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In this course, you will learn the basics of medical genomics, with a special focus on cancer genomics, through lectures, practicals, and projects
Fig 1. Schematic of computational analyses used in the Rare Cancers Genomics Initiative
- medical genomic concepts
- knowledge of resources (references, databases, workflow repositories)
- sequencing techniques
- basics of molecular biology
- basics of next-generation sequencing and chip sequencing
- R scripting
- basics of programming
Introduction: course objectives and organization
- Genomics: germline and somatic variation (SNVs, indels, structural variants, mutational signatures, cf DNA), resources (genome references, annotation, databases), sequencing strategies (whole-genome sequencing, whole-exome sequencing, arrays)
- Transcriptomics, multi-omics and beyond: heterogeneity and microenvironment, resources (tissue expression reference databases), sequencing strategies (bulk, single-cell), deconvolution, multi-omic integration, deep learning and integration with image analysis
- Metabolomics Part 1 and Part 2: Overview of metabolome and biomarkers, mass-spectrometry, metabolomics data processing and analysis, metabolite identification and metabolic pathway analysis, resources (databases, workflow repositories)
- Epigenomics: chromatin and histone modification, resources (annotations and databases for tissue-specific profiles), ATAC-seq, bisulfite sequencing, methylation arrays, methylation quantification, peak calling, differentially methylated positions and regions, deconvolution and identification of cell types, inference of environmental risk factors
Bonus: course on cancer evolution
- TP1: Developing and deploying an open-source medical genomic bioinformatic workflow
- TP2: Performing a multi-omic analysis of cancer data with R
Several projects will be proposed to process (bioinformatic workflow development) and analyze cancer data, related to the interests of researchers of the International Agency for Research on Cancer - WHO. Students will work in small groups (~4-5 people). Weekly meetings (in person or remotely) will take place with the supervisor. A final project restitution and debriefing will be held at the end of the module.
- Project 1: Building a transcriptomic map of small intestine neuroendocrine neoplasms
- Project 2: Building a methylation map and multi-omic map for lung cancers
- Project 3: Creating a workflow to identify recurrent somatic copy number alterations
- Project 4: Testing deconvolution methods for transcriptomic data
- Project 5: Metabolomics
Don't forget to join the Slack channel: https://join.slack.com/t/medicalgenomi-wkc1941/shared_invite/zt-imf2vepv-GK7MLJ~qhgjKIuVkjnu9mg
- GATK Best practices
- nextflow: nf-core, IARCbioinfo
- snakemake: snakemake-workflows
- wdl: GATK
- jupyter notebook: jupyter
- binder binder