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Cancer Genomics

11th-14th December, 2017

Profs. David Gfeller (LICR@UNIL) and Giovanni Ciriello (DBC@UNIL)

 

REGISTRATION:

francoise.flejszman@unil.ch - until 15.10.2017 - Maximal number of participants is set to 20. Priority will be given to UNIL PhD students

 

AIMS OF THE COURSE:

  1. Provide participants with knowledge of what can be/is being done in cancer genomics (focusing on DNA/RNA Sequencing).
  2. Provide participants with basic tools on how to access and visualize these data (Portal + R scripts).
  3. Provide students with a view of how they could use these data (what questions to ask, what are the limitations).

The course will feature first technical/computational and then biological aspects in order to provide participants with some tools on how to access and analyze cancer genomics data. Participants will therefore be expected to do some basic programming and data analysis during the afternoon sessions.

It is not meant to be a full course on cancer molecular biology or genetics of cancer.

All lectures take place in Epalinges.

Contact: David Gfeller

 

REQUIREMENTS:

  • PhD students affiliated to UNIL or EPFL (post-docs may be considered provided there are places left).
  • Basic knowledge of cancer biology and immunology.
  • Own computer for the practical. R installed (R Studio). Basic skills in R (e.g., understanding of what a variable is, opening and printing to files) are recommended, please have a look at this tutorial from Giovanni.
  • Students are expected to attend all sessions and should notify in advance the organizers of the reason of their absence.

 


EVALUATION (credits):

The course is worth 3 ECTS credits. Credits will be given based on compulsory participation during the 4 full-day (Dec 11-14). In addition, a presentation of the solution obtained for the selected excercise is expected on Dec 22 and is required for obtaining the credits.

Total hours: 32h + 20h problem-solving.

List of exercises:

  • To be updated

 

PROGRAM:

Monday Dec 11 (Giovanni Ciriello) - room F308

Morning (9-12): Introduction to cancer genomics - Slides_Day1
  • Focus on genetic alterations
• Advent of large-scale studies
• Technologies and tools
• Data portals for download and browsing
• Web services for analyses (cBioPortal)
Afternoon (13-17): Practicals - Data_for_Practical
  • Download a dataset
• Browse a dataset (cBioPortal)
• Browse and obtain analyses for specific tumor types


Tuesday Dec 12 (Giovanni Ciriello) - room F308

Morning (9-12): Introduction to the concept of molecular cancer subtypes - Slides_Day2
  • Genetic heterogeneity within tumors
• Tumor subtypes defined by mutations and copy number alterations
• Genetic similarities between tumors
• Patient stratification based on molecular changes
• Concept of actionable alterations and basket trials
Afternoon (13-17): Practicals
  • Select a tumor type (e.g. starting from one TCGA paper)
• Identify relevant genetic alterations
• Identity overall alteration rate
• Do they characterize tumor subpopulations? How heterogeneous is the tumor type?
• Identify actionable alterations
• Stratify samples based on candidate combination therapies


Wednesday Dec 13 (David Gfeller) - room F308

Morning (9-12): Tumor gene expression data analysis - I Slides_Day3
  • Basic understanding of RNA-Seq experiments and data processing.
• Dimensionality reduction, principle component analysis.
• Differential expression.
Afternoon (13-17): Practicals - Instructions - Rcode
  • Gene expression data analysis.
• How to do it on your machine in R.
• Walking through large gene expression matrices.
• Principle component analysis.


Thursday Dec 14 (David Gfeller) - room F308

Morning (9-12):

Tumor gene expression data analysis - II Slides_Day4

 

• Gene Set Enrichment Analysis and immune signatures.
• Introduction to single-cell RNA-Seq.

Afternoon (13-17): Practicals - Instructions - Rcode
  • Tools for identification of immune signatures (GSEA, EPIC).

 

Friday Dec 22 (Giovanni Ciriello + David Gfeller) - room F308

Morning (9-12): Group Presentations - Project_Ideas
  Each group of two or three persons will present the result of their analyses (including biological motivation for the problem, methods used in the analysis and final solution).

 

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Switzerland
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