Analyse de données reproductible - Research - Institut Pasteur

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Assistant Professor
Associate Professor
Clinical Research Assistant
Clinical Research Nurse
Clinician Researcher
Department Manager
Dual-education Student
Full Professor
Honorary Professor
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Master Student
Non-permanent Researcher
Nursing Staff
Permanent Researcher
Pharmacist
PhD Student
Physician
Post-doc
Prize
Project Manager
Research Associate
Research Engineer
Retired scientist
Technician
Undergraduate Student
Veterinary
Visiting Scientist

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Deputy Director of Center
Deputy Director of Department
Deputy Director of National Reference Center
Deputy Head of Facility
Director of Center
Director of Department
Director of Institute
Director of National Reference Center
Group Leader
Head of Facility
Head of Operations
Head of Structure
Honorary President of the Departement
Labex Coordinator

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MOOC Tuberculosis

Bioinformatics program for PhD students 2021-2022

Scientific Fields

Diseases

Organisms

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Technique

Starting Date

21

Jun 2021

Ending Date

29

Jun 2021

Time

09:00:00

28 Rue du Dr Roux, Paris, France

Address

2021-06-21 09:00:00 2021-06-29 17:00:00 Europe/Paris Analyse de données reproductible La production de données de plus en plus massives, le développement de méthodes d’analyse de plus en plus complexes, et le nombre en constante augmentation d’outils disponibles amènent les scientifiques à développer des chaines de traitement (workflows) de plus […] 28 Rue du Dr Roux, Paris, France Frédéric Lemoine frederic.lemoine@pasteur.fr

La production de données de plus en plus massives, le développement de méthodes d’analyse de plus en plus complexes, et le nombre en constante augmentation d’outils disponibles amènent les scientifiques à développer des chaines de traitement (workflows) de plus en plus complexes. Cela constitue une opportunité unique pour extraire des connaissances scientifiques, mais pose également de nombreux problèmes.

Il devient en effet difficile de :

Implémenter efficacement de nombreuses chaînes de traitement de données ;
Tenir à jour une grande liste d’outils et de leurs versions ;
Garder la trace des anciennes analyses (outils, version, données, etc.) ;
Reproduire d’anciennes analyses ;
Partager les workflows.

Dans cette formation, nous aborderons les notions nécessaires à l’implémentation et à l’exécution de chaînes de traitement (workflows) complexes en suivant les meilleurs pratiques : Versionning (git), Utilisation de containers (Docker, Singularity), Utilisation de systèmes de workflows (Snakemake, Nextflow) ou de Notebooks (Jupyter Notebooks), ou encore adoption de bonnes pratiques pour le développement d’outils.

Location

Location: 28 Rue du Dr Roux, Paris, France

Published on: 24 Aug 2021

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