A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry and imaging data.

R scripts to reproduce analyses in our paper comparing clustering methods for high-dimensional cytometry data

A tutorial for the analysis of high-dimensional flow cytometry data

Flow cytometry analysis workflow. The aim of this project is to provide an intuitive workflow for the analysis of high-dimensionality cytometry data in R.

R package for differential discovery analyses in high-dimensional cytometry data

An R package for analyzing high-dimensional cytometry data using the tidyverse.

Python package to generate high dimensional Flow Cytometry datasets using imputation by XGBoost regression

Data package containing high-dimensional cytometry data sets in SummarizedExperiment and flowSet formats

A package for clustering high-dimensional cytometry data in Python.

A simplified, semi-automated high parameter workflow for people who don't know how to code. High dimensional flow cytometry analysis.

Analysis of high-dimensional cytometry data using tSNE and FlowSOM

An R package for advanced pathfinding analysis in high-dimensional cytometry data without the use of dimensional reduction.

A comprehensive framework to objectively assess high-dimensional cytometry data for batch effects

A computational toolkit for the analysis of high-dimensional single-cell cytometry data

Autoencoder-based models for dimension reduction of high-dimensional cytometry and single-cell RNA-seq data based on geometry and nearest-neighbour relations

R scripts to use various flow cytometry analyses

BrickPlots - a visualisation tool for clustered high dimensional cytometry data

A Graphical User Interface for streamlining analysis of high-dimensional cytometry data

An optimized high dimensional workflow for flow cytometry data designed for people comfortable with some R.

This repository contains scripts and data to generate figures in Liechti et al, 2021, Nature Immunology: An updated guide for the perplexed: cytometry in the high-dimensional era. Nature Immunology.

THIS PACKAGE IS DEPRECATED AND REPLACED BY flowSpecs. This is a package for processing of high-dimensional cytometry data, such as from mass cytometry and spectral flow cytometry. In it are functions for spectal unmixing and correction, transfomration, batch normalization and also different automated 1D filters. The package is being updated to adhere to flowCore standards, but will avoid the filter classes, and instead include the filters as logical columns in the exprs slot of the flowFrames/flowSets.

Workshop on high-dimensional cytometry data

No description available

No description available

High-dimensional flow cytometry analysis with agents

Differential discovery analyses in high-dimensional cytometry data.

analysis of high dimensional single-cell cytometry data

Draft 1 - Combination of packages used to analyse flow cytometry data including Spectre, Cytofkit2, Cytonorm among others

Analysis of high dimension flow cytometry data

Tools for the analysis of high dimensional flow cytometry data