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DATA ANALYSIS AND BIOINFORMATICS

Resources for analyses of the immune response and big data


​The HIMSR will help you cover all of your analysis needs by offering both self-service access to state-of-the-art analysis software, and computational and statistical support ranging from consultation and advice to custom analysis and integration with existing data.

inForm is an automated image analysis software package that uses trainable algorithms in a user-friendly interface to accurately visualize and quantify biomarkers in tissue sections from the Vectra 3. Capability includes phenotyping, co-localization, co-expression, tissue region detection (e.g. tumor versus stroma), nearest-neighbor quantification, and traditional scoring functions. Cell type identification and localization allows downstream analyses including density of each cell type within each tissue, quantification of cell-cell contacts, and distances between cell types and tissue types. [Coming soon! Check out video of the workshop showing how to use inForm.] One copy of inForm is freely available for use by our on-campus customers (contact us for access by emailing Kim Jordan and sign up for time on the iL​ab calendar​).

Cell Engine is a new web-based tool for analyzing flow and mass cytometry data, harnessing the power of elastic cloud computing for speed, scalability, and collaboration. Quickly and intuitively determine cell populations of interest and quantify marker expression levels. We at HIMSR have access to one single-user account of the beta-release of the Cell Engine software (developed by Zach Bjornson, who cooperatively helped developed SPADE). Please contact us if you would like to try it out.


The FlowJo™ workspace is used for a variety of cytometry quantification analyses, including immunophenotyping, cell cycle, proliferation, kinetics studies, quantitative population comparison, and plate screening assays. This software is available for use on a dedicated analysis station in the Department of Immunology and Microbiology Flow Cytometry Shared Resource Laboratory. Please contact Erin Kitten for access.

Ron Schuyler is HI3’s resident bioinformatician. He obtained his PhD from the Computational Bioscience Program at the University of Colorado and did postdoctoral training in the Spanish National Centre for Genomic Analysis and Centre for Genomic Regulation.

Examples of projects that Ron has been working on include: high dimensional data analysis, immunohistochemistry phenotype densities and nearest-neighbor analysis, and heterogeneous data harmonization and integration.

Make an appointment to talk to Ron to see if he can help you with your computational and statistical needs or submit specific questions through the Bioinformatics Request link​.

Prices are subsidized by the HI3 (CU School of Medicine). Further reduced rates are available for preliminary data that will be used in future grant applications, please inquire if your study qualifies. Users outside the CU system, please inquire about non-academic, non-subsidized pricing.