Showing 11 of total 11 results (show query)
bioc
ggcyto:Visualize Cytometry data with ggplot
With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. ggcyto wrapper and some customed layers also make it easy to add gates and population statistics to the plot.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassaysinfrastructurevisualization
58 stars 11.25 score 362 scripts 5 dependentsbioc
flowStats:Statistical methods for the analysis of flow cytometry data
Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassays
14 stars 8.27 score 195 scripts 1 dependentsbioc
openCyto:Hierarchical Gating Pipeline for flow cytometry data
This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy.
Maintained by Mike Jiang. Last updated 3 days ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationcpp
8.02 score 404 scripts 1 dependentsbioc
flowWorkspace:Infrastructure for representing and interacting with gated and ungated cytometry data sets.
This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.
Maintained by Greg Finak. Last updated 23 days ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationzlibopenblascpp
7.89 score 576 scripts 10 dependentsbioc
CytoML:A GatingML Interface for Cross Platform Cytometry Data Sharing
Uses platform-specific implemenations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.
Maintained by Mike Jiang. Last updated 23 days ago.
immunooncologyflowcytometrydataimportdatarepresentationzlibopenblaslibxml2cpp
30 stars 7.60 score 132 scriptsbioc
PeacoQC:Peak-based selection of high quality cytometry data
This is a package that includes pre-processing and quality control functions that can remove margin events, compensate and transform the data and that will use PeacoQCSignalStability for quality control. This last function will first detect peaks in each channel of the flowframe. It will remove anomalies based on the IsolationTree function and the MAD outlier detection method. This package can be used for both flow- and mass cytometry data.
Maintained by Annelies Emmaneel. Last updated 5 months ago.
flowcytometryqualitycontrolpreprocessingpeakdetection
16 stars 7.38 score 28 scripts 3 dependentsbioc
CytoPipeline:Automation and visualization of flow cytometry data analysis pipelines
This package provides support for automation and visualization of flow cytometry data analysis pipelines. In the current state, the package focuses on the preprocessing and quality control part. The framework is based on two main S4 classes, i.e. CytoPipeline and CytoProcessingStep. The pipeline steps are linked to corresponding R functions - that are either provided in the CytoPipeline package itself, or exported from a third party package, or coded by the user her/himself. The processing steps need to be specified centrally and explicitly using either a json input file or through step by step creation of a CytoPipeline object with dedicated methods. After having run the pipeline, obtained results at all steps can be retrieved and visualized thanks to file caching (the running facility uses a BiocFileCache implementation). The package provides also specific visualization tools like pipeline workflow summary display, and 1D/2D comparison plots of obtained flowFrames at various steps of the pipeline.
Maintained by Philippe Hauchamps. Last updated 5 months ago.
flowcytometrypreprocessingqualitycontrolworkflowstepimmunooncologysoftwarevisualization
4 stars 6.71 score 18 scripts 2 dependentsbioc
CytoMDS:Low Dimensions projection of cytometry samples
This package implements a low dimensional visualization of a set of cytometry samples, in order to visually assess the 'distances' between them. This, in turn, can greatly help the user to identify quality issues like batch effects or outlier samples, and/or check the presence of potential sample clusters that might align with the exeprimental design. The CytoMDS algorithm combines, on the one hand, the concept of Earth Mover's Distance (EMD), a.k.a. Wasserstein metric and, on the other hand, the Multi Dimensional Scaling (MDS) algorithm for the low dimensional projection. Also, the package provides some diagnostic tools for both checking the quality of the MDS projection, as well as tools to help with the interpretation of the axes of the projection.
Maintained by Philippe Hauchamps. Last updated 2 months ago.
flowcytometryqualitycontroldimensionreductionmultidimensionalscalingsoftwarevisualization
1 stars 5.23 score 2 scriptsbioc
CytoPipelineGUI:GUI's for visualization of flow cytometry data analysis pipelines
This package is the companion of the `CytoPipeline` package. It provides GUI's (shiny apps) for the visualization of flow cytometry data analysis pipelines that are run with `CytoPipeline`. Two shiny applications are provided, i.e. an interactive flow frame assessment and comparison tool and an interactive scale transformations visualization and adjustment tool.
Maintained by Philippe Hauchamps. Last updated 5 months ago.
flowcytometrypreprocessingqualitycontrolworkflowstepimmunooncologysoftwarevisualizationguishinyapps
4.70 score 2 scriptsbioc
flowGate:Interactive Cytometry Gating in R
flowGate adds an interactive Shiny app to allow manual GUI-based gating of flow cytometry data in R. Using flowGate, you can draw 1D and 2D span/rectangle gates, quadrant gates, and polygon gates on flow cytometry data by interactively drawing the gates on a plot of your data, rather than by specifying gate coordinates. This package is especially geared toward wet-lab cytometerists looking to take advantage of R for cytometry analysis, without necessarily having a lot of R experience.
Maintained by Andrew Wight. Last updated 5 months ago.
softwareworkflowstepflowcytometrypreprocessingimmunooncologydataimport
4.00 score 3 scriptsbioc
flowVS:Variance stabilization in flow cytometry (and microarrays)
Per-channel variance stabilization from a collection of flow cytometry samples by Bertlett test for homogeneity of variances. The approach is applicable to microarrays data as well.
Maintained by Ariful Azad. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassaysmicroarray
3.82 score 11 scripts