UE Biostatistics, Bioinformatics, Modeling , Part II

Diplômes intégrant cet élément pédagogique :

Descriptif

Course outline

 At the end of the course, the students should be able to analyze a "omic" dataset. More precisely, they should be able:

1- to load, explore and summarize graphically a dataset;

2- to compute confidence interval estimates for proportions, means and variances;

3- to formulate hypotheses, compute tests statistics, interpret p-values and make practical decisions for the

standard parametric and non-parametric tests;

4- to adjust simple and multiple linear models, analyses of variance (anovas), logistic regression, Cox

model;

5- to select genes that explain a response variable by applying multiple testing approaches;

6- to analyze a data set of differential gene expression.

 

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Format of the course

 

Activities

Hours

Percentage

Lectures

15h

20%

Tutorials and discussions

 

 

Lab sessions

30h

30%

Estimated work load at home

50h

50%

Total

95h

100%

 

 

Exam requirements

 

Nature of the exams

Mid-term (Number of hours, % of the final grade)

Final (Number of hours, % of the final grade)

Second session

Written exam

 

 

 

Oral exam

 

30 min, 60%

20min

Research project

30 min, 20%

 

 

Synthesis

 

 

 

Practicals: report

20%

 

 

 

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Pré-requis

-Language used for the teaching and evaluation: English

-To which kind of program can you apply when taking this course?

PhD programs in Biology

-Pre-requisites:

None

-Is the number of students limited in this course? No

Compétences visées

 Overview of the principal techniques of statistical data treatment, with an emphasis on practical skills and the use of the statistical software R.

Informations complémentaires

Lieu(x) : Grenoble - Domaine universitaire
Langue(s) : Anglais