ISAC Probe Tag Dictionary: Standardized Nomenclature for Detection and Visualization Labels Used in Cytometry and Microscopy Imaging.

Since the advent of microscopy imaging and flow cytometry, there has been an explosion in the number of probes, consisting of a component binding to an analyte and a detectable tag, to mark areas of interest in or on cells and tissue. Probe tags have been created to detect and/or visualize probes. Over time, these probe tags have increased in number. The expansion has resulted in arbitrarily created synonyms of probe tags used in publications and software. The synonyms are problematic for readability of publications, accuracy of text/data mining, and bridging data from multiple platforms, protocols, and databases for Big Data analysis. Development and implementation of a universal language for probe tags will ensure equivalent quality and level of data being reported or extracted for clinical/scientific evaluation as well as help connect data from many platforms. The International Society for Advancement of Cytometry Data Standards Task Force composed of academic scientists and industry hardware/software/reagent manufactures have developed recommendations for a standardized nomenclature for probe tags used in cytometry and microscopy imaging. These recommendations are shared in this technical note in the form of a Probe Tag Dictionary. © 2020 International Society for Advancement of Cytometry.

Data File Standard for Flow Cytometry, version FCS 3.1.

The flow cytometry data file standard provides the specifications needed to completely describe flow cytometry data sets within the confines of the file containing the experimental data. In 1984, the first Flow Cytometry Standard format for data files was adopted as FCS 1.0. This standard was modified in 1990 as FCS 2.0 and again in 1997 as FCS 3.0. We report here on the next generation flow cytometry standard data file format. FCS 3.1 is a minor revision based on suggested improvements from the community. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type.The FCS 3.1 standard retains the basic FCS file structure and most features of previous versions of the standard. Changes included in FCS 3.1 address potential ambiguities in the previous versions and provide a more robust standard. The major changes include simplified support for international characters and improved support for storing compensation. The major additions are support for preferred display scale, a standardized way of capturing the sample volume, information about originality of the data file, and support for plate and well identification in high throughput, plate based experiments. Please see the normative version of the FCS 3.1 specification in Supporting Information for this manuscript (or at http://www.isac-net.org/ in the Current standards section) for a complete list of changes.

Identifier Mapping in Cytoscape.

Identifier Mapping, the association of terms across disparate taxonomies and databases, is a common hurdle in bioinformatics workflows. The idmapper app for Cytoscape simplifies identifier mapping for genes and proteins in the context of common biological networks. This app provides a unified interface to different identifier resources accessible through a right-click on the table's column header. It also provides an OSGi programming interface via Cytoscape Commands and CyREST that can be utilized for identifier mapping in scripts and other Cytoscape apps, and supports integrated Swagger documentation.

The Cytoscape Automation app article collection.

Cytoscape is the premiere platform for interactive analysis, integration and visualization of network data. While Cytoscape itself delivers much basic functionality, it relies on community-written apps to deliver specialized functions and analyses. To date, Cytoscape's CyREST feature has allowed researchers to write workflows that call basic Cytoscape functions, but provides no access to its high value app-based functions. With Cytoscape Automation, workflows can now call apps that have been upgraded to expose their functionality. This article collection is a resource to assist readers in quickly and economically leveraging such apps in reproducible workflows that scale independently to large data sets and production runs.

Data standards for flow cytometry.

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research--impacting a notably diverse range of medical and environmental research areas.