, CA

About Cytapex Bioinformatics Inc.

Cytapex Bioinformatics Inc. removes the barriers to high throughput / high dimensional cytometry data by providing expert services in data management, quality checking and data analysis including customized gating and biomarker discovery pipelines. Our speciality is customized automated gating based on client's manual gating hierarchy delivered as a FlowJo plugin to match the results you wold have obtained by hand.

Recent Publications

  • 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. 2017
  • 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.
  • 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.
  • O’Neill K, Brinkman RR. Publishing code is essential for reproducible flow cytometry bioinformatics. Cytometry A. 89(1): 10-1, 2016.
  • 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.
  • 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.
  • 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.

Our Services (4)


Flow Cytometry Data Analysis

Price on request

No one knows your data like you do. That's why we use the knowledge you've built into your gating hierarchies to customize bioinformatics pipelines that can analyze your flow cytometry data better and faster (a couple of seconds per file) than you would have by manual analysis. Our workflows leverage algorithms we developed in-house, and that have consistently been peer-reviewed to be the best performing and state-of-the art (PMC3906045, PMC4874734, PMC4748244). We also have experience with all the commonly used automated tools for the automated analysis of flow cytometry and mass cytometry (CyTOF) datasets (PMC4824634).


Data Management

Price on request
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Computational Modeling

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Data Services

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