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Practicals in next generation sequencing

Responsables : Marie Sémon (MCU, ENS Lyon)

3 ECTS credits, 36h de cours

Language

English/French

 

Summary:

NGS (Next Generation Sequencing) refers to high-throughput DNA sequencing technologies that generate a very large number of nucleic sequences. There are many applications (RNA-seq, metagenomics, resequencing, ChIP-seq…) that are used today in many fields of biology, such as cancerology, development, microbiology, epigenetics, evolution, and ecology. In this context, the main objective of this course is to show the practical use of NGS, from the sample, to the final results, via library preparation, sequencing, and bioinformatics analysis. Each group of students will be in charge of a small project, chosen among several concrete applications whose list will depend on the year and/or on the interests of the students, and will reflect several disciplines. One group of students (max 4) will be entrusted a bioinformatics/bench project, with the generation of their own sequences. The other groups will have purely, more elaborated, bioinformatic projects. During the practical courses, the discussion of methodological choices with other students and teachers will be encouraged (experimental settings, choices of tools, interpretation of the results). A workshop will be organised at the end of the session so that each group can present and discuss its results. No prerequisite in bioinformatics is necessary ; all tools will be used through Galaxy and R. NGS sequencing is made available through the sequencing platform at the IGFL.

Les calculs sont réalisés grace aux machines virtuelles fournies par la fédération de clouds Biosphère de l’IFB. 

List of past miniprojects (content vary according to year):

- single-cell RNA-seq and brain development - genetic loci associated with colored stripes in clownfish.

- polymorphism and misadaptations in human

- adaptation to arid environments in rodents

- misregulation in a skin disease

- effects of soil pollutants on microorganism diversity

- metagenomics in drosophila gut

- epigenetics in arabidopsis development

 

Course organisation:

-  The course lasts 6 days, in two steps (3 days each, separated by ca 1 month).   -  Students are divided into small groups (3-5 pers each). Each group has a different subject that corresponds to a different type of data and analysis. One of these groups has a bench  / bioinfo topic ( 3 days bioinfo, 3 days at the bench), and the other groups have 6 days bioinfo.

- Before the course, we discuss with the students on the allocation of themes and about possible data sets.

- During the practical course, the students produce their own codes and make their own methodological choices, with the help of their tutors.   - It is the students who present the methods they use. They also present the advancement of their project (2 group presentations).  - We insist on the need for transparency (bioinformatic codes must be freely available at the end of the course) and on reproducibility (in general, the results found during reanalyses of public data sets are different from the results described in the original publications).

 

Objectives and skills

Practical objectives:

- UNIX (basic commands), github, bash scripts, use of virtual machines

- NGS Data quality assessment, alignments, assembly (depending on project) - Quantifications of expression, polymorphism - Preliminary post-analyzes (statistics, graphical representations with R + For bench group (4 students)

- RNA extraction and librairie preparation. - sequencing   - Reproducibility of analyzes (ethics): codes on github. - Autonomy on the project from design to completion, choose and master the appropriate practical methodology.

General objectives:

- Respect people (listening skills, constructive spirit, politeness), teamwork

- Acquire current and cutting-edge scientific knowledge in NGS - Respect ethics rules, in particular refuse any fraud and work for reproducible research: github - Learn new methods and present them to other students - Interpretat complex data and be critical (potential bias).

 

Prerequisites:

None. This course builds upon pratical notions tought in the “bioinformatics” course in L3 , but it is not compulsory.

 

Assessment:

Contrôle continu 40%; Contrôle terminal 40%

Participation/interaction during the practicals (20%), 2 group presentations (40%), Code allowing to reproduce the analyses (documented and available on github 40%).