Teaching

2012-2019 Statistical analyses for the interpretation of gene lists and gene network inference, courses/TD (12h), researchers, Agrocampus Ouest Rennes,  website

Description: presentation of functional annotation databases, enrichment test for the functional characterization of lists of genes of interest, gene network inference methods (WGCNA and Glasso package). Application on several real datasets, use of R software.

2017-2019 Statistical analysis of genomic data, course/TD (8h), M1-M2, Université Paris Descartes

Description: Introduction to high throughput technologies, overview of classical data preprocessing methods and statistical methods for the search of differentially expressed genes (Student /limma test, correction for multiple tests), use of R software.

2009-2013 General statistics, TD (48h/year), L3-M1, Agrocampus Ouest Rennes.

Description: descriptive statistics, statistical inference (estimation, hypothesis tests, confidence intervals), variance analysis, simple linear regression; introduction to R software.

2012-2013 Linear model and data analysis, TD (48h), L3-M1, Agrocampus West Rennes

Description: multiple linear regression, analysis of variance, experimental design, exploratory analysis (PCA); use of FactoMineR package in R software.

2012-2013 Statistics and decision support, TD (18h), M1-M2, Agrocampus Ouest Rennes

Description: categorical data modeling (χ test, logistic regression, decision trees); TD with R software.

2012-2013 Biostatistics and introduction to the R language, courses/TD (17h), M1, University of South Brittany, Lorient

Description: Introduction to high throughput technologies, overview of classical data preprocessing methods and statistical methods for the search of differentially expressed genes (student /limma test, correction for multiple tests). Introduction to R software.

2010-2012 Statistical analysis of transcriptomic data, course/TD (10h), L3, Roscoff Biological Station.

Description: Introduction to high throughput technologies, overview of classical data preprocessing methods and statistical methods for the search of differentially expressed genes (student /limma test, correction for multiple tests), use of R software.

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