BiRD

Analysis pipeline using Snakemake for RNAseq analysis in order to find differentially expressed genes.

This workflow provides an automated microbiome data analysis, starting with sequenced taxonomic markers (such as 16SrRNA) and using the standard QIIME2 toolbox to produce an abundance table and preliminary diversity, phylogeny and taxonomy analysis.

• Biologie
• Biomédical
• Informatique

Le BiRD est cogéré par l'ITX et le LS2N, et emploie six biologistes computationnels. Grâce aux compétences de ce personnel dévoué et hautement qualifié, BiRD conseille, propose et développe des services bioinformatiques basés sur des données de séquençage à haut débit. Le BiRD possède une expertise dans l'analyse de données à grande échelle et a développé des flux de travail bio-informatiques dédiés qui normalisent le traitement des données brutes jusqu'à leur importance biologique. Sur la base de ces expertises, nous proposons à nos utilisateurs des formations sur l'analyse des données ou les langages de programmation. Ces services sont soutenus par une infrastructure de calcul et de stockage dédiée, accessible à distance via plusieurs services et ouverte à tous les scientifiques, quelle que soit leur institution d'accueil.

• Cloud
• Ecology
• Biodiversity
• Microbial ecology
• Metabolic engineering
• Multi-scale analysis and modelling
• Dynamic systems
• Ecological modelling
• Metagenomics
• Metabolic Network Modelling
• Machine learning
• Gene expression differential analysis
• metatranscriptomics
• Ontologies
• Panels (amplicons, captures)
• Exomes
• Variant analysis
• System modeling
• Systems Biology
• Interoperability
• Semantic web
• Knowledge mining
• Functioning of complex biological systems
• Regulatory network modelling
• Complete genomes
• Transcriptomics (RNA-seq)
• Integration of heterogeneous data
• Knowledge representation
• Cluster
• Computing Environments
• Data Integration
• Data management and transfer
• NGS Sequencing Data Analysis
• Données
• Toolkit
• Tool integration
• Workflow development
• Développements technologiques de l‘Information et de la Communication

Objectives
- Understand the principles and advantages of the Linux system
- Know and use the main bash commands. Ability to chain multiple commands using pipes
- Launch programs with arguments
- Gain independence to perform command line analyses

Pedagogical Content
- Introduction to the Linux system.
- File system: directory structure, paths, home directory, file and directory management.
- Principle of protections: reading file attributes, access rights, management of user groups.
- Shell usage: command reminders, input/output redirection, history, completion, launching programs with arguments.
- Commands relevant to bioinformatics: grep, cut, sed, sort, more, etc.
- Connection (ssh) - how to start a session from Linux or Windows PowerShell

Objectives
- Understand and implement the principles of reproducible science in analysis and development projects
- Acquire basic commands necessary for optimal use of the cluster

Pedagogical Content
- Introduction to reproducibility
- Best practices on code history and sharing: Git
- Conda environment
- Presentation of the computing cluster
- Introduction to workflows using Snakemake

Objectives
- Understand the key steps in RNASeq data analysis for a differential expression study
- Know how to perform command-line analysis using Snakemake.

Pedagogical Content
Day 1
- Principle of RNASeq technology: objectives and experimental design.
- Data quality assessment (FastQC, MultiQC).
- Sequence alignment to a reference genome (STAR).

Day 2
- Differential gene expression analysis (HTSeqCount, DESeq2).
- Functional annotation (GO, Kegg).
- Using the Snakemake workflow system.
- Comparison between RNASeq and 3’SRP methods.

The theoretical part is followed by a pipeline run step-by-step on a test dataset.
It will be possible to start an analysis on your own data.

Objectives
- Understand the principles and advantages of the Linux system
- Know and use the main bash commands. Ability to chain multiple commands using pipes
- Launch programs with arguments
- Gain independence to perform command line analyses

Pedagogical Content
- Introduction to the Linux system.
- File system: directory structure, paths, home directory, file and directory management.
- Principle of protections: reading file attributes, access rights, management of user groups.
- Shell usage: command reminders, input/output redirection, history, completion, launching programs with arguments.
- Commands relevant to bioinformatics: grep, cut, sed, sort, more, etc.
- Connection (ssh) - how to start a session from Linux or Windows PowerShell

Objectives
- Understand and implement the principles of reproducible science in analysis and development projects
- Acquire basic commands necessary for optimal use of the cluster

Pedagogical Content
- Introduction to reproducibility
- Best practices on code history and sharing: Git
- Conda environment
- Presentation of the computing cluster
- Introduction to workflows using Snakemake

Objectives
- Understand the key steps in RNASeq data analysis for a differential expression study
- Know how to perform command-line analysis using Snakemake.

Pedagogical Content
Day 1
- Principle of RNASeq technology: objectives and experimental design.
- Data quality assessment (FastQC, MultiQC).
- Sequence alignment to a reference genome (STAR).

Day 2
- Differential gene expression analysis (HTSeqCount, DESeq2).
- Functional annotation (GO, Kegg).
- Using the Snakemake workflow system.
- Comparison between RNASeq and 3’SRP methods.

The theoretical part is followed by a pipeline run step-by-step on a test dataset.
It will be possible to start an analysis on your own data.