#FLOWJO SOFTWARE TREE STAR MANUAL#

Such errors are neither obvious nor easy to detect via the examinations of dot plot outputs from individual FCS files that are performed as part of regular, daily quality control procedures in a flow cytometry core. Variation in instrumentation, antibody staining, reagent lots, and other technical problems can crop up over time and manifest themselves as biases in the extracted cell subpopulation statistics or fluorescence intensities.

Importantly, clinical trials in these fields often use flow cytometry to monitor the immune system or the progression of a disease over time, generating large amounts of data in the process. It is also used for cross-matching organs for transplantation and in research involving stem cells, vaccine development, apoptosis, phagocytosis, and a wide range of cellular properties including phenotype, cytokine expression, and cell-cycle status. The technology is widely used in health research and treatment, including for monitoring of infection, diagnosis of cancers like lymphoma and leukaemia, and autoвЂ“immune diseases. The QUAliFiER tool objectively, efficiently, and reproducibly identifies outlier samples in an automated manner by monitoring cell population statistics from gated or ungated flow data conditioned on experimentвЂ“level metadata.ДЇlow cytometry (FCM) is a high-throughput technology that offers rapid quantification of a set of physical and chemical characteristics for a large number of cells in a sample. The pipeline addresses the increasing demand for tools capable of performing quality checks on large flow data sets generated in typical clinical trials. We present a pipeline constructed from two new R packages for importing manually gated flow cytometry data and performing flexible and robust quality assessment checks. QUAliFiER implements SVGвЂ“based interactive visualization methods, allowing investigators to examine quality assessment results across different views of the data, and it has a flexible interface allowing users to tailor quality checks and outlier detection routines to suit their data analysis needs.

#FLOWJO SOFTWARE TREE STAR MANUAL#

The QUAliFiER package takes advantage of the manual gates to perform an extensive series of statistical quality assessment checks on the gated cell subвЂ“populations while taking into account the structure of the data and the study design to monitor the consistency of population statistics across staining panels, subject, aliquots, channels, or other experimental variables. flowWorkspace makes manually gated data accessible to BioConductorвЂ™s computational flow tools by importing preвЂ“processed and gated data from the widely used manual gating tool, FlowJo (Tree Star Inc, Ashland OR). We have developed two new packages, flowWorkspace and QUAliFiER to construct a pipeline for quality assessment of gated flow cytometry data. Gated cell populations and their statistics must be monitored within the context of the experimental run, assay, and the overall study. Consequently, a systematic and integrated approach to quality assessment of flow cytometry data is necessary to effectively identify technical errors that impact multiple samples over time. These biases can manifest themselves in nonвЂ“obvious ways that can be difficult to detect without leveraging information about the study design or other experimental metadata. Technical issues like instrument variation, problematic antibody staining, or reagent lot changes can lead to biases in the extracted cell subpopulation statistics.

Effective quality assessment is an important part of any high-throughput flow cytometry data analysis pipeline, especially when considering the complex designs of the typical flow experiments applied in clinical trials.

Flowjo software tree star