Data preparation

Data preparation and export

Here we provide instructions for initial data preparation, including compensation, cleanup gating, and data export from programs such as FlowJo.


Core analysis workflows

Simple discovery workflow

Batch alignment discovery workflowSpatial


A simple workflow (with worked example) using a single R script to run clustering/dimensionality reduction, make plots, and perform some limited quantitative/statistical analysis. 

No batch alignment steps included.

A comprehensive and adaptable workflow (with worked example) for the integration and analysis of data from multiple batches.

Analysis workflows for high-dimensional imaging mass cytometry (IMC) data, using Spectre and SpectreMAP, an extension of Spectre, to facilitate spatial analysis. 

Other workflows

Rapidly generate tSNE/UMAP plots from CSV or FCS filesConvert FCS to CSV (and vise versa)Computational analysis using FlowJo

An R script to automatically generate tSNE/UMAP plots, after clustering/tSNE/UMAP has run in programs such as FlowJo.An R script to rapidly convert FCS files to CSV files (or vise versa).

Here we provide protocols for performing Spectre's discovery analysis workflows using FlowJo.

Specialised analysis areas

Time-series clustering and analysis with ChronoClustAnalysis tools and functions to assist in the analysis of scRNAseq dataQuantitative and statistical analysis from summary data

Here we provide a time-series clustering workflow using ChronoClust.

Here we provide analysis options and tools to support scRNAseq analysis, in conjunction with existing tools such as Seurat and SingleCellExperiment.

A workflow to rapidly generate graphs and heatmaps from summary data to perform quantitative and statistical analysis.


Advanced applications

These are approaches that are in use within our team, but are still under active development. These are described in our preprint (Ashhurst*, Marsh-Wakefield*, Putri*, et al. 2020. bioRxiv). If you are interested in using any of these approaches, please get in touch with us.

Integrating data derived from different experiments or instruments

Automated cell classification

Workflows to manage larger-than-memory datasets

A workflow to facilitate the alignment and automated classification of cell types in new cytometry datasets, based on an existing labelled reference dataset.

Strategies to facilitate automated cell classification.Strategies for the analysis of very large datasets, that are larger than the memory capacity of the computer being used.

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