Author

Philippe Hauchamps

de Duve InstituteORCID 0000-0003-2865-1852Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Approach:statistical model· 3 Research Focus:dimensionality reduction· 2 Research Focus:software / tool· 2 Research Focus:batch correction / integration· 1 Approach:benchmark study· 1 Assay:CITE-seq· 1 Approach:experimental assay· 1

Frequent Co-Authors

Laurent GattoiD· 3 shared Lin DaniD· 2 shared Simon DelandreiD· 2 shared Stéphane T. TemmermaniD· 2 shared Andrea ViciniiD· 1 shared Babak Bayat· 1 shared Marie Toussaint· 1 shared Mehdi Hamrouni· 1 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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3 shared papersBioinformatics

Laurent GattoORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 23, 2025

MDSvis, a Shiny application for interactive visualisation of Multi Dimensional Scaling projections

Philippe Hauchamps, Andrea Vicini, Laurent Gatto

MDSvis provides an interactive Shiny app for visualizing MDS projections, enabling users to customize and explore high-dimensional data without programming.

DOI 10.1101/2025.06.23.660991

statistical modelexperimental assay

𝕏 PostBluesky

BioinformaticsCytometry Part APeer-reviewedMar 1, 2025

Visual quality control with CytoMDS, a Bioconductor package for low dimensional representation of cytometry sample distances

Philippe Hauchamps, Simon Delandre, Stéphane T. Temmerman…·Laurent Gatto

CytoMDS provides a method for visual quality control of cytometry data by representing samples in low dimensions to detect batch effects and outliers.

8 citations

CITE-seqstatistical model

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedFeb 20, 2024

CytoPipeline & CytoPipelineGUI: An R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data

Philippe Hauchamps, Babak Bayat, Simon Delandre…·Laurent Gatto

The paper introduces two R packages for building and visualizing automated flow cytometry data pre-processing pipelines and demonstrates their use through benchmarking and visualization.

5 citations

statistical modelbenchmark study

𝕏 PostBluesky