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NGS bioinformatics quality control and variant annotation for cancer diagnosis
28 August 2018
For-profit: 300 CHF
Next course(s):
12 Nov 2019 | Bern | |
14 Sep 2020 | Lausanne | |
15 Mar 2021 | Streamed |
Overview
This course is organised by SIB Swiss Institute of Bioinformatics, in collaboration with the Clinical Pathology Division of the University Hospital of Geneva (HUG).
Cutting-edge technologies, like next-generation-sequencing (NGS) applied to gene panels, combined with the development of targeted therapies are now revolutionising clinical practice in oncology. In this context, clinical bioinformatics plays a pivotal role, ensuring that NGS data are converted into clinically relevant knowledge. While bioinformatics analysis pipelines can be automated to some extent, they still require human expertise to perform robust quality control and annotation/interpretation of somatic variants.
This course therefore aims at deepening the underlying bioinformatics concepts for professionals from clinical labs working on NGS data, to improve their skills for spotting artifacts from NGS data and annotating true somatic variants. This interactive course will consist of lectures alternating with study cases using a bioinformatics pipeline for cancer diagnosis, and group discussions/presentations.
Programme
I. NGS BIOINFORMATICS PIPELINE
Overview of a bioinformatics analysis pipeline: from FASTQ to BAM, VCF and annotation.
II: BIOINFORMATICS QUALITY CONTROL
Quality control throughout the NGS pipeline
Variant-level quality control: common measures and thresholds for IonTorrent and Illumina
Study case – Spotting data artifacts among true variants
III: ANNOTATION & INTERPRETATION
Clinical significance: pathogenicity and actionability
Literature and other public databases: essentials and extras
From variant to gene, assessing functional impact
Study case – Annotation with literature and other public databases
Audience
Priority will be given to members of clinical laboratories in Switzerland with some experience in NGS somatic variant analysis.
Learning objectives
At the end of the course, the participants are expected to:
- Participants improve their skills in NGS somatic variant annotation through theory and practical hands-on sessions related to their daily clinical practice.
- Participants share and discuss their own practices, addressing topics from Ion Torrent and Illumina technologies.
Prerequisites
Knowledge / competencies
Some experience in NGS variant analysis.
Technical
None. Computers will be provided to participants.
Application
- Registration is free of charge for HUG staff (valid HUG email required).
- For other academics, a registration fee of CHF 60.- applies.
- Participants from non-academic institutions should contact us before application.
Application is CLOSED, the course is full. Deadline for registration and free-of-charge cancellation is set is set to 28/08/2018. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.
You will be informed by email of your registration confirmation.
Venue and Time
University of Bern, more details later.
The course will start at 9:15 and end around 17:15. Precise information will be provided to the participants on due time.
Additional information
- Participation to this course is recognized by SSPath with 7 credits of continuing education
- The course will be taught in english.
- Teachers: Dr. Walid Gharib (University of Bern & SIB Training), Dr. Aitana Lebrand (SIB Clinical Bioinformatics), more to be announced.
- Scientific responsibility: Prof. Thomas McKee (Head HUG Molecular Pathology).
- Hospital contributor: Dr. Yann Christinat (HUG Molecular Pathology).
- Course coordinators: Dr. Aitana Lebrand (SIB Clinical Bioinformatics) and Dr. Grégoire Rossier (SIB Training / SIB Vital-IT).
You are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@sib.swiss.