MOTIVATION: For immune system monitoring in large-scale studies at the single-cell resolution using CyTOF, (semi-)automated computational methods are applied for annotating live cells of mixed cell types. Here, we show that the live cell pool can be highly enriched with undefined heterogeneous cells, i.e. 'ungated' cells, and that current semi-automated approaches ignore their modeling resulting in misclassified annotations. RESULT: We introduce 'CyAnno', a novel semi-automated approach for deconvoluting the unlabeled cytometry dataset based on a machine learning framework utilizing manually gated training data that allows the integrative modeling of 'gated' cell types and the 'ungated' cells. By applying this framework on several CyTOF datasets, we demonstrated that including the 'ungated' cells can lead to a significant increase in the precision of the 'gated' cell types prediction. CyAnno can be used to identify even a single cell type, including rare cells, with higher efficacy than current state-of-the-art semi-automated approaches. AVAILABILITY AND IMPLEMENTATION: The CyAnno is available as a python script with a user-manual and sample dataset at https://github.com/abbioinfo/CyAnno. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Summary: : Open access to raw clinical and molecular data related to immunological studies has created a tremendous opportunity for data-driven science. We have developed RImmPort that prepares NIAID-funded research study datasets in ImmPort (immport.org) for analysis in R. RImmPort comprises of three main components: (i) a specification of R classes that encapsulate study data, (ii) foundational methods to load data of a specific study and (iii) generic methods to slice and dice data across different dimensions in one or more studies. Furthermore, RImmPort supports open formalisms, such as CDISC standards on the open source bioinformatics platform Bioconductor, to ensure that ImmPort curated study datasets are seamlessly accessible and ready for analysis, thus enabling innovative bioinformatics research in immunology. Availability and Implementation: RImmPort is available as part of Bioconductor (bioconductor.org/packages/RImmPort). Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Researchers are applying a wide variety of assay methods to explore the complex and dynamic human immunology system. There are a number of initiatives to encourage sharing of results, the standardization of terminology, and the reanalysis of data to improve reproducibility and ensure scientific rigor. The ImmPort project is an example of a NIH resource to collect, curate, and share immunological research. We describe the ImmPort project resources available to encourage an exploration of the tools and skill sets needed for analyzing shared immunological data, including clinical and mechanistic studies, analysis tools, and example analysis code. There is an ongoing effort to annotate the shared data with standardized terms from ontologies, make these curated data sets available in formats amenable to bioinformatic tools, and provide examples of how to access and analyze the data sets.