CytofRUV: Removing unwanted variation to integrate multiple CyTOF datasets

Trussart, Marie; Ce, Teh; Tan, Tianwei; Leong, Lawrence; Gray, D. H.; Speed, TP

doi:10.1101/2020.05.09.085621

Cited by 13 publications

(20 citation statements)

References 20 publications

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“…The increasing use of CyTOF in clinical research requires standardized workflows and protocols for the acquisition and analysis of large-scale, multicentre, immune-monitoring clinical studies. Batch-correcting algorithms 89 and reproducible data generation are the basis for reliable and robust clinical analyses. For this objective, a method that uses a lyophilized core antibody panel to streamline blood sample processing has been implemented to reduce technical variation and standardize operations 90 and includes quality control by removing events caused by loss of stability and compensating for signal spillover resulting from isotopic impurities or oxide formation 91 .…”

Section: Cytof Analyses Provide Novel Clinical Insightsmentioning

confidence: 99%

Immune cell profiling in atherosclerosis: role in research and precision medicine

Fernandez

Giannarelli

2021

Nat Rev Cardiol

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Inflammation is intimately involved at all stages of atherosclerosis and remains a substantial residual cardiovascular risk factor in optimally treated patients. The proof of concept that targeting inflammation reduces cardiovascular events in patients with a history of myocardial infarction has highlighted the urgent need to identify new immunotherapies to treat patients with atherosclerotic cardiovascular disease. Importantly, emerging data from new clinical trials show that successful immunotherapies for atherosclerosis need to be tailored to the specific immune alterations in distinct groups of patients. In this Review, we discuss how single-cell technologies -such as single-cell mass cytometry, single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing -are ideal for mapping the cellular and molecular composition of human atherosclerotic plaques and how these data can aid in the discovery of new precise immunotherapies. We also argue that single-cell data from studies in humans need to be rigorously validated in relevant experimental models, including rapidly emerging single-cell CRISPR screening technologies and mouse models of atherosclerosis. Finally, we discuss the importance of implementing single-cell immune monitoring tools in early phases of drug development to aid in the precise selection of the target patient population for data-driven translation into randomized clinical trials and the successful translation of new immunotherapies into the clinic.

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Section: Cytof Analyses Provide Novel Clinical Insightsmentioning

confidence: 99%

Immune cell profiling in atherosclerosis: role in research and precision medicine

Fernandez

Giannarelli

2021

Nat Rev Cardiol

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“…Such an approach could be more appropriate in cases where the references' expression distributions are less aligned. An alternative method, CytofRUV 30 , exploits the concept of pseudo-replicates to remove unwanted variation (RUV) between proteins and cells. Here, cells are grouped into subpopulations using Flow-SOM 31 clustering.…”

Section: Discussionmentioning

confidence: 99%

An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data

et al. 2020

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Mass cytometry (CyTOF) has become a method of choice for in-depth characterization of tissue heterogeneity in health and disease, and is currently implemented in multiple clinical trials, where higher quality standards must be met. Currently, preprocessing of raw files is commonly performed in independent standalone tools, which makes it difficult to reproduce. Here, we present an R pipeline based on an updated version of CATALYST that covers all preprocessing steps required for downstream mass cytometry analysis in a fully reproducible way. This new version of CATALYST is based on Bioconductor’s SingleCellExperiment class and fully unit tested. The R-based pipeline includes file concatenation, bead-based normalization, single-cell deconvolution, spillover compensation and live cell gating after debris and doublet removal. Importantly, this pipeline also includes different quality checks to assess machine sensitivity and staining performance while allowing also for batch correction. This pipeline is based on open source R packages and can be easily be adapted to different study designs. It therefore has the potential to significantly facilitate the work of CyTOF users while increasing the quality and reproducibility of data generated with this technology.

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“…Our algorithm is implemented in the R package ‘CytofRUV’ and is available at:( www.github.com/mtrussart/CytofRUV ) ( Trussart, 2020 ). Installation and R code usage instructions for both the R package and the R-Shiny application can be found on the GitHub page.…”

Section: Methodsmentioning

confidence: 99%

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

Trussart

Teh

Tan

et al. 2020

eLife

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Mass cytometry (CyTOF) is a technology that has revolutionised single cell biology. By detecting over 40 proteins on millions of single cells, CyTOF allows the characterisation of cell subpopulations in unprecedented detail. However most CyTOF studies require the integration of data from multiple CyTOF batches usually acquired on different days and possibly at different sites. To date, the integration of CyTOF datasets remains a challenge due to technical differences arising in multiple batches. To overcome this limitation, we developed an approach called CytofRUV for analysing multiple CyTOF batches which includes an R-Shiny application with diagnostics plots. CytofRUV can correct for batch effects and integrate data from large numbers of patients and conditions across batches, to confidently compare cellular changes and correlate these with clinically relevant outcomes.

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CytofRUV: Removing unwanted variation to integrate multiple CyTOF datasets

Cited by 13 publications

References 20 publications

Immune cell profiling in atherosclerosis: role in research and precision medicine

Immune cell profiling in atherosclerosis: role in research and precision medicine

An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data

Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets

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