I am a third year Biostatistics PhD student at Penn State University. My current research topic is the inactivation of the X-chromosome (XCI) in females and the associated escape mechanisms. With my PhD advisor, Dr Dajiang Liu, I develop statistical models and software for the prediction of XCI status and study its association with various X-linked diseases and gender biased phenotypes.

Until 2016, I worked as a scientific programmer at the Fred Hutchinson Cancer Research Center in the RGLab where I was a developper and administrator for the ImmuneSpace portal. Additionaly, I handled data analysis as well as the development and maintainenance of R package for various projects.

In 2011, I completed my master degree in Bioinformatics and Biostatistics at Université Paris-Sud. My training ended with a six months internship in the Department of Biochemistry and Biophysics, at Stockholm University under the supervision of Prof. Arne Elofsson.


Following is a list of R packages I developped or am currently maintaining. These packages are available on my GitHub page or the RGLab's GitHub page.


X-chromosome Inactivation inference from bulk RNA-Seq data. Joint modelling of mosaicism and sources of errors in allele specific expression, and prediction of XCI-state at the subject level.



An R API to download an manipulate data from ImmuneSpace. The package uses references classes for efficient caching of the data.

Bioconductor, GitHub


For the analysis of ChIP-Seq data, PICS (Probabilistic Inference for ChIP-Seq) identifies genomic regions bound by transcription factors. The algorithm is implemented in C and makes use of parallel computing.

Bioconductor, GitHub


PING increments on PICS and propose a method for the detection of nucleosome positions for both single-end and paired-end sequencing data. The packages also includes graphic tools for the representation and comparison of results.

Bioconductor, GitHub


This package predicts antibody binding sites on peptides using microarray data.

Bioconductor, GitHub


pepDat is a data package that contains datasets and sample files used for examples and vignettes in the peptide microarray analysis pipeline.

Bioconductor, GitHub


Pviz is an R package for peptide visualisation inspired by and depending on the popular Gviz. It introduces new types of track and extends the existing ones in order to deal with amino-acid based data such as peptide microarray.

Bioconductor, GitHub


Currently a work in progress, LumiR provides S4 structures and functions to manipulate and analyse Luminex Bead Array Multiplex Assay data. It is designed to handle raw data from the three main manufacturer: Luminex, MiraiBio and BioRad.


PING plot

Summary plot of a PING analysis

Pviz plot

Pviz plot of antibody response frequency calculated by pepStat analysis

LumiR plot

Fitting of 5-Parameter Logistic curves using LumiR


  • HIPC-CHI Signatures Project Team, HIPC-I Consortium. Multicohort analysis reveals baseline transcriptional predictors of influenza vaccination responses Science Immunology doi: 10.1126/sciimmunol.aal4656 (2017)

  • Lucia Vojtech, Sangsoon Woo, Sean Hughes, Claire Levy, Lamar Ballweber, Renan Sauteraud, Johanna Strobl, Katharine Westerberg, Raphael Gottardo, Muneesh Tewari and Florian Hladik. Exosomes in human semen carry a distinctive repertoire of small non-coding RNAs with potential regulatory functions Nucleic Acids Research doi: 10.1093/nar/gku347 (2014)

  • Greg C. Imholte, Renan Sauteraud, Bette Korber, Robert T. Bailer, Ellen T. Turk, Xiaoying Shen, Georgia D. Tomaras, John R. Mascola, Richard A. Koup, David C. Montefiori, Raphael Gottardo A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling Journal of Immunological Methods, Volume 395, Issues 1–2, 30 September 2013, Pages 1–13

  • Sangsoon Woo, Xuekui Zhang, Renan Sauteraud, Francois Robert, Raphael Gottardo. PING 2.0: an R/Bioconductor package for nucleosome positioning using next-generation sequencing data. Bioinformatics 29(16): 2049-2050 (2013)

Posters & presentations

  • Male-female subject-specific XCI-adjusted differential gene expression reveals changes in active-X expression of escape genes. ASHG 2018, poster presentation (Reviewer’s choice award). San Diego, CA.

  • Novel Statistical and experimental approaches for quantifying the X chromosome inactivation landscape using RNA-Seq data. ASHG 2017, poster presentation. Orlando, FL.

  • An introduction to ImmuneSpaceR. BioConductor 2016, workshop. San Jose, CA.

  • ImmuneSpaceR for flow cytometry. Cyto 2016, poster presentation. Seattle, WA.

  • ImmuneSpaceR. AAI 2016, poster presentation. Seattle, WA.