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Rau_Andrea_CV.tex
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Rau_Andrea_CV.tex
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%!TEX TS-program = xelatex
%!TEX encoding = UTF-8 Unicode
% Awesome CV LaTeX Template for CV/Resume
%
% This template has been downloaded from:
% https://github.com/posquit0/Awesome-CV
%
% Author:
% Claud D. Park <posquit0.bj@gmail.com>
% http://www.posquit0.com
%
%
% Adapted to be an Rmarkdown template by Mitchell O'Hara-Wild
% 23 November 2018
%
% Template license:
% CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
%
%-------------------------------------------------------------------------------
% CONFIGURATIONS
%-------------------------------------------------------------------------------
% A4 paper size by default, use 'letterpaper' for US letter
\documentclass[11pt, a4paper]{awesome-cv}
% Configure page margins with geometry
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% If you would like to change the social information separator from a pipe (|) to something else
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\def\endfirstpage{\newpage}
%-------------------------------------------------------------------------------
% PERSONAL INFORMATION
% Comment any of the lines below if they are not required
%-------------------------------------------------------------------------------
% Available options: circle|rectangle,edge/noedge,left/right
\name{Andrea}{Rau}
\position{Research Director • Directrice de Recherche}
\address{INRAE • French National Research Institute for Agriculture,
Food and Environment}
\mobile{+33 1 34 65 22 82}
\email{\href{mailto:andrea.rau@inrae.fr}{\nolinkurl{andrea.rau@inrae.fr}}}
\homepage{andrea-rau.com}
\orcid{0000-0001-6469-488X}
\googlescholar{9\_\_bzfgAAAAJ}
\github{andreamrau}
\twitter{andreamrau}
% \gitlab{gitlab-id}
% \stackoverflow{SO-id}{SO-name}
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\usepackage{booktabs}
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\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}
%------------------------------------------------------------------------------
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\begin{document}
% Print the header with above personal informations
% Give optional argument to change alignment(C: center, L: left, R: right)
\makecvheader
% Print the footer with 3 arguments(<left>, <center>, <right>)
% Leave any of these blank if they are not needed
% 2019-02-14 Chris Umphlett - add flexibility to the document name in footer, rather than have it be static Curriculum Vitae
\makecvfooter
{January 2023}
{Andrea Rau~~~·~~~Curriculum Vitae}
{\thepage}
%-------------------------------------------------------------------------------
% CV/RESUME CONTENT
% Each section is imported separately, open each file in turn to modify content
%------------------------------------------------------------------------------
\hypertarget{about-me}{%
\section{About me}\label{about-me}}
My research is focused on developing and writing software for sound
statistical methods for genomic and transcriptomic data analysis,
including differential expression analyses, co-expression analyses,
network inference, and integrative multi-omic analyses.
I am a member of the
\href{https://www6.jouy.inra.fr/gabi_eng/}{\textbf{Animal Genetics and
Integrative Biology}} (GABI) research unit (Jouy en Josas, France) in
the Genomics, Biodiversity, Bioinformatics, Statistics (GiBBS) team.
\emph{Keywords}: Analysis of high-throughput sequencing data, mixture
models, supervised classification methods, multi-omic integration, gene
regulatory networks
\emph{Languages}: English (maternal), French (fluent)
\hypertarget{education}{%
\section{Education}\label{education}}
\begin{cventries}
\cventry{Université d’Évry-Val-d’Essonne}{HDR in Applied Mathematics}{2017}{Évry, France}{\begin{cvitems}
\item Title: Statistical methods and software for the analysis of transcriptomic data \\ Note: An HDR is the French accreditation to supervise research and represents the highest French academic qualification level based on independent scholarship. It is reviewed by and defended before an academic committee.
\end{cvitems}}
\cventry{Purdue University}{PhD in Statistics}{2007-2010}{West Lafayette, Indiana, USA}{\begin{cvitems}
\item Title: Reverse engineering gene regulatory networks using genomic time-course data \\ Advisors: Rebecca W. Doerge, Jean-Louis Foulley, and Florence Jaffrézic
\end{cvitems}}
\cventry{Purdue University}{MS in Applied Statistics}{2005-2007}{West Lafayette, Indiana, USA}{\begin{cvitems}
\item Internship: Time series modeling of advertising interventions on pharmacy sales (Walgreens; Deerfield, Illinois, USA)
\end{cvitems}}
\cventry{Saint Olaf College}{BA in French and Mathematics (concentration in Statistics)}{2001-2005}{Northfield, Minnesota, USA}{\begin{cvitems}
\item Internship: pharmacokinetic analysis of Phase I clinical trial data using a limited-sample model (Mayo Clinic; Rochester, Minnesota, USA)
\end{cvitems}}
\end{cventries}
\hypertarget{work-experience}{%
\section{Work experience}\label{work-experience}}
\begin{cventries}
\cventry{INRAE}{Research Director (Directrice de Recherche)}{2023-present}{Jouy-en-Josas, France}{}\vspace{-4.0mm}
\cventry{INRAE}{Research Scientist (Chargée de Recherche)}{2011-2022}{Jouy-en-Josas, France}{}\vspace{-4.0mm}
\cventry{Medical College of Wisconsin (4 months)}{Adjunct Assistant Professor}{2019}{Milwaukee, Wisconsin, USA}{}\vspace{-4.0mm}
\cventry{Zilber School of Public Health, University of Wisconsin-Milwaukee (20 months)}{AgreenSkills+ Visiting Scholar}{2017-2019}{Milwaukee, Wisconsin, USA}{}\vspace{-4.0mm}
\cventry{Zilber School of Public Health, University of Wisconsin-Milwaukee (6 weeks)}{Visiting Scholar}{2016}{Milwaukee, Wisconsin, USA}{}\vspace{-4.0mm}
\cventry{Ensai}{Adjunct Assistant Professor}{2012-2017}{Rennes, France}{}\vspace{-4.0mm}
\cventry{Inria - Île-de-France}{Post-doctoral researcher}{2010-2011}{Orsay, France}{}\vspace{-4.0mm}
\cventry{Department of Statistics, Purdue University (R. W. Doerge}{Research assistant}{2008-2010}{West Lafayette, Indiana, USA}{}\vspace{-4.0mm}
\cventry{Department of Statistics, Purdue University}{Consultant in the Statistical Consulting Service}{2007}{West Lafayette, Indiana, USA}{}\vspace{-4.0mm}
\end{cventries}
\hypertarget{awards}{%
\section{Awards}\label{awards}}
\begin{cvhonors}
\cvhonor{}{Graduate Women in Science Programs travel award}{2010}{\rightarrow}
\cvhonor{}{Student travel award, Conference on Applied Statistics in Agriculture at Kansas State University}{2010}{\rightarrow}
\cvhonor{}{Honorable mention, Gertrude M. Cox Scholarship}{2009}{\rightarrow}
\cvhonor{}{A.H. Ismail Interdisciplinary Program doctoral research travel award}{2009}{\rightarrow}
\end{cvhonors}
\hypertarget{professional-organizations}{%
\section{Professional organizations}\label{professional-organizations}}
\begin{cvhonors}
\cvhonor{}{Femmes \& Sciences}{2022-present}{F\&S}
\cvhonor{}{Société Française de la Statistique}{2011-present}{SFdS}
\cvhonor{}{American Statistical Association}{2005-present}{ASA}
\end{cvhonors}
\hypertarget{dissertations-books-book-chapters}{%
\section{Dissertations, books \& book
chapters}\label{dissertations-books-book-chapters}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
Duranthon, V., Araújo, S., Palma, M., \textbf{Rau, A.}, Matzapetakis,
M., and Almeida, A. (2021) Rabbit research in the post-genomic era:
transcriptome, proteome, and metabolome analysis. \emph{In: The
Genetics and Genomics of the Rabbit}, Ed. L. Fontanesi.
\item
\textbf{Rau, A.} (2017) Statistical methods and software for the
analysis of transcriptomic data. \emph{HDR thesis}, Université d'Évry
Val-d'Essonne.
\item
Martin-Magniette, M.-L., Maugis-Rabusseau, C. and \textbf{Rau, A.}
(2017) Clustering of co-expressed genes. \emph{In: Model Choice and
Model Aggregation}, Ed. F. Bertrand, J.-J. Droesbeke, G. Saporta, C.
Thomas-Agnan.
\item
Albert, I., Ancelet, S., David, O., Denis, J.-B., Makowski, D.,
Parent, É., \textbf{Rau, A.}, and Soubeyrand, S. (2015) Initiation à
la statistique bayésienne : Bases théoriques et applications en
alimentation, environnement, épidémiologie et génétique.
\emph{Éditions Ellipses}, collection références sciences.
\item
\textbf{Rau, A.} (2010) Reverse engineering gene networks using
genomic time-course data.. \emph{PhD thesis}, Purdue University.
\end{enumerate}
\hypertarget{peer-reviewed-publications}{%
\section{Peer-reviewed publications}\label{peer-reviewed-publications}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
Mollandin, F., Gilbert, H., Croiseau, P., and \textbf{Rau, A.} (2022)
Accounting for overlapping annotations in genomic prediction models of
complex traits. \emph{BMC Bioinformatics}, 23:65.
\url{https://dx.doi.org/10.1186/s12859-022-04914-5}
\item
Mazurier, M., Drouaud, J., Bahrman, N., \textbf{Rau, A.},
Lejeune-Hénaut, I., Delbreil, B., and Legrand, S. (2022) Integrated
sRNA-seq and RNA-seq analyses reveal a microRNA regulation network
involved in cold response in Pisum sativum L. \emph{Genes}, 13:1119.
\url{https://dx.doi.org/10.3390/genes13071119}
\item
\textbf{Rau, A.}, Passet, B., Castille, J., Asset, A., Lecardonnel,
J., Moroldo, M., Jaffrézic, F., Laloë, D., Moazami-Goudarzi, K., and
Vilotte, J.-L. (2022) Potential genetic robustness of Prnp and Sprn
double knockout mouse embryos towards ShRNA-lentiviral inoculation.
\emph{Veterinary Research}, 53:54.
\url{https://dx.doi.org/10.1186/s13567-022-01075-4}
\item
Cazals, A., \textbf{Rau, A.}, Estellé, J., Bruneau, N., Coville,
J.-L., Menanteau, P., Rossignol, M.-N., Jardet, D., Bevilacqua, C.,
Bed'Hom, B., Velge, P., and Calenge, F. (2022) Comparative analysis of
the caecal tonsil transcriptome in two chicken lines experimentally
infected with Salmonella Enteritidis. \emph{PLoS ONE}, 17(8):
e0270012. \url{https://dx.doi.org/10.1371/journal.pone.0270012}
\item
Cazals, A., Estellé, J., Bruneau, N., Coville, J.-L., Menanteau, P.,
Rossignol, M.-N., Jardet, D., Bevilacqua, C., \textbf{Rau, A.},
Bed'Hom, B., Velge, P., and Calenge, F. (2022) Differences in caecal
microbiota composition and Salmonella carriage between experimentally
infected inbred lines of chickens. \emph{Genetics Selection
Evolution}, 54:7. \url{https://dx.doi.org/10.1186/s12711-022-00699-6}
\item
\textbf{Rau, A.}, Manansala, R., Flister, M. J., Rui, H., Jaffrézic,
F., Laloë, D., and Auer, P. L. (2022) Individualized multi-omic
pathway deviation scores using multiple factor analysis.
\emph{Biostatistics}, 23(2):362-379.
\url{https://dx.doi.org/10.1093/biostatistics/kxaa029}
\item
\textbf{Rau, A.} (2021) Cooking up knowledge from big data using data
science. \emph{Frontiers in Young Minds}, 9:632923.
\url{https://dx.doi.org/10.3389/frym.2021.632923}
\item
Mollandin, F., \textbf{Rau, A.}, and Croiseau, P. (2021) An evaluation
of the predictive performance and mapping power of the BayesR model
for genomic prediction. \emph{G3}, jkab225.
\url{https://dx.doi.org/10.1093/g3journal/jkab225}
\item
Sellem, E., Marthey, S., \textbf{Rau, A.}, Jouneau, L., Bonnet, A., Le
Danvic, C., Kiefer, H., Jammes, H., and Schibler, L. (2021) Dynamics
of cattle sperm sncRNAs during maturation, from testis to ejaculated
sperm. \emph{Epigenetics and Chromatin}, 14:24.
\url{https://dx.doi.org/10.1186/s13072-021-00397-5}
\item
Mach, N., Moroldo, M., \textbf{Rau, A.}, Lecardonnel, J., Le Moyec,
L., Robert, C., and Barrey, E. (2021) Understanding the holobiont:
crosstalk between gut microbiota and mitochondria during endurance.
\emph{Frontiers Molecular Biosciences}, 8:656204.
\url{https://dx.doi.org/10.3389/fmolb.2021.656204}
\item
Devogel, N., Auer, P. L., Manansala, R., \textbf{Rau, A.}, and Wang,
T. (2021) A unified linear mixed model for familial relatedness and
population structure in genetic association studies. \emph{Genetic
Epidemiology}, 45(3): 305-315.
\url{https://dx.doi.org/10.1002/gepi.22371}
\item
Cho, Y., \textbf{Rau, A.}, Reiner, A., Auer, P. L. (2020) Mendelian
randomization analysis with survival outcomes. \emph{Genetic
Epidemiology}, 45(1): 16-23.
\url{https://dx.doi.org/10.1002/gepi.22354}
\item
Sellem, E., Marthey, S., \textbf{Rau, A.}, Jouneau, L., Bonnet, A.,
Perrier, J.-P., Fritz, S., Le Danvic, C. Boussaha, M., Kiefer, H.,
Jammes, H., Schiblier, L. (2020) A comprehensive overview of bull
sperm-borne small non-coding RNAs and their diversity in six breeds.
\emph{Epigenetics and Chromatin}, 13:19.
\url{https://dx.doi.org/10.1186/s13072-020-00340-0}
\item
Godichon-Baggioni, A., Maugis-Rabusseau, C. and \textbf{Rau, A.}
(2020) Multi-view cluster aggregation and splitting, with an
application to multi-omic breast cancer data. \emph{Annals of Applied
Statistics}, 14:2, 752-767.
\url{https://dx.doi.org/10.1214/19-AOAS1317}
\item
Jehl, F., Désert, C., Klopp, C., Brenet, M., \textbf{Rau, A.}, Leroux,
S., Boutin, M., Muret, K., Blum, Y., Esquerré, D., Gourichon, D.,
Burlot, T., Collin, A., Pitel, F., Benani, A., Zerjal, T., Lagarrigue,
S. (2019) Chicken adaptive response to low energy diet: main role of
the hypothalamic lipid metabolism revealed by a phenotypic and
multi-tissue transcriptomic approach. \emph{BMC Genomics}, 20.
\url{https://dx.doi.org/10.1186/s12864-019-6384-8}
\item
Foissac, S., Djebali, S., Munyard, K., Villa-Vialaneix, N.,
\textbf{Rau, A.}, Muret, K., Esquerre, D., Zytnicki, M., Derrien, T.,
Bardou, P., Blanc, F., Cabau, C., Crisci, E., Dhorne-Pollet, S.,
Drouet, F., Gonzales, I., Goubil, A., Lacroix-Lamande, S., Laurent,
F., Marthey, S., Marti-Marimon, M., Momal-Leisenring, R., Mompart, F.,
Quere, P., Robelin, D., San Cristobal, M., Tosser-Klopp, G.,
Vincent-Naulleau, S., Fabre, S., Pinard-Van der Laan, M.-H., Klopp,
C., Tixier-Boichard, M., Acloque, H., Lagarrigue, S., Giuffra, E.
(2019) Multi-species annotation of transcriptome and chromatin
structure in domesticated animals. \emph{BMC Biology}, 18:48.
\url{https://dx.doi.org/10.1186/s12915-019-0726-5}
\item
Dhara, S., \textbf{Rau, A.}, Flister, M., Recka, N., Laiosa, M., Auer,
P., and Udvadia, A. (2019) Cellular reprogramming for successful CNS
axon regeneration is driven by a temporally changing cast of
transcription factors. \emph{Scientific Reports}, 9:14198.
\url{https://dx.doi.org/10.1038/s41598-019-50485-6}
\item
\textbf{Rau, A.}, Dhara, S., Udvadia, A., and Auer, P. (2019)
Regeneration Rosetta: An interactive web application to explore
regeneration-associated gene expression and chromatin accessibility.
\emph{G3: Genes\textbar Genomes\textbar Genetics}, 9(12): 3953-3959.
\url{https://dx.doi.org/10.1534/g3.119.400729}
\item
Plasterer, C., Tsaih, S.-W., Lemke, A., Schilling, R., Dwinell, M.,
\textbf{Rau, A.}, Auer, P., Rui, H., Flister, M.J. (2019)
Identification of a rat mammary tumor risk locus that is syntenic with
the commonly amplified 8q12.1 and 8q22.1 regions in human breast
cancer patients. \emph{G3: Genes\textbar Genomes\textbar Genetics},
9(5): 1739-1743. \url{https://dx.doi.org/10.1534/g3.118.200873}
\item
Ramayo-Caldas, Y., Zingaretti, L., Bernard, A., Estellé, J. Popova,
M., Pons, N., Bellot, P., Mach, N., \textbf{Rau, A.}, Roume, H.,
Perez-Encisco, M., Faverdin, P., Edouard, N., Dusko, S., Morgavi, D.P.
and Renand, G. (2019) Identification of rumen microbial biomarkers
linked to methane emission in Holstein dairy cows. \emph{Journal of
Animal Breeding and Genetics}, 137:49-59.
\url{https://dx.doi.org/10.1111/jbg.12427}
\item
\textbf{Rau, A.}, Flister, M. J., Rui, H. and Livermore Auer, P.
(2019) Exploring drivers of gene expression in The Cancer Genome
Atlas. \emph{Bioinformatics}, 35(1): 62-68.
\url{https://dx.doi.org/10.1093/bioinformatics/bty551}
\item
Godichon-Baggioni, A., Maugis-Rabusseau, C. and \textbf{Rau, A.}
(2018) Clustering transformed compositional data using K-means, with
applications in gene expression and bicycle sharing system data.
\emph{Journal of Applied Statistics}, 46(1):47-65.
\url{https://dx.doi.org/10.1080/02664763.2018.1454894}
\item
\textbf{Rau, A.} and Maugis-Rabusseau, C. (2018) Transformation and
model choice for RNA-seq co-expression analysis. \emph{Briefings in
Bioinformatics}, bbw128. \url{https://dx.doi.org/10.1093/bib/bbw128}
\item
Verrier, E., Genet, C., Laloë, D., Jaffrézic, J., \textbf{Rau, A.},
Esquerre, D., Dechamp, N., Ciobataru, C., Hervet, C., Krieg, F.,
Quillet, E., Boudinot, P. (2018) Genetic and transcriptomic analyses
provide new insights on the early antiviral response to VHSV in
resistant and susceptible rainbow trout. \emph{BMC Genomics}, 19:482.
\url{https://dx.doi.org/10.1186/s12864-018-4860-1}
\item
Maroilley, T., Berri, M., Lemonnier, G., Esquerré, D., Chevaleyre, C.,
Mélo, S., Meurens, F., Coville, J.L., Leplat, J.J, \textbf{Rau, A.},
Bed'hom, B., Vincent-Naulleau, S., Mercat, M.J., Billon, Y., Lepage,
P., Rogel-Gaillard, C., and Estellé, J. (2018) Immunome differences
between porcine ileal and jejunal Peyer's patches revealed by global
transcriptome sequencing of gut-associated lymphoid tissues.
\emph{Scientific Reports}, 8:9077.
\url{https://dx.doi.org/10.1038/s41598-018-27019-7}
\item
Mondet, F., \textbf{Rau, A.}, Klopp, C., Rohmer, M. Severac, D., Le
Conte, Y., and Alaux, C. (2018) Transcriptome profiling of the
honeybee parasite Varroa destructor provides new biological insights
into the mite adult life cycle. \emph{BMC Genomics}, 19:328.
\url{https://dx.doi.org/10.1186/s12864-018-4668-z}
\item
He, B., Tjhung, K., Bennett, N., Chou, Y., \textbf{Rau, A.}, Huang,
J., and Derda, R. (2018) Compositional bias in naïve and
chemically-modified phage-displayed libraries uncovered by paired-end
deep sequencing. \emph{Scientific Reports}, 8:1214.
\url{https://dx.doi.org/10.1038/s41598-018-19439-2}
\item
Monneret, G., Jaffrézic, F., \textbf{Rau, A.}, Zerjal, T. and Nuel, G.
(2017) Identification of marginal causal relationships in gene
networks from observational and interventional expression data.
\emph{PLoS One}, 12(3): e0171142.
\url{https://dx.doi.org/10.1371/journal.pone.0171142}
\item
Sauvage, C., \textbf{Rau, A.}, Aichholz, C., Chadoeuf, J., Sarah, G.,
Ruiz, M., Santoni, S., Causse, M., David, J., Glémin, S. (2017)
Domestication rewired gene expression and nucleotide diversity
patterns in tomato. \emph{The Plant Journal}, 91(4):631-645.
\url{https://dx.doi.org/10.1111/tpj.13592}
\item
Rigaill, G., Balzergue, S., Brunaud, V., Blondet, E., \textbf{Rau,
A.}, Rogier, O., Caius, J., Maugis-Rabusseau, C., Soubigou-Taconnat,
L., Aubourg, S., Lurin, C., Martin-Magniette, M.-L., and Delannoy, E.
(2016) Synthetic datasets for the identification of key ingredients
for RNA-seq differential analysis. \emph{Briefings in Bioinformatics},
19(1):65-76. \url{https://dx.doi.org/10.1093/bib/bbw092}
\item
Gallopin, M., Celeux, G., Jaffrézic, F., \textbf{Rau, A.} (2015) A
model selection criterion for model-based clustering of annotated gene
expression data. \emph{Statistical Applications in Genetics and
Molecular Biology}, 14(5): 413-428.
\url{https://dx.doi.org/10.1515/sagmb-2014-0095}
\item
Monneret, G., Jaffrézic, F., \textbf{Rau, A.}, Nuel, G. (2015)
Estimation d'effets causaux dans les réseaux de régulation génique :
vers la grande dimension. \emph{Revue d'intelligence artificielle},
29(2): 205-227.
\item
\textbf{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.
\emph{Bioinformatics}, 31(9): 1420-1427.
\url{https://dx.doi.org/10.1093/bioinformatics/btu845}
\item
\textbf{Rau, A.}, Marot, G. and Jaffrézic, F. (2014) Differential
meta-analysis of RNA-seq data from multiple studies. \emph{BMC
Bioinformatics}, 16:31.
\url{https://dx.doi.org/10.1186/1471-2105-15-91}
\item
Endale Ahanda, M.-L., Zerjal, T., Dhorne-Pollet, S., \textbf{Rau, A.},
Cooksey, A., and Giuffra, E. (2014) Impact of the genetic background
on the composition of the chicken plasma miRNome in response to a
stress. \emph{PLoS One}, 9(12): e114598.
\url{https://dx.doi.org/10.1371/journal.pone.0114598}
\item
Nuel, G., \textbf{Rau, A.}, and Jaffrézic, F. (2013) Using pairwise
ordering preferences to estimate causal effects in gene expression
from a mixture of observational and intervention experiments..
\emph{Quality Technology and Quantitative Management}, 11(1):23-37.
\url{https://dx.doi.org/10.1080/16843703.2014.11673323}
\item
\textbf{Rau, A.}, Jaffrézic, F., and Nuel, G. (2013) Joint estimation
of causal effects from observational and intervention gene expression
data. \emph{BMC Systems Biology}, 8:51.
\url{https://dx.doi.org/10.1186/1752-0509-7-111}
\item
Gallopin, M. \textbf{Rau, A.}, and Jaffrézic, F. (2013) A hierarchical
Poisson log-normal model for network inference from RNA sequencing
data. \emph{PLoS One}, 8(10): e77503.
\url{https://dx.doi.org/10.1371/journal.pone.0077503}
\item
\textbf{Rau, A.}, Gallopin, M., Celeux, G., and Jaffrézic, F. (2013)
Data-based filtering for replicated high-throughput transcriptome
sequencing experiments. \emph{Bioinformatics}, 29(17): 2146-2152.
\url{https://dx.doi.org/10.1093/bioinformatics/btt350}
\item
Dillies, M.-A., \textbf{Rau, A.}, Aubert, J., Hennequet-Antier, C.,
Jeanmougin, M., Servant, N., Keime, C., Marot, G., Castel, D.,
Estelle, J., Guernec, G., Jagla, B., Jouneau, L., Laloë, D., Le Gall,
C., Schaëffer, B., Charif, D., Le Crom, S., Guedj, M., and Jaffrézic,
F. (2013) A comprehensive evaluation of normalization methods for
Illumina high-throughput RNA sequencing data analysis. \emph{Briefings
in Bioinformatics}, 14(6): 671-683.
\url{https://dx.doi.org/10.1093/bib/bbs046}
\item
Brenault, P., Lefevre, L. \textbf{Rau, A.}, Laloë, D., Pisoni, G.,
Moroni, P., Bevilacquia, C. and Martin, P. (2013) Contribution of
mammary epithelial cells to the immune response during early stages of
a bacterial infection to Staphylococcus aureus. \emph{Veterinary
Research}, 45:16. \url{https://dx.doi.org/10.1186/1297-9716-45-16}
\item
\textbf{Rau, A.}, Jaffrézic, F., Foulley, J.-L., and Doerge, R. W.
(2012) Reverse engineering gene regulatory networks using approximate
Bayesian computation. \emph{Statistics and Computing}, 22: 1257-1271.
\url{https://dx.doi.org/10.1007/s11222-011-9309-1}
\item
\textbf{Rau, A.}, Jaffrézic, F., Foulley, J.-L., and Doerge, R. W.
(2010) An empirical Bayesian method for estimating biological networks
from temporal microarray data. \emph{Statistical Applications in
Genetics and Molecular Biology}, 9(1): 9.
\url{https://dx.doi.org/10.2202/1544-6115.1513}
\item
Furth, A., Mandrekar, S., Tan, A. \textbf{Rau, A.}, Felten, S., Ames,
M. Adjei, A. Erlichman, C. and Reid, J. (2008) A limited sample model
to predict area under the drug concentration curve for
17-(allylamino)-17-demethoxygeldanamycin and its active metabolite
17-(amino)-17-demethoxygeldanomycin. \emph{Cancer Chemotherapy
Pharmacology}, 61(1): 39-45.
\url{https://dx.doi.org/10.1007/s00280-007-0443-6}
\end{enumerate}
\hypertarget{pre-prints-technical-reports-other-publications}{%
\section{Pre-prints, technical reports, \& other
publications}\label{pre-prints-technical-reports-other-publications}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
Duran Garzon, C., Chemin, C., \textbf{Rau, A.}, Decaux, B.,
Sellier-Richard, H., Drouaud, J., Soubigou-Taconnat, L., Brunaud, V.,
Martin, M.-L., Palaffre, C., Rayon, C., Lourgant, K., Guénin, S.
Gutierrez, L., Charcosset, A., Coursol, S., and Giauffret, C. (2022)
Integrative analysis of genetic and transcriptomic data reveals
volatile terpenoids biosynthesis genes linked with chilling tolerance.
Submitted.
\item
Noël, A., Dumas, C., Rottier, E., Beslay, D., Costagliola, G., Ginies,
C., Nicolè, F., \textbf{Rau, A.}, Le Conte, Y., and Mondet, F. (2022)
Volatolome of the honey bee (Apis mellifera) worker brood: from egg to
emergence. Submitted.
\item
Mollandin, F., Gilbert, H., Croiseau, P., and \textbf{Rau, A.} (2022)
Capitalizing on complex annotations in Bayesian genomic prediction for
a backcross population of growing pigs. \emph{12th World Congress on
Genetics Applied to Livestock Production (3-8 July 2022)} Rotterdam,
Netherlands.
\item
Mazo, G., Karlis, D., and \textbf{Rau, A.} (2022) A randomized
pairwise likelihood method for complex statistical inferences.
Submitted. \url{https://hal.archives-ouvertes.fr/hal-03126621}
\item
Bruford, M., Leroy, G., Orozco-terWengel, P., \textbf{Rau, A.}, and
Simianer H. (2015) Section B: Molecular tools for exploring genetic
diversity. \emph{The Second Report on the State of the World's Animal
Genetic Resources for Food and Agriculture} FAO Commission on Genetic
Resources for Food and Agriculture.
\item
Nuel, G., \textbf{Rau, A.}, and Jaffrézic, F. (2013) Joint likelihood
calculation for intervention and observational data from a Gaussian
Bayesian network. \emph{arXiv} 1305.0709.
\item
\textbf{Rau, A.}, Celeux, G., Martin-Magniette, M.-L., and
Maugis-Rabusseau, C. (2011) Clustering high-throughput sequencing data
with Poisson mixture models. \emph{Inria Research Report} 7786.
\item
\textbf{Rau, A.}, Jaffrézic, F., Foulley, J.-L., and Doerge, R. W.
(2010) Approximate Bayesian approaches for reverse engineering
biological networks. \emph{Proceedings of the Kansas State University
Conference on Applied Statistics in Agriculture} Manhattan, Kansas.
\item
\textbf{Rau, A.} (2008) Success of Volunteer Statistical Consulting
Service Leads to Expanded Network. \emph{The Statistical Consultant}
25(1).
\item
\textbf{Rau, A.} (2008) STATCOM Network Engages Growing Number of
Student Volunteers. \emph{Newsletter for the Section on Statistical
Education} 13(1).
\item
\textbf{Rau, A.} (2008) Success of Statistical Service Leads to
Expanded Network. \emph{Amstat News} April 2008.
\end{enumerate}
\hypertarget{conference-presentations}{%
\section{Conference presentations}\label{conference-presentations}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
\textbf{(Invited talk) Leveraging multi-omic data for integrative
exploratory and predictive analyses}\\
Journées Math Bio Santé du GDR MATHSAV @ Besançon (2022-10-06)
\item
\textbf{(Poster) A hierarchical Bayesian mixture model for predicting
phenotypes from genomic data with prior biological information}\\
Working Group on Model-Based Clustering Summer Session @ virtual
(2022-07-26)
\item
\textbf{(Invited talk) Mixture models as a useful tool for identifying
co-expressed genes from RNA-seq data}\\
MiMo Workshop on mixture models @ virtual (2021-04-08)
\item
\textbf{(Invited keynote) Integrative and interactive analyses of
multi-omics data}\\
JOBIM 2020 @ virtual (2020-07-02)
\item
\textbf{(Invited talk) Individualized multi-omic pathway deviation
scores using multiple factor analysis}\\
EuroBioc 2019 @ Brussels, Belgium (2019-12-09)
\item
\textbf{(Poster) Integrative methods for multi-omic data reveal
multi-level gene and pathway regulation}\\
AgreenSkills+ annual meeting @ Brussels, Belgium (2019-04-12)
\item
\textbf{coseq, An R/Bioconductor package for co-expression analyses of
RNA-seq data}\\
Plant and Animal Genomes (PAG) XXVI @ San Diego, California, USA
(2018-01-15)
\item
\textbf{(Invited talk) Model-based clustering to identify co-expressed
genes from high-throughput sequencing data}\\
Working Group on Model-Based Clustering @ Perugia, Italy (2017-07-20)
\item
\textbf{Clustering transformed compositional data using coseq}\\
useR!2017 @ Brussels, Belgium (2017-07-05)
\item
\textbf{(Invited talk, FAANG workshop) An update on the FAANG pilot
project FR-AgENCODE}\\
Plant and Animal Genomes (PAG) XXVI @ San Diego, California, USA
(2017-01-12)
\item
\textbf{(Invited talk) Statistical tools to identify and visualize
co-expression clusers from RNA-seq data}\\
INRA RNA-seq day @ Avignon (2016-11-17)
\item
\textbf{Identifying marginal causal relationships in gene networks
from observational and interventional expression data}\\
Joint Statistical Meetings of the American Statistical Association @
Chicago (2016-07-31)
\item
\textbf{(Invited talk) Experimental design in 'omics studies}\\
2nd International Symposium on Microgenomics, Technical Workshop @
Jouy-en-Josas (2016-05-31)
\item
\textbf{HTSCluster, a mixture-based approach for co-expression
analyses of RNA-seq data}\\
15th Workshop: Statistical Methods for Post-Genomic Data @ Munich
(2015-02-13)
\item
\textbf{HTSDiff -- More sensitive differential analysis of RNA-seq
data}\\
Statistical analysis of RNA-seq data: Advances and challenges @ Paris
(2013-11-26)
\item
\textbf{HTSFilter -- Data-based filtering for replicated
high-throughput sequencing experiments}\\
Deuxièmes rencontres R @ Lyon (2013-06-28)
\item
\textbf{(Invited round table) Statistics applied to RNA-seq}\\
Journée de la transcriptome végétale de l'URGV-Genopole @ Evry
(2013-05-16)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
StatSeq meeting on genetical genomics @ Paris (2013-03-28)
\item
\textbf{(Invited talk) A comprehensive evaluation of normalization
methods for high-throughput RNA sequencing data analysis}\\
Journée APLIBIO (Alliance des PLates-formes Île-de-France de
BIOinformatique) @ Paris (2012-10-11)
\item
\textbf{Clustering high-throughput sequencing data using Poisson
mixture models}\\
Joint Statistical Meetings of the American Statistical Association @
San Diego, California (2012-07-31)
\item
\textbf{Clustering high-throughput sequencing data using Poisson
mixture models}\\
12th Workshop: Statistical Methods for Post-Genomic Data @ Lyon
(2012-01-26)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation}\\
11th Workshop: Statistical Methods for Post-Genomic Data @ Paris
(2011-01-27)
\item
\textbf{Approximate Bayesian methods for reverse engineering
biological networks}\\
Conference on Applied Statistics in Agriculture @ Manhattan, Kansas
(2010-04-26)
\item
\textbf{Reverse-Engineering Gene Networks from Microarray Data with
Dynamic Bayesian Networks}\\
GENESYS Satellite Meeting at the European Conference on Complex
Systems @ Warwick, UK (2009-09-22)
\item
\textbf{Using Dynamic Bayesian Networks with Hidden States to Infer
Gene Regulatory Networks}\\
Joint Statistical Meetings of the American Statistical Association @
Washington, DC (2009-08-05)
\item
\textbf{(Poster) Reverse-Engineering Genetic Regulatory Interactions
from Transcriptomic Data using Dynamic Bayesian Networks}\\
2nd Biennial Workshop on Statistical Bioinformatics and Stochastic
Systems Biology @ Newcastle, UK (2009-05-18)
\item
\textbf{(Poster) An Empirical Bayes Approach to Inferring Genetic
Regulatory Interactions with Dynamic Bayesian Networks}\\
Conference on Applied Statistics in Agriculture @ Manhattan, Kansas
(2009-04-19)
\item
\textbf{(Poster) An Empirical Bayes Approach to Inferring Genetic
Regulatory Interactions with Dynamic Bayesian Networks}\\
Gordon Conference on Quantitative Genetics and Genomics @ Galveston,
Texas (2009-02-22)
\item
\textbf{(Poster) Seven Years of StatCom at Purdue: Managing a Growing
Number of Student Volunteers}\\
Joint Statistical Meetings of the American Statistical Association @
Denver, Colorado (2008-08-04)
\end{enumerate}
\hypertarget{seminar-working-group-presentations}{%
\section{Seminar \& working group
presentations}\label{seminar-working-group-presentations}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item
\textbf{Incorporating multiple annotations in genomic prediction
models}\\
Integration of gene co-expression networks with genomic prediction
(IGEN) Workshop, CIRAD @ Montpellier (2022-12-12)
\item
\textbf{Leveraging multi-omic data for integrative exploratory,
predictive, and network analyses}\\
Séminaire Biogeco @ Bordeaux (2022-09-16)
\item
\textbf{(Poster) Differential network analysis of mixed-type data with
copulae}\\
Journées Scientifiques du Département de Génétique Animale @ Bordeaux
(2022-09-13)
\item
\textbf{Leveraging multi-omic data for integrative exploratory,
predictive, and network analyses}\\
KIM -- Data \& Life Sciences seminar (MUSE) @ Montpellier (2022-05-30)
\item
\textbf{(Invited talk) A randomized pairwise likelihood method for
complex statistical inferences}\\
Séminaire statistique de Paris @ virtual (2022-02-07)
\item
\textbf{Intégration d'annotations biologiques complexes dans les
modèles bayésiens de prédiction génomique -- Evaluation et extension
du modèle BayesRC}\\
SAPS seminar @ virtual (2022-01-21)
\item
\textbf{E pluribus unum -- l'intégration de données à GiBBS pour une
vision unifiée des données hétérogènes complexes}\\
Lundi de SAPS seminar @ virtual (2021-12-13)
\item
\textbf{Leveraging multi-omic data for integrative exploratory,
predictive, and network analyses}\\
NutriNeurO lab seminar @ virtual (2021-11-22)
\item
\textbf{Multi-omic integration for enhanced interpretability in
exploratory analyses}\\
Grenoble Laboratoire Jean Kuntzmann seminar @ virtual (2021-04-29)
\item
\textbf{Happy 20th Birthday, R!}\\
INRAE GiBBS team meeting @ virtual (2020-05-18)
\item
\textbf{Integrative methods for multi-omic data reveal multi-level
gene regulation}\\
AgroParisTech statistics seminar @ Paris, France (2020-01-20)
\item
\textbf{Integrative multivariate methods for multi-omic data}\\
Lundi de GABI seminar @ Jouy en Josas, France (2020-01-13)
\item
\textbf{Integrative methods for multi-omic data reveal multi-level
gene regulation}\\
INRA MaIAGE research seminar @ Jouy en Josas, France (2019-11-18)
\item
\textbf{Integrative methods for multi-omic data reveal multi-level
gene regulation}\\
Journée régionale Genotoul @ Toulouse, France (2019-10-04)
\item
\textbf{Integrative methods for multi-omic data reveal multi-level
gene regulation}\\
EpiFun workshop @ Orléans, France (2019-09-17)
\item
\textbf{Exploring drivers of gene expression in The Cancer Genome
Atlas}\\
Division of Biostatistics Seminar at MCW @ Milwaukee, Wisconsin
(2018-12-04)
\item
\textbf{Co-expression analyses of RNA-seq data in practice with the
R/Bioconductor package coseq}\\
MixStatSeq Workshop on Mixture Models -- Theory and Application @
Paris (2018-06-22)
\item
\textbf{Exploring drivers of gene expression in The Cancer Genome
Atlas}\\
Research seminar series, Joseph J. Zilber School of Public Health @
Milwaukee, WI (2018-04-09)
\item
\textbf{Exploring drivers of gene expression in The Cancer Genome
Atlas}\\
Physiology Department Seminar at MCW @ Milwaukee, WI (2018-03-28)
\item
\textbf{Easy interactivity in R with (gg)plotly and Shiny}\\
INRA national bioinformatics workshop @ Dijon (2017-06-13)
\item
\textbf{Challenges in data integration}\\
SAPS doctoral school -- Experimental animal biology and predictive
modelisation @ Jouy en Josas, France (2017-03-17)
\item
\textbf{Transformation, model choice, and visualization for RNA-seq
co-expression}\\
Seminar at the Human and Molecular Genetics Center, Milwaukee College
of Medicine @ Milwaukee, WI (2016-09-10)
\item
\textbf{Transformation, model choice, and visualization for RNA-seq
co-expression}\\
Seminar at the Zilber School of Public Health @ Milwaukee, WI
(2016-09-09)
\item
\textbf{Poisson mixtures with slope heuristics and visualization tools
for RNA-seq co-expression}\\
Groupe de travail de statistiques du LMRS @ Rouen (2016-05-12)
\item
\textbf{From genotype to phenotype -- what statistical methods to
integrate heterogeeous data?}\\
INRA national bioinformatics workshop @ Toulouse (2016-03-22)
\item
\textbf{Integration of heterogeneous 'omics data}\\
SAPS doctoral school: Experimental animal biology and predictive
modelisation @ Jouy en Josas, France (2016-03-11)
\item
\textbf{Poisson mixture models and visualization tools for RNA-seq
co-expression}\\
INRA NGS club @ Jouy en Josas, France (2016-03-08)
\item
\textbf{Poisson mixtures with slope heuristics and visualization tools
for RNA-seq co-expression}\\
MAP5 seminar at Université Paris-Descartes @ Paris (2016-01-29)
\item
\textbf{Model selection in mixture model based classification --
Applications in biostatistics}\\
4th Annual SFdS Young Statisticians and Probabilists Day @ Paris
(2016-01-22)
\item
\textbf{Statistical analysis of microarray and RNA-seq data}\\
Seminar at Toulouse Mathematics Institute (IMT) @ Toulouse
(2015-11-17)
\item
\textbf{Integrative clustering and classification in multiple
heterogeneous data}\\
Statomique seminar @ Paris (2015-11-09)
\item
\textbf{RNA-seq co-expression analysis using mixture models}\\
NETBIO working group @ Paris (2015-09-29)
\item
\textbf{HTSCluster, a mixture-based approach for co-expression
analyses of RNA-seq data}\\
Cirad seminar @ Montpellier (2015-09-25)
\item
\textbf{Slope heuristics -- the missing ingredient for identifying
co-expressed genes from RNA-seq data}\\
SELECT seminar @ Orsay (2014-10-16)
\item
\textbf{HTSFilter -- filtering replicated RNA-seq data using a
data-driven approach}\\
Statistics for Systems Biology (SSB) seminar @ Evry (2013-11-12)
\item
\textbf{Reinforcing the biology-statistics feedback loop with tools
for genomic data analysis}\\
Seminar at INRA-GABI @ Jouy en Josas, France (2013-11-04)
\item
\textbf{HTSAnalysis -- a suite of R/Bioconductor packages for the
analysis of RNA-seq data}\\
Statistics for Integrative Biology (SIB) seminar @ Rennes (2013-10-29)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
NETBIO working group @ Paris (2013-09-20)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
Statistique et Santé working group @ Paris (2013-06-24)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
AppliBUGS Workshop @ Paris (2013-06-20)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
Statistics seminar @ Toulouse (2013-06-18)
\item
\textbf{Joint estimation of causal effects from observational and
intervention gene expression data}\\
Statistics for Integrative Biology seminar @ Rennes (2013-02-22)
\item
\textbf{Differential analysis of RNA-seq data by unsupervised
classification}\\
Assemblée générale PEPI IBIS @ Toulouse (2012-12-07)
\item
\textbf{Independent data-based filtering for replicated
high-throughput sequencing experiments}\\
Statomique seminar @ Lyon (2012-11-27)
\item
\textbf{Clustering high-throughput sequencing data using Poisson
mixture models}\\
LGC and SAGA seminar at INRA @ Toulouse (2012-06-25)
\item
\textbf{Clustering high-throughput sequencing data using Poisson
mixture models}\\
SSB working group seminar @ Jouy en Josas, France (2012-06-19)
\item
\textbf{Inferring gene regulatory networks with hidden variables using
state space models}\\
MIA Biological network inference methodological working group meeting
@ Paris (2012-02-09)
\item
\textbf{Exploring the identifiability of gene regulatory networks with
approximate Bayesian computation}\\
AppliBugs Workshop @ Paris (2011-12-09)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
Seminar at the Institut de Recherche Mathématique Avancée @ Strasbourg
(2011-05-24)
\item
\textbf{Reverse Engineering Gene Networks -- A Statistician's
Perspective}\\
Seminar at the Unité de Recherche en Génomique Végétale @ Evry
(2011-04-07)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
Seminar at the Institut de Mathématiques de Luminy @ Marseille
(2011-04-04)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
Seminar at the Laboratoire Statistique et Génome @ Evry (2011-03-22)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
Seminar at the équipe Génétique et Génomique Statistique @ Le Kremlin
Bicêtre (2011-03-02)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
Rencontre de statistique autour des modèles hiérarchiques @ Strasbourg
(2011-01-14)
\item
\textbf{Reverse Engineering Gene Networks Using Approximate Bayesian
Computation (ABC)}\\
INA P-G, Paris Descartes, and SELECT working group @ Paris
(2010-10-18)
\item
\textbf{Approximate Bayesian methods for reverse engineering
biological networks}\\
Bioinformatics seminar at Purdue University @ West Lafayette, Indiana
(2010-04-13)
\item
\textbf{Inférence sur les réseaux génomiques par des modèles
espace-état}\\
Seminar at the AgroParisTech @ Paris (2009-06-22)
\item
\textbf{Inférence sur les réseaux génomiques par des modèles
espace-état}\\
Seminar at the UMR GABI-INRA @ Jouy-en-Josas (2009-06-15)
\item
\textbf{Reverse Engineering Gene Regulatory Networks}\\
Ph.D.~student seminar, INRA Département de Génétique Animale @
Jouy-en-Josas (2009-03-23)
\item
\textbf{(Poster) Inferring Gene Regulatory Network through Linear
Feedback State Space Models}\\
Ph.D.~student seminar, INRA Département de Génétique Animale @
Toulouse (2008-03-20)
\end{enumerate}
\hypertarget{participation-in-working-groups}{%
\section{Participation in working
groups}\label{participation-in-working-groups}}
\begin{itemize}
\tightlist
\item
Statomique (2009-present)
\item
Netbio (2014-present)
\end{itemize}
\hypertarget{software}{%
\section{Software}\label{software}}
\begin{enumerate}
\def\labelenumi{\arabic{enumi}.}
\tightlist
\item