(Updated on March 2025)

My research mainly focuses on the development of tools and practices to analyze mass spectrometry-based single-cell proteomics (SCP) data. I achieved several milestones during my PhD at Prof. Laurent Gatto’s lab.

I established the first standardized data structure for mass spectrometry-based single-cell proteomics with the development of scp, an R/Bioconductor package for storing and processing single-cell proteomics data. I am the head maintainer of the sofware which cumulates over 8500 downloads. In parallel, I actively contributed and still am an official maintainer of QFeatures, an R/Bioconductor package to store and process MS-based quantitative data (cumulating over 58000 downloads). You may read more in

Vanderaa & Gatto (2021). Replication of single-cell proteomics data reveals important computational challenges. In Expert Review of Proteomics (Vol. 18, Issue 10, pp. 835–843). Cited by 33.

Next, I created a database of curated data sets that are ready for analysis. The aim of the database is to guide computational development based on real data. I have published the software as another R/Bioconductor package, scpdata. Currently, the database contains 29 data sets and cumulates over 4000 downloads. You can read more in

Vanderaa & Gatto (2023). The Current State of Single‐Cell Proteomics Data Analysis. In Current Protocols (Vol. 3, Issue 1). Cited by 14.

Thanks to scp and scpdata, I replicated various SCP data analyses. I report these replication efforts in my SCP.replication website. Replicating the analysis offered me many benefits. First, I repurposed these replications efforts as didactic material, increasing the visibility of my software. Second, replicating data analyses increases the trust in published results or to highlight potential flaws, effectively moving the field forward. It allowed me to grow an international reputation which materialized in an important collaboration among pioneers of the field, read more in

Gatto, Aebersold, Cox, Demichev, Derks, Emmott, Franks, Ivanov, Kelly, Khoury, Leduc, MacCoss, Nemes, Perlman, Petelski, Rose, Schoof, Van Eyk, Vanderaa, Yates 3rd, Slavov (2023). Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. In Nature Methods (Vol. 20, Issue 3, pp. 375–386). Cited by 101.

A last benefit from replicating analyses was to pinpoint the key challenges of SCP data analysis and the current bottlenecks. One major bottleneck I identified was the high prevalence of missing values. You can find my recommendation on how to handle missing values in SCP data in

Vanderaa & Gatto (2023). Revisiting the Thorny Issue of Missing Values in Single-Cell Proteomics. In Journal of Proteome Research (Vol. 22, Issue 9, pp. 2775–2784). Cited by 15.

Finally, my main achievement was the developement of scplainer, a principled approach that lays the ground for rigourous analysis of SCP data. Since the publication of the preprint, it already initiated several collaborations across the world. To read more

Vanderaa & Gatto (2024). Scplainer: Using Linear Models to Understand Mass Spectrometry-Based Single-Cell Proteomics Data. bioRxiv (submitted, not peer-reviewed).

Thanks to Prof. Laurent Gatto’s mentorship, I developed a strong commitment to open and reproducible science. Prof. Laurent Gatto is internationally renowned for his exemplary research practices concerning open and reproducible science. All my projects and software packages are available on GitHub (https://github.com/cvanderaa and https://github.com/UCLouvain-CBIO/) and my analyses are reproducible through Docker images (https://hub.docker.com/u/cvanderaa, see also https://uclouvain-cbio.github.io/SCP.replication/).

The next goal for me is to unlock SCP for biomedical research as my ultimate goal is to apply my research to help answering tangible health-related questions. Therefore, I joined the lab of Prof. Lieven Clement to extend the current tools. I will solve the key data analysis bottlenecks of current workflows by (1) identifying unknown source of variation through dimension reduction while accounting for technical effects and the high prevalence of missing values; (2) addressing the hierarchical correlation structure of multiple cells within each sample in multi-sample SCP data; and (3) revolutionize SCP data analysis by building tools to infer on differences that go beyond the mean, i.e. for differential variance, skewness, multimodality and presence/absence without relying on harmful imputation strategies. Thanks to Prof. Lieven Clement’s mentorship, I plan to perfect my statistical skills and acquire rigourous method benchmarking practices.

Scientific meetings

You can find a comprehensive list of my attendence to different scientific meetings. Below are some highlights:

  • I was an invited speaker at the European symposium on single-cell proteomics 2024.
  • I presented several short talks: SCP2020, RSG symposium 2020, Eurobioc2020, IB2 research day 2021, EuroBioc2023.
  • I presented several workshops providing hands-on tutorials on my software: Bioc2021, SCP2021, BiocAsia2021. I’m also invited to provide workshops in Strasbourg and Liverpool in 2025.
  • I have presented up to 7 posters during different conferences.

Supervision

I enjoyed supervising the following students:

  • Samuel Grégoire: Master student in Biomedical Sciences
  • Charlotte Léonard: Master student in Applied Mathematics
  • Théo Christopher Borremans: bachelor student in Biology
  • Léopold Guyot: Master student in Bioinformatics

Scientific awards and research funding

  • ASP-FNRS fellowship (graded A+: outstanding, 2019)
  • EURASIP, best poster award, 2018, Tensor-based Signal Processing
  • Best poster award during the de Duve PhD day (2020).

List of software

Software I still maintain

Software I contributed

Reviewing software

I am an official Bioconductor reviewer.

List of publications

First author

  • Vandenbulcke* S, Vanderaa* C, Crook O, Martens L, Clement L. msqrob2TMT: robust linear mixed models for inferring differential abundant proteins in labelled experiments with arbitrarily complex design. bioRxiv. Published online March 29, 2024:2024.03.29.587218. doi:10.1101/2024.03.29.587218

  • Vanderaa C, Gatto L. scplainer: using linear models to understand mass spectrometry-based single-cell proteomics data. bioRxiv. Published online January 10, 2024:2023.12.14.571792. doi:10.1101/2023.12.14.571792

  • Thesis: Vanderaa C. A Principled Approach and Standardised Software for Mass Spectrometry-Based Single-Cell Proteomics Data Analysis. UCL-Université Catholique de Louvain; 2024.

  • Vanderaa C, Gatto L. Revisiting the Thorny Issue of Missing Values in Single-Cell Proteomics. J Proteome Res. 2023;22(9):2775-2784.

  • Vanderaa C, Gatto L. The Current State of Single-Cell Proteomics Data Analysis. Curr Protoc. 2023;3(1):e658.

  • Vanderaa C, Gatto L. Replication of single-cell proteomics data reveals important computational challenges. Expert Rev Proteomics. 2021;18(10):835-843.

Co-author

  • Dzialo MC, Arumugam S, Piampongsant S, Cool L, Vanderaa C, Herrera-Malaver B, et al. Drosophila suzukii and Drosophila melanogaster prefer distinct microbial and plant aroma compounds in a complex fermented matrix. iScience. 2024;27(11):111141.

  • Schreurs M, Piampongsant S, Roncoroni M, Cool L, Herrera-Malaver B, Vanderaa C, et al. Predicting and improving complex beer flavor through machine learning. Nat Commun. 2024;15(1):2368.

  • Grégoire S, Vanderaa C, Ruys SPD, Mazzucchelli G, Kune C, Vertommen D, et al. Mass Spectrometry Based Single Cell Proteomics. Springer US; 2023.

  • Eckenrode KB, Righelli D, Ramos M, Argelaguet R, Vanderaa C, Geistlinger L, et al. Curated single cell multimodal landmark datasets for R/Bioconductor. PLoS Comput Biol. 2023;19(8):e1011324.

  • Gannoun L, De Schrevel C, Belle M, Dauguet N, Achouri Y, Loriot A, et al. Axon guidance genes control hepatic artery development. Development. 2023;150(16). doi:10.1242/dev.201642

  • Gatto L, Aebersold R, Cox J, Demichev V, Derks J, Emmott E, et al. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods. 2023;20(3):375-386.

  • Lecomte S, Devreux J, de Streel G, van Baren N, Havelange V, Schröder D, et al. Therapeutic activity of GARP:TGF-β1 blockade in murine primary myelofibrosis. Blood. 2023;141(5):490-502.

  • Moulis M, Runser SVM, Glorieux L, Dauguet N, Vanderaa C, Gatto L, et al. Identification and implication of tissue-enriched ligands in epithelial-endothelial crosstalk during pancreas development. Sci Rep. 2022;12(1):12498.

  • Goelen T, Sobhy IS, Vanderaa C, Wäckers F, Rediers H, Wenseleers T, et al. Bacterial phylogeny predicts volatile organic compound composition and olfactory response of an aphid parasitoid. Oikos. 2020;129(9):1415-1428.

  • Goelen T, Sobhy IS, Vanderaa C, Boer JG, Delvigne F, Francis F, et al. Volatiles of bacteria associated with parasitoid habitats elicit distinct olfactory responses in an aphid parasitoid and its hyperparasitoid. Funct Ecol. 2020;34(2):507-520.

  • Liénart S, Merceron R, Vanderaa C, Lambert F, Colau D, Stockis J, et al. Structural basis of latent TGF-β1 presentation and activation by GARP on human regulatory T cells. Science. 2018;362(6417):952-956.

Reviewing papers

I reviewed the following articles:

  • One article for Nature Communications (not published)
  • One article for Nature Methods (under revision)
  • One article for Bioinformatics (under revision)
  • (co-revision with Laurent) Kong, Weijia, Harvard Wai Hann Hui, Hui Peng, and Wilson Wen Bin Goh. 2022. “Dealing with Missing Values in Proteomics Data.” Proteomics 22 (23-24): e2200092.
  • (co-revision with Laurent) Li, Wei, Fan Yang, Fang Wang, Yu Rong, Bingzhe Wu, Han Zhang, and Jianhua Yao. 2023. “A Versatile Deep Graph Contrastive Learning Framework for Single-Cell Proteomics Embedding.” bioRxiv.
  • (co-revision with Laurent) Wang, Fang, Chunpu Liu, Jiawei Li, Fan Yang, Jiangning Song, Tianyi Zang, Jianhua Yao, and Guohua Wang.2023. “SPDB: A Comprehensive Resource and Knowledgebase for Proteomic Data at the Single-Cell Resolution.” Nucleic Acids Research.


Attending conferences

2 minute read

In this post, I list all the conferences I have attended and, for some, the material I have presented.