 |
| Developer(s) | FlowJo LLC |
|---|---|
| Initial release | 1996 |
| Stable release | v10.10 / 16 November 2023 |
| License | Proprietary |
| Website | www |
FlowJo is a software package for analyzing flow cytometry data. Files produced by modern flow cytometers are written in the Flow Cytometry Standard [1] format with an .fcs file extension. FlowJo will import and analyze cytometry data regardless of which flow cytometer is used to collect the data.
In FlowJo, samples are organized in a "Workspace" window, which presents a hierarchical view of all the samples and their analyses (gates and statistics). Viewing an entire experiment in a Workspace permits organizing and managing complex cytometry experiments and produces detailed graphical reports. FlowJo's ability to automate repetitive operations facilitates the production of statistics tables and graphical reports when the experiment involves many samples, parameters and/or operations.
Within a workspace, samples can be grouped or sorted by various attributes such as the panel of antibodies with which they are stained, tissue type, or patient from whom they came. When an operation on a group is initiated, FlowJo can perform the same operation on every sample belonging to that group. Thus, you can apply a gate to a sample, copy it to the group, and that gate will be automatically placed on all samples in the group.
FlowJo provides tools for the creation of histogram and other plot overlays, cell cycle analysis. calcium flux analysis, proliferation analysis, quantification, cluster identification and backgating display
FlowJo became a commercial product in 1996. In 2002, Tree Star released a Windows version. FlowJo is currently developed by the Ashland, Oregon-based FlowJo LLC, a subsidiary of Becton Dickinson. [2]
SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc., it was acquired by IBM in 2009. Versions of the software released since 2015 have the brand name IBM SPSS Statistics.
Flow cytometry (FC) is a technique used to detect and measure the physical and chemical characteristics of a population of cells or particles.
RKWard is a transparent front-end to the R programming language, a scripting-language with a strong focus on statistics functions. RKWard tries to combine the power of the R language with the ease of use of commercial statistical packages.
A Coulter counter is an apparatus for counting and sizing particles suspended in electrolytes. The Coulter counter is the commercial term for the technique known as resistive pulse sensing or electrical zone sensing. The apparatus is based on the Coulter principle named after its inventor, Wallace H. Coulter.
The Apple Developer Tools are a suite of software tools from Apple to aid in making software dynamic titles for the macOS and iOS platforms. The developer tools were formerly included on macOS install media, but are now exclusively distributed over the Internet. As of macOS 10.12, Xcode is available as a free download from the Mac App Store.
Azure DevOps Server, formerly known as Team Foundation Server (TFS) and Visual Studio Team System (VSTS), is a Microsoft product that provides version control, reporting, requirements management, project management, automated builds, testing and release management capabilities. It covers the entire application lifecycle and enables DevOps capabilities. Azure DevOps can be used as a back-end to numerous integrated development environments (IDEs) but is tailored for Microsoft Visual Studio and Eclipse on all platforms.
A gate in cytometry is a set of value limits (boundaries) that serve to isolate a specific group of cytometric events from a large set. Gates can be defined by discrimination analysis, or can simply be drawn around a given set of data points on a printout and then converted to a computer-useful form. Gates can be implemented with a physical blinder. Gates may be used either to selectively gather data or to segregate data for analysis.
Green Kenue is an advanced data preparation, analysis, and visualization tool for hydrologic modellers. It is a Windows/OpenGL-based graphical user interface, integrating environmental databases and geo-spatial data with model input and results data. Green Kenue provides complete pre- and post-processing for the WATFLOOD and HBV-EC hydrologic models. Also included is a 1D "reach scale" unsteady hydrodynamic flow solver, Gen1D.
Psychometric software refers to specialized programs used for the psychometric analysis of data that was obtained from tests, questionnaires, polls or inventories that measure latent psychoeducational variables. Although some psychometric analysis can be conducted using general statistical software like SPSS, most require dedicated tools designed specifically for psychometric purposes.
Cytometry is the measurement of number and characteristics of cells. Variables that can be measured by cytometric methods include cell size, cell count, cell morphology, cell cycle phase, DNA content, and the existence or absence of specific proteins on the cell surface or in the cytoplasm. Cytometry is used to characterize and count blood cells in common blood tests such as the complete blood count. In a similar fashion, cytometry is also used in cell biology research and in medical diagnostics to characterize cells in a wide range of applications associated with diseases such as cancer and AIDS.
The virus counter is an instrument for rapid quantification of viruses in liquid samples. It is a specialized flow cytometer that uses high-sensitivity fluorescence detection to give a direct measurement of the concentration of virus particles in a fraction of the time required for traditional plaque assays.
LabKey Server is a software suite available for scientists to integrate, analyze, and share biomedical research data. The platform provides a secure data repository that allows web-based querying, reporting, and collaborating across a range of data sources. Specific scientific applications and workflows can be added on top of the basic platform and leverage a data processing pipeline.
Cytometry by time of flight, or CyTOF, is an application of mass cytometry used to quantify labeled targets on the surface and interior of single cells. CyTOF allows the quantification of multiple cellular components simultaneously using an ICP-MS detector.
LIMDEP is an econometric and statistical software package with a variety of estimation tools. In addition to the core econometric tools for analysis of cross sections and time series, LIMDEP supports methods for panel data analysis, frontier and efficiency estimation and discrete choice modeling. The package also provides a programming language to allow the user to specify, estimate and analyze models that are not contained in the built in menus of model forms.
Mass cytometry is a mass spectrometry technique based on inductively coupled plasma mass spectrometry and time of flight mass spectrometry used for the determination of the properties of cells (cytometry). In this approach, antibodies are conjugated with isotopically pure elements, and these antibodies are used to label cellular proteins. Cells are nebulized and sent through an argon plasma, which ionizes the metal-conjugated antibodies. The metal signals are then analyzed by a time-of-flight mass spectrometer. The approach overcomes limitations of spectral overlap in flow cytometry by utilizing discrete isotopes as a reporter system instead of traditional fluorophores which have broad emission spectra.
Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results.
Flow Cytometry Standard (FCS) is a data file standard for the reading and writing of data from flow cytometry experiments. The FCS specification has traditionally been developed and maintained by the International Society for Advancement of Cytometry (ISAC). FCS used to be the only widely adopted file format in flow cytometry. Recently, additional standard file formats have been developed by ISAC.
Bacterioplankton counting is the estimation of the abundance of bacterioplankton in a specific body of water, which is useful information to marine microbiologists. Various counting methodologies have been developed over the years to determine the number present in the water being observed. Methods used for counting bacterioplankton include epifluorescence microscopy, flow cytometry, measures of productivity through frequency of dividing cells (FDC), thymidine incorporation, and leucine incorporation.
Minimum information standards are sets of guidelines and formats for reporting data derived by specific high-throughput methods. Their purpose is to ensure the data generated by these methods can be easily verified, analysed and interpreted by the wider scientific community. Ultimately, they facilitate the transfer of data from journal articles into databases in a form that enables data to be mined across multiple data sets. Minimal information standards are available for a vast variety of experiment types including microarray (MIAME), RNAseq (MINSEQE), metabolomics (MSI) and proteomics (MIAPE).
Tissue image cytometry or tissue cytometry is a method of digital histopathology and combines classical digital pathology and computational pathology into one integrated approach with solutions for all kinds of diseases, tissue and cell types as well as molecular markers and corresponding staining methods to visualize these markers. Tissue cytometry uses virtual slides as they can be generated by multiple, commercially available slide scanners, as well as dedicated image analysis software – preferentially including machine and deep learning algorithms. Tissue cytometry enables cellular analysis within thick tissues, retaining morphological and contextual information, including spatial information on defined cellular subpopulations.