Main research interests
RNA-seq analysis, gene network inference, mixture models, integrative data analysis
Selection of 3 major recent publications
Rau, A., Maugis-Rabusseau, C., Martin-Magniette, M.-L., Celeux, G. (2015) Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models. Bioinformatics, 31(9): 1420-1427.
Rau, A., Marot, G. and Jaffrézic, F. (2014) Differential meta-analysis of RNA-seq data from multiple studies. BMC Bioinformatics, 15:91.
Rau, A., Gallopin, M., Celeux, G., and Jaffrézic, F. (2013). Data-based filtering for replicated high-throughput transcriptome sequencing experiments. Bioinformatics 29(17): 2146-2152.
Andrea Rau is a research scientist at the French National Institute for Agronomical Research (INRA) in the Animal Genetics and Integrative Biology research unit (Populations, Statistics, and Genome team). She received her Ph.D. in 2010 from Purdue University (West Lafayette, Indiana, USA) for the development of statistical methods to infer gene regulatory networks from time-course microarray data. Following this, she did a one-year post-doctoral fellowship in the Model Selection and Statistical Learning (Select) team at Inria Saclay -- Île-de-France, with a focus on clustering RNA-seq data to identify groups of co-expressed genes. She was recruited as a researcher at INRA in the Animal Genetics department in 2011.
Dr. Rau's research interests focus on the development of appropriate statistical methodology for the analysis of high-dimensional genomic and transcriptomic data, and the implementation of these methods in open-source software packages. She is an active user and developer of the R programming language, and has developed or co-developed six R packages. Today, her work centers on the inference of causal regulatory networks from gene knock-out and knock-down experiments, as well as differential and co-expression analyses of RNA-seq data. Since 2014, she has been a work-package leader in the French National Research Agency (ANR) grant MixStatSeq, which seeks to develop mixture-based procedures for the statistical analysis of RNA-seq data.
Since 2011, Dr. Rau has worked in close collaboration with biologists on interdisciplinary problems at the interface of statistics and biology. She enjoys training students, and has taught courses on the statistical analysis of 'omics data at a variety of levels, from Master's level students to fellow researchers. She is also an active participant in the Statomique consortium, which gathers together more than 40 statisticians and bioinformaticians involved in high-throughput 'omics data analysis in France.
GABI, INRA, AgroParisTech
Université Paris Saclay
78350 Jouy en Josas
Tel: + 33(0)18.104.22.168.82