The immunology database and analysis portal (ImmPort) system is the archival repository and dissemination vehicle for clinical and molecular datasets created by research consortia funded by the National Institute of Allergy and Infectious Diseases Division of Allergy, Immunology, and Transplantation. With nearly 100 datasets now publicly available and hundreds of downloads per month, ImmPort is an important source for raw data and protocols from clinical trials, mechanistic studies, and novel methods for cellular and molecular measurements. To facilitate data transfer, templates for data representation and standard operating procedures have also been created and are also publicly available. ImmPort facilitates transparency and reproducibility in immunology research, serves as an important resource for education, and enables newly generated hypotheses and data-driven science.
Background
Advances in multi-parameter flow cytometry (FCM) now allow for the independent detection of larger numbers of fluorochromes on individual cells, generating data with increasingly higher dimensionality. The increased complexity of these data has made it difficult to identify cell populations from high-dimensional FCM data using traditional manual gating strategies based on single-color or two-color displays.
Methods
To address this challenge, we developed a novel program, FLOCK (FLOw Clustering without K), that uses a density-based clustering approach to algorithmically identify biologically relevant cell populations from multiple samples in an unbiased fashion, thereby eliminating operator-dependent variability.
Results
FLOCK was used to objectively identify seventeen distinct B cell subsets in a human peripheral blood sample and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations in peripheral blood. FLOCK has been implemented in the publically available Immunology Database and Analysis Portal – ImmPort (http://www.immport.org) for open use by the immunology research community.
Conclusions
FLOCK is able to identify cell subsets in experiments that use multi-parameter flow cytometry through an objective, automated computational approach. The use of algorithms like FLOCK for FCM data analysis obviates the need for subjective and labor intensive manual gating to identify and quantify cell subsets. Novel populations identified by these computational approaches can serve as hypotheses for further experimental study.
Post hoc, within-woman analysis of migraine treatment episodes categorized based on International Headache Society criteria showed that menstrual treatment episodes were more impairing, longer lasting, and more likely to relapse than nonmenstrual treatment episodes in this selected population of women with frequent menstrual migraine. The current analysis indicates that most of the variability in these outcomes is due to differences between headache types and not within-patient differences for a given type of headache, suggesting that menstrual episodes are potentially treatable. These findings underscore the differences between menstrual and nonmenstrual episodes of migraine and the need to offer effective migraine treatment to women.
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