About this Research Topic
Understanding single-cell data sets and the biological systems they represent is a critical effort for the fields of immunology and medicine. The amount of data associated with each published study is dramatically increasing in terms of cell quantity and number of dimensions. It is not rare that analysis of extremely rich data sets like those generated by technology such as flow, mass, and imaging cytometry remains partly unexplored following the publication of a study. In addition, differently from the field of genomics, where data are extremely standardized, it is rare in cytometry to find examples of analysis of data combined from different sources. Stable efforts in the cytometry data-repository field have seen success with the NIH supported “ImmPort” project. More generally, at the European level, the Elixir organization provides an infrastructure to mutualize data repositories. Dataset Search from Google is an additional tool to index datasets across repositories. Nevertheless, secondary analysis in the field of cytometry remains limited.
Addressing perceived limitations and activating the value and recognition for discovery through secondary analysis is critical to leverage the depth of knowledge in cytometry data sets. We believe that secondary analyses that comes from data sharing may be a desirable aim for founding programs for hypothesis generation, confirmation, and statistical considerations (reproducibility and power in future study design). We also believe an important amount of scientific knowledge remains unexplored in these datasets and, more interesting, data integration from different studies may lead to new unforeseen findings. Additionally, new algorithms applied to existing datasets may stimulate the field to develop innovative analysis tools. Finally, flow cytometry core facilities may play an important role in this re-use of data since they often manage data storage and, in each institution, they perform an activity of harmonization among projects and departments.
This Research Topic aims to promote cytometry secondary analysis, specifically in the field of immunology. We welcome the submission of Original Research, Review, Mini-Review, Methods, Protocols, and Hypothesis and Theory articles covering, but not limited to, the following topics, and discussing clear immunological applications:
• Secondary analysis of cytometry data with the aim to answer new immunological questions
• Integration of non-cytometry data set and /or integration of data from different articles in the field of immunology
• Preparedness for new projects aiming at studying the immune system by the generation of preliminary data or calculation of statistical power
• Analysis of data by means of new algorithms will be welcome, provided the new algorithm give a new immunological insight
Keywords: Immunology; Cytometry; Data; Existing; Mining; Secondary Analysis
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