Towards the characterization of normal peripheral immune cells with data from ImmPort

To date, our understanding of a normal immune system is far behind that of other healthy organ systems. One reason for this is the lack of standardization in the lab techniques, especially flow cytometry. To take a step towards the characterization of a normal immune system, we re-analyzed and combined data that was made publicly available through the Immunology Database and Analysis Portal (ImmPort, immport.niaid.nih.gov) [1]. ImmPort is a public warehouse for the management and analysis of clinical and mechanistic data from NIAID/DAIT-funded research studies. Currently, 108 studies are made publicly available in ImmPort of which 27 contain raw FCS files from flow cytometry experiments run on samples of adults. Here we use ImmPort as a source of publicly available raw flow cytometry files from hundreds of participants in several trials, to study immune cells from the blood of healthy individuals. To characterize well-defined cells in a normal immune system, we used an unbiased method to compare data from different cytometers and antibody staining panels. As an initial step, we obtained the marker information from each raw FCS file in an automated fashion and made their nomenclature consistent. We applied and evaluated various transformation strategies and normalized the data on a per-channel basis using the R function warpSet [2] from the flowStats package of Bioconductor to make the flow cytometry data more comparable across studies. Initial promising results were observed for the cell-surface markers used to define T and B cells in general in automatically gated lymphocyte populations. Using our pipeline, the distribution of percentages of B cells as well as CD4+ and CD8+ T cells of subjects is in the range as immunologically expected and mostly comparable across the different studies originating from different laboratories. We plan to extend this approach to more cell types and eventually to studies of healthy individuals separated by gender, age group or ethnicity. Our approach promises to give further insights into the normal immune system.

[1]  Ryan R Brinkman,et al.  Per‐channel basis normalization methods for flow cytometry data , 2009, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[2]  Jeffrey A. Wiser,et al.  ImmPort: disseminating data to the public for the future of immunology , 2014, Immunologic Research.