Showing 67 of total 67 results (show query)
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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
10.0 match 58 stars 11.25 score 362 scripts 5 dependentsbioc
CATALYST:Cytometry dATa anALYSis Tools
CATALYST provides tools for preprocessing of and differential discovery in cytometry data such as FACS, CyTOF, and IMC. Preprocessing includes i) normalization using bead standards, ii) single-cell deconvolution, and iii) bead-based compensation. For differential discovery, the package provides a number of convenient functions for data processing (e.g., clustering, dimension reduction), as well as a suite of visualizations for exploratory data analysis and exploration of results from differential abundance (DA) and state (DS) analysis in order to identify differences in composition and expression profiles at the subpopulation-level, respectively.
Maintained by Helena L. Crowell. Last updated 4 months ago.
clusteringdataimportdifferentialexpressionexperimentaldesignflowcytometryimmunooncologymassspectrometrynormalizationpreprocessingsinglecellsoftwarestatisticalmethodvisualization
10.0 match 67 stars 11.06 score 362 scripts 2 dependentsbioc
flowCore:flowCore: Basic structures for flow cytometry data
Provides S4 data structures and basic functions to deal with flow cytometry data.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyinfrastructureflowcytometrycellbasedassayscpp
10.0 match 10.34 score 1.7k scripts 59 dependentsbioc
diffcyt:Differential discovery in high-dimensional cytometry via high-resolution clustering
Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.
Maintained by Lukas M. Weber. Last updated 1 months ago.
immunooncologyflowcytometryproteomicssinglecellcellbasedassayscellbiologyclusteringfeatureextractionsoftware
10.0 match 20 stars 9.98 score 225 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
10.0 match 13 stars 8.24 score 195 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 8 days ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationzlibopenblascpp
10.0 match 7.89 score 576 scripts 10 dependentsbioc
FlowSOM:Using self-organizing maps for visualization and interpretation of cytometry data
FlowSOM offers visualization options for cytometry data, by using Self-Organizing Map clustering and Minimal Spanning Trees.
Maintained by Sofie Van Gassen. Last updated 5 months ago.
cellbiologyflowcytometryclusteringvisualizationsoftwarecellbasedassays
10.0 match 7.71 score 468 scripts 10 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 5 months ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationcpp
10.0 match 7.62 score 404 scripts 1 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 8 days ago.
immunooncologyflowcytometrydataimportdatarepresentationzlibopenblaslibxml2cpp
10.0 match 30 stars 7.60 score 132 scriptsbioc
ncdfFlow:ncdfFlow: A package that provides HDF5 based storage for flow cytometry data.
Provides HDF5 storage based methods and functions for manipulation of flow cytometry data.
Maintained by Mike Jiang. Last updated 2 months ago.
immunooncologyflowcytometryzlibcpp
10.0 match 7.56 score 96 scripts 11 dependentsbioc
flowViz:Visualization for flow cytometry
Provides visualization tools for flow cytometry data.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyinfrastructureflowcytometrycellbasedassaysvisualization
10.0 match 7.44 score 231 scripts 12 dependentsbioc
cytolib:C++ infrastructure for representing and interacting with the gated cytometry data
This package provides the core data structure and API to represent and interact with the gated cytometry data.
Maintained by Mike Jiang. Last updated 2 months ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentation
10.0 match 7.39 score 7 scripts 60 dependentsbioc
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
10.0 match 16 stars 7.38 score 28 scripts 3 dependentsbioc
flowClust:Clustering for Flow Cytometry
Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyclusteringvisualizationflowcytometry
10.0 match 7.30 score 83 scripts 6 dependentsbioc
tidytof:Analyze High-dimensional Cytometry Data Using Tidy Data Principles
This package implements an interactive, scientific analysis pipeline for high-dimensional cytometry data built using tidy data principles. It is specifically designed to play well with both the tidyverse and Bioconductor software ecosystems, with functionality for reading/writing data files, data cleaning, preprocessing, clustering, visualization, modeling, and other quality-of-life functions. tidytof implements a "grammar" of high-dimensional cytometry data analysis.
Maintained by Timothy Keyes. Last updated 5 months ago.
singlecellflowcytometrybioinformaticscytometrydata-sciencesingle-celltidyversecpp
10.0 match 19 stars 7.26 score 35 scriptsbioc
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
10.0 match 4 stars 6.78 score 18 scripts 2 dependentsbioc
COMPASS:Combinatorial Polyfunctionality Analysis of Single Cells
COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyflowcytometrycpp
10.0 match 7 stars 6.51 score 42 scriptsbioc
distinct:distinct: a method for differential analyses via hierarchical permutation tests
distinct is a statistical method to perform differential testing between two or more groups of distributions; differential testing is performed via hierarchical non-parametric permutation tests on the cumulative distribution functions (cdfs) of each sample. While most methods for differential expression target differences in the mean abundance between conditions, distinct, by comparing full cdfs, identifies, both, differential patterns involving changes in the mean, as well as more subtle variations that do not involve the mean (e.g., unimodal vs. bi-modal distributions with the same mean). distinct is a general and flexible tool: due to its fully non-parametric nature, which makes no assumptions on how the data was generated, it can be applied to a variety of datasets. It is particularly suitable to perform differential state analyses on single cell data (i.e., differential analyses within sub-populations of cells), such as single cell RNA sequencing (scRNA-seq) and high-dimensional flow or mass cytometry (HDCyto) data. To use distinct one needs data from two or more groups of samples (i.e., experimental conditions), with at least 2 samples (i.e., biological replicates) per group.
Maintained by Simone Tiberi. Last updated 5 months ago.
geneticsrnaseqsequencingdifferentialexpressiongeneexpressionmultiplecomparisonsoftwaretranscriptionstatisticalmethodvisualizationsinglecellflowcytometrygenetargetopenblascpp
10.0 match 11 stars 6.35 score 34 scripts 1 dependentsbioc
scDataviz:scDataviz: single cell dataviz and downstream analyses
In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.
Maintained by Kevin Blighe. Last updated 5 months ago.
singlecellimmunooncologyrnaseqgeneexpressiontranscriptionflowcytometrymassspectrometrydataimport
10.0 match 63 stars 6.30 score 16 scriptsbioc
flowPloidy:Analyze flow cytometer data to determine sample ploidy
Determine sample ploidy via flow cytometry histogram analysis. Reads Flow Cytometry Standard (FCS) files via the flowCore bioconductor package, and provides functions for determining the DNA ploidy of samples based on internal standards.
Maintained by Tyler Smith. Last updated 5 months ago.
flowcytometryguiregressionvisualizationbioconductorevolutionflow-cytometrypolyploidy
10.0 match 5 stars 6.26 score 5 scriptsbioc
flowPeaks:An R package for flow data clustering
A fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means.
Maintained by Yongchao Ge. Last updated 4 months ago.
immunooncologyflowcytometryclusteringgatinggslcpp
10.0 match 5.91 score 30 scripts 3 dependentsbioc
CytoGLMM:Conditional Differential Analysis for Flow and Mass Cytometry Experiments
The CytoGLMM R package implements two multiple regression strategies: A bootstrapped generalized linear model (GLM) and a generalized linear mixed model (GLMM). Most current data analysis tools compare expressions across many computationally discovered cell types. CytoGLMM focuses on just one cell type. Our narrower field of application allows us to define a more specific statistical model with easier to control statistical guarantees. As a result, CytoGLMM finds differential proteins in flow and mass cytometry data while reducing biases arising from marker correlations and safeguarding against false discoveries induced by patient heterogeneity.
Maintained by Christof Seiler. Last updated 5 months ago.
flowcytometryproteomicssinglecellcellbasedassayscellbiologyimmunooncologyregressionstatisticalmethodsoftware
10.0 match 2 stars 5.68 score 1 scripts 1 dependentsbioc
flowAI:Automatic and interactive quality control for flow cytometry data
The package is able to perform an automatic or interactive quality control on FCS data acquired using flow cytometry instruments. By evaluating three different properties: 1) flow rate, 2) signal acquisition, 3) dynamic range, the quality control enables the detection and removal of anomalies.
Maintained by Gianni Monaco. Last updated 5 months ago.
flowcytometryqualitycontrolbiomedicalinformaticsimmunooncology
10.0 match 5.67 score 86 scripts 3 dependentsbioc
cydar:Using Mass Cytometry for Differential Abundance Analyses
Identifies differentially abundant populations between samples and groups in mass cytometry data. Provides methods for counting cells into hyperspheres, controlling the spatial false discovery rate, and visualizing changes in abundance in the high-dimensional marker space.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologyflowcytometrymultiplecomparisonproteomicssinglecellcpp
10.0 match 5.64 score 48 scriptsbioc
flowMeans:Non-parametric Flow Cytometry Data Gating
Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required.
Maintained by Nima Aghaeepour. Last updated 5 months ago.
immunooncologyflowcytometrycellbiologyclustering
10.0 match 5.64 score 36 scripts 2 dependentsbioc
scifer:Scifer: Single-Cell Immunoglobulin Filtering of Sanger Sequences
Have you ever index sorted cells in a 96 or 384-well plate and then sequenced using Sanger sequencing? If so, you probably had some struggles to either check the electropherogram of each cell sequenced manually, or when you tried to identify which cell was sorted where after sequencing the plate. Scifer was developed to solve this issue by performing basic quality control of Sanger sequences and merging flow cytometry data from probed single-cell sorted B cells with sequencing data. scifer can export summary tables, 'fasta' files, electropherograms for visual inspection, and generate reports.
Maintained by Rodrigo Arcoverde Cerveira. Last updated 3 months ago.
preprocessingqualitycontrolsangerseqsequencingsoftwareflowcytometrysinglecell
10.0 match 5 stars 5.54 score 9 scriptsbioc
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
10.0 match 1 stars 5.32 score 2 scriptsbioc
DepecheR:Determination of essential phenotypic elements of clusters in high-dimensional entities
The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.
Maintained by Jakob Theorell. Last updated 5 months ago.
softwarecellbasedassaystranscriptiondifferentialexpressiondatarepresentationimmunooncologytranscriptomicsclassificationclusteringdimensionreductionfeatureextractionflowcytometryrnaseqsinglecellvisualizationcpp
10.0 match 5.18 score 15 scriptsbioc
flowDensity:Sequential Flow Cytometry Data Gating
This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.
Maintained by Mehrnoush Malek. Last updated 5 months ago.
bioinformaticsflowcytometrycellbiologyclusteringcancerflowcytdatadatarepresentationstemcelldensitygating
10.0 match 5.17 score 83 scripts 3 dependentsbioc
plotGrouper:Shiny app GUI wrapper for ggplot with built-in statistical analysis
A shiny app-based GUI wrapper for ggplot with built-in statistical analysis. Import data from file and use dropdown menus and checkboxes to specify the plotting variables, graph type, and look of your plots. Once created, plots can be saved independently or stored in a report that can be saved as a pdf. If new data are added to the file, the report can be refreshed to include new data. Statistical tests can be selected and added to the graphs. Analysis of flow cytometry data is especially integrated with plotGrouper. Count data can be transformed to return the absolute number of cells in a sample (this feature requires inclusion of the number of beads per sample and information about any dilution performed).
Maintained by John D. Gagnon. Last updated 5 months ago.
immunooncologyflowcytometrygraphandnetworkstatisticalmethoddataimportguimultiplecomparisonbioconductorggplot2plottingshiny
10.0 match 6 stars 4.78 score 10 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
10.0 match 4.78 score 2 scriptsbioc
Sconify:A toolkit for performing KNN-based statistics for flow and mass cytometry data
This package does k-nearest neighbor based statistics and visualizations with flow and mass cytometery data. This gives tSNE maps"fold change" functionality and provides a data quality metric by assessing manifold overlap between fcs files expected to be the same. Other applications using this package include imputation, marker redundancy, and testing the relative information loss of lower dimension embeddings compared to the original manifold.
Maintained by Tyler J Burns. Last updated 5 months ago.
immunooncologysinglecellflowcytometrysoftwaremultiplecomparisonvisualization
10.0 match 4.74 score 11 scriptsbioc
MetaCyto:MetaCyto: A package for meta-analysis of cytometry data
This package provides functions for preprocessing, automated gating and meta-analysis of cytometry data. It also provides functions that facilitate the collection of cytometry data from the ImmPort database.
Maintained by Zicheng Hu. Last updated 5 months ago.
immunooncologycellbiologyflowcytometryclusteringstatisticalmethodsoftwarecellbasedassayspreprocessing
10.0 match 4.73 score 18 scriptsbioc
flowFP:Fingerprinting for Flow Cytometry
Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry.
Maintained by Herb Holyst. Last updated 5 months ago.
flowcytometrycellbasedassaysclusteringvisualization
10.0 match 4.72 score 11 scripts 2 dependentsbioc
quantiseqr:Quantification of the Tumor Immune contexture from RNA-seq data
This package provides a streamlined workflow for the quanTIseq method, developed to perform the quantification of the Tumor Immune contexture from RNA-seq data. The quantification is performed against the TIL10 signature (dissecting the contributions of ten immune cell types), carefully crafted from a collection of human RNA-seq samples. The TIL10 signature has been extensively validated using simulated, flow cytometry, and immunohistochemistry data.
Maintained by Federico Marini. Last updated 3 months ago.
geneexpressionsoftwaretranscriptiontranscriptomicssequencingmicroarrayvisualizationannotationimmunooncologyfeatureextractionclassificationstatisticalmethodexperimenthubsoftwareflowcytometry
10.0 match 4.65 score 3 scripts 1 dependentsbioc
reconsi:Resampling Collapsed Null Distributions for Simultaneous Inference
Improves simultaneous inference under dependence of tests by estimating a collapsed null distribution through resampling. Accounting for the dependence between tests increases the power while reducing the variability of the false discovery proportion. This dependence is common in genomics applications, e.g. when combining flow cytometry measurements with microbiome sequence counts.
Maintained by Stijn Hawinkel. Last updated 5 months ago.
metagenomicsmicrobiomemultiplecomparisonflowcytometry
10.0 match 2 stars 4.60 score 2 scriptsbioc
treekoR:Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations
treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; quantify a cell types as a proportion relative to all cells in a sample (%total), and, as the proportion relative to a parent population (%parent); perform significance testing using the calculated proportions; and provide an interactive html visualisation to help highlight key results.
Maintained by Adam Chan. Last updated 5 months ago.
clusteringdifferentialexpressionflowcytometryimmunooncologymassspectrometrysinglecellsoftwarestatisticalmethodvisualization
10.0 match 4.56 score 12 scripts 1 dependentsbioc
flowClean:flowClean
A quality control tool for flow cytometry data based on compositional data analysis.
Maintained by Kipper Fletez-Brant. Last updated 5 months ago.
flowcytometryqualitycontrolimmunooncology
10.0 match 4.56 score 18 scriptsbioc
flowMerge:Cluster Merging for Flow Cytometry Data
Merging of mixture components for model-based automated gating of flow cytometry data using the flowClust framework. Note: users should have a working copy of flowClust 2.0 installed.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyclusteringflowcytometry
10.0 match 4.56 score 6 scripts 1 dependentsbioc
MAPFX:MAssively Parallel Flow cytometry Xplorer (MAPFX): A Toolbox for Analysing Data from the Massively-Parallel Cytometry Experiments
MAPFX is an end-to-end toolbox that pre-processes the raw data from MPC experiments (e.g., BioLegend's LEGENDScreen and BD Lyoplates assays), and further imputes the ‘missing’ infinity markers in the wells without those measurements. The pipeline starts by performing background correction on raw intensities to remove the noise from electronic baseline restoration and fluorescence compensation by adapting a normal-exponential convolution model. Unwanted technical variation, from sources such as well effects, is then removed using a log-normal model with plate, column, and row factors, after which infinity markers are imputed using the informative backbone markers as predictors. The completed dataset can then be used for clustering and other statistical analyses. Additionally, MAPFX can be used to normalise data from FFC assays as well.
Maintained by Hsiao-Chi Liao. Last updated 5 months ago.
softwareflowcytometrycellbasedassayssinglecellproteomicsclustering
10.0 match 1 stars 4.54 scorebioc
spillR:Spillover Compensation in Mass Cytometry Data
Channel interference in mass cytometry can cause spillover and may result in miscounting of protein markers. We develop a nonparametric finite mixture model and use the mixture components to estimate the probability of spillover. We implement our method using expectation-maximization to fit the mixture model.
Maintained by Marco Guazzini. Last updated 5 months ago.
flowcytometryimmunooncologymassspectrometrypreprocessingsinglecellsoftwarestatisticalmethodvisualizationregression
10.0 match 4.48 score 3 scriptsbioc
flowTime:Annotation and analysis of biological dynamical systems using flow cytometry
This package facilitates analysis of both timecourse and steady state flow cytometry experiments. This package was originially developed for quantifying the function of gene regulatory networks in yeast (strain W303) expressing fluorescent reporter proteins using BD Accuri C6 and SORP cytometers. However, the functions are for the most part general and may be adapted for analysis of other organisms using other flow cytometers. Functions in this package facilitate the annotation of flow cytometry data with experimental metadata, as often required for publication and general ease-of-reuse. Functions for creating, saving and loading gate sets are also included. In the past, we have typically generated summary statistics for each flowset for each timepoint and then annotated and analyzed these summary statistics. This method loses a great deal of the power that comes from the large amounts of individual cell data generated in flow cytometry, by essentially collapsing this data into a bulk measurement after subsetting. In addition to these summary functions, this package also contains functions to facilitate annotation and analysis of steady-state or time-lapse data utilizing all of the data collected from the thousands of individual cells in each sample.
Maintained by R. Clay Wright. Last updated 5 months ago.
flowcytometrytimecoursevisualizationdataimportcellbasedassaysimmunooncology
10.0 match 4.48 score 8 scriptsbioc
MACSQuantifyR:Fast treatment of MACSQuantify FACS data
Automatically process the metadata of MACSQuantify FACS sorter. It runs multiple modules: i) imports of raw file and graphical selection of duplicates in well plate, ii) computes statistics on data and iii) can compute combination index.
Maintained by Raphaël Bonnet. Last updated 5 months ago.
dataimportpreprocessingnormalizationflowcytometrydatarepresentationgui
10.0 match 4.48 score 3 scripts
niaid
HDStIM:High Dimensional Stimulation Immune Mapping ('HDStIM')
A method for identifying responses to experimental stimulation in mass or flow cytometry that uses high dimensional analysis of measured parameters and can be performed with an end-to-end unsupervised approach. In the context of in vitro stimulation assays where high-parameter cytometry was used to monitor intracellular response markers, using cell populations annotated either through automated clustering or manual gating for a combined set of stimulated and unstimulated samples, 'HDStIM' labels cells as responding or non-responding. The package also provides auxiliary functions to rank intracellular markers based on their contribution to identifying responses and generating diagnostic plots.
Maintained by Rohit Farmer. Last updated 1 years ago.
complexheatmapassaycytofcytometrycytometry-analysis-pipelineflowcytometrystimulation
10.0 match 3 stars 4.41 score 17 scriptsbioc
flowTrans:Parameter Optimization for Flow Cytometry Data Transformation
Profile maximum likelihood estimation of parameters for flow cytometry data transformations.
Maintained by Greg Finak. Last updated 5 months ago.
10.0 match 4.40 score 21 scriptsbioc
immunoClust:immunoClust - Automated Pipeline for Population Detection in Flow Cytometry
immunoClust is a model based clustering approach for Flow Cytometry samples. The cell-events of single Flow Cytometry samples are modelled by a mixture of multinominal normal- or t-distributions. The cell-event clusters of several samples are modelled by a mixture of multinominal normal-distributions aiming stable co-clusters across these samples.
Maintained by Till Soerensen. Last updated 4 months ago.
clusteringflowcytometrysinglecellcellbasedassaysimmunooncologygslcpp
10.0 match 4.38 score 4 scriptsbioc
flowSpecs:Tools for processing of high-dimensional cytometry data
This package is intended to fill the role of conventional cytometry pre-processing software, for spectral decomposition, transformation, visualization and cleanup, and to aid further downstream analyses, such as with DepecheR, by enabling transformation of flowFrames and flowSets to dataframes. Functions for flowCore-compliant automatic 1D-gating/filtering are in the pipe line. The package name has been chosen both as it will deal with spectral cytometry and as it will hopefully give the user a nice pair of spectacles through which to view their data.
Maintained by Jakob Theorell. Last updated 5 months ago.
softwarecellbasedassaysdatarepresentationimmunooncologyflowcytometrysinglecellvisualizationnormalizationdataimport
10.0 match 6 stars 4.38 score 7 scriptsbioc
censcyt:Differential abundance analysis with a right censored covariate in high-dimensional cytometry
Methods for differential abundance analysis in high-dimensional cytometry data when a covariate is subject to right censoring (e.g. survival time) based on multiple imputation and generalized linear mixed models.
Maintained by Reto Gerber. Last updated 5 months ago.
immunooncologyflowcytometryproteomicssinglecellcellbasedassayscellbiologyclusteringfeatureextractionsoftwaresurvival
10.0 match 4.30 score 2 scriptsbioc
cyanoFilter:Phytoplankton Population Identification using Cell Pigmentation and/or Complexity
An approach to filter out and/or identify phytoplankton cells from all particles measured via flow cytometry pigment and cell complexity information. It does this using a sequence of one-dimensional gates on pre-defined channels measuring certain pigmentation and complexity. The package is especially tuned for cyanobacteria, but will work fine for phytoplankton communities where there is at least one cell characteristic that differentiates every phytoplankton in the community.
Maintained by Oluwafemi Olusoji. Last updated 5 months ago.
flowcytometryclusteringonechannel
10.0 match 4.30 score 4 scriptsbioc
tidyFlowCore:tidyFlowCore: Bringing flowCore to the tidyverse
tidyFlowCore bridges the gap between flow cytometry analysis using the flowCore Bioconductor package and the tidy data principles advocated by the tidyverse. It provides a suite of dplyr-, ggplot2-, and tidyr-like verbs specifically designed for working with flowFrame and flowSet objects as if they were tibbles; however, your data remain flowCore data structures under this layer of abstraction. tidyFlowCore enables intuitive and streamlined analysis workflows that can leverage both the Bioconductor and tidyverse ecosystems for cytometry data.
Maintained by Timothy Keyes. Last updated 5 months ago.
singlecellflowcytometryinfrastructure
10.0 match 1 stars 4.30 score 7 scriptsbioc
cytoMEM:Marker Enrichment Modeling (MEM)
MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features' levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry using RMSD.
Maintained by Jonathan Irish. Last updated 5 months ago.
proteomicssystemsbiologyclassificationflowcytometrydatarepresentationdataimportcellbiologysinglecellclustering
10.0 match 4.18 score 15 scriptsbioc
flowCyBar:Analyze flow cytometric data using gate information
A package to analyze flow cytometric data using gate information to follow population/community dynamics
Maintained by Joachim Schumann. Last updated 5 months ago.
immunooncologycellbasedassaysclusteringflowcytometrysoftwarevisualization
10.0 match 4.15 score 1 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
10.0 match 4.00 score 3 scriptsbioc
flowBeads:flowBeads: Analysis of flow bead data
This package extends flowCore to provide functionality specific to bead data. One of the goals of this package is to automate analysis of bead data for the purpose of normalisation.
Maintained by Nikolas Pontikos. Last updated 5 months ago.
immunooncologyinfrastructureflowcytometrycellbasedassays
10.0 match 4.00 score 7 scriptsbioc
CyTOFpower:Power analysis for CyTOF experiments
This package is a tool to predict the power of CyTOF experiments in the context of differential state analyses. The package provides a shiny app with two options to predict the power of an experiment: i. generation of in-sicilico CyTOF data, using users input ii. browsing in a grid of parameters for which the power was already precomputed.
Maintained by Anne-Maud Ferreira. Last updated 5 months ago.
flowcytometrysinglecellcellbiologystatisticalmethodsoftware
10.0 match 4.00 score 2 scriptsbioc
CytoDx:Robust prediction of clinical outcomes using cytometry data without cell gating
This package provides functions that predict clinical outcomes using single cell data (such as flow cytometry data, RNA single cell sequencing data) without the requirement of cell gating or clustering.
Maintained by Zicheng Hu. Last updated 5 months ago.
immunooncologycellbiologyflowcytometrystatisticalmethodsoftwarecellbasedassaysregressionclassificationsurvival
10.0 match 4.00 score 8 scriptsbioc
cytoKernel:Differential expression using kernel-based score test
cytoKernel implements a kernel-based score test to identify differentially expressed features in high-dimensional biological experiments. This approach can be applied across many different high-dimensional biological data including gene expression data and dimensionally reduced cytometry-based marker expression data. In this R package, we implement functions that compute the feature-wise p values and their corresponding adjusted p values. Additionally, it also computes the feature-wise shrunk effect sizes and their corresponding shrunken effect size. Further, it calculates the percent of differentially expressed features and plots user-friendly heatmap of the top differentially expressed features on the rows and samples on the columns.
Maintained by Tusharkanti Ghosh. Last updated 5 months ago.
immunooncologyproteomicssinglecellsoftwareonechannelflowcytometrydifferentialexpressiongeneexpressionclusteringcpp
10.0 match 4.00 score 4 scriptsbioc
flowGraph:Identifying differential cell populations in flow cytometry data accounting for marker frequency
Identifies maximal differential cell populations in flow cytometry data taking into account dependencies between cell populations; flowGraph calculates and plots SpecEnr abundance scores given cell population cell counts.
Maintained by Alice Yue. Last updated 5 months ago.
flowcytometrystatisticalmethodimmunooncologysoftwarecellbasedassaysvisualization
10.0 match 4.00 score 10 scriptsbioc
flowCut:Automated Removal of Outlier Events and Flagging of Files Based on Time Versus Fluorescence Analysis
Common techinical complications such as clogging can result in spurious events and fluorescence intensity shifting, flowCut is designed to detect and remove technical artifacts from your data by removing segments that show statistical differences from other segments.
Maintained by Justin Meskas. Last updated 5 months ago.
flowcytometrypreprocessingqualitycontrolcellbasedassays
10.0 match 3.92 score 21 scriptsbioc
flowMatch:Matching and meta-clustering in flow cytometry
Matching cell populations and building meta-clusters and templates from a collection of FC samples.
Maintained by Ariful Azad. Last updated 5 months ago.
immunooncologyclusteringflowcytometrycpp
10.0 match 3.90 score 1 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
10.0 match 3.82 score 11 scriptsbioc
flowCHIC:Analyze flow cytometric data using histogram information
A package to analyze flow cytometric data of complex microbial communities based on histogram images
Maintained by Author: Joachim Schumann. Last updated 5 months ago.
immunooncologycellbasedassaysclusteringflowcytometrysoftwarevisualization
10.0 match 3.78 score 1 scriptsbioc
infinityFlow:Augmenting Massively Parallel Cytometry Experiments Using Multivariate Non-Linear Regressions
Pipeline to analyze and merge data files produced by BioLegend's LEGENDScreen or BD Human Cell Surface Marker Screening Panel (BD Lyoplates).
Maintained by Etienne Becht. Last updated 5 months ago.
softwareflowcytometrycellbasedassayssinglecellproteomics
10.0 match 3.60 score 4 scriptsbioc
GateFinder:Projection-based Gating Strategy Optimization for Flow and Mass Cytometry
Given a vector of cluster memberships for a cell population, identifies a sequence of gates (polygon filters on 2D scatter plots) for isolation of that cell type.
Maintained by Nima Aghaeepour. Last updated 5 months ago.
immunooncologyflowcytometrycellbiologyclustering
10.0 match 3.30 score 7 scriptsbioc
optimalFlow:optimalFlow
Optimal-transport techniques applied to supervised flow cytometry gating.
Maintained by Hristo Inouzhe. Last updated 5 months ago.
softwareflowcytometrytechnology
10.0 match 3.30 score 1 scriptsbioc
flowPlots:flowPlots: analysis plots and data class for gated flow cytometry data
Graphical displays with embedded statistical tests for gated ICS flow cytometry data, and a data class which stores "stacked" data and has methods for computing summary measures on stacked data, such as marginal and polyfunctional degree data.
Maintained by N. Hawkins. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassaysvisualizationdatarepresentation
10.0 match 3.30 score 1 scriptsbioc
flowBin:Combining multitube flow cytometry data by binning
Software to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them, by establishing common bins across tubes in terms of the common markers, then determining expression within each tube for each bin in terms of the tube-specific markers.
Maintained by Kieran ONeill. Last updated 5 months ago.
immunooncologycellbasedassaysflowcytometry
10.0 match 3.30 score 2 scripts