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Online info event, Thursday, 15.1.2026

Life Sc...
CAS Applied Bioinformatics: Next-Generation Sequencing Data Analysis

CAS Applied Bioinformatics: Next-Generation Sequencing Data Analysis

Advance your expertise in programming, analysis and interpretation to deepen your knowledge of bioinformatics and computational biology.

Key data

Degree
Certificate of Advanced Studies FHNW Applied Bioinformatics: Next-Generation Sequencing Data Analysis
ECTS points
12
Next start
26.3.2026
Duration
12 days
Final application date
12.2.2026
Teaching language
English
Place
Online (first and last session on-site)
Fee
CHF 6 800
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Develop practical skills in next-generation sequencing data analysis through a combination of lectures by experts, interactive exercises, and real-world case studies. You will gain a solid theoretical foundation and practical expertise in applied bioinformatics.

  • Develop core skills in next-generation sequencing and Nanopore using Unix, Python and Git for effective, reproducible bioinformatics workflows.
  • Gain proficiency in widely used open-source bioinformatics tools and databases, including GATK, Ensembl, ClinVar and Kraken.
  • Apply your knowledge in hands-on sessions with real-world case studies drawn from research and clinical contexts.
  • Flexible attendance options: fully online, with the option of attending the first and final sessions on-site.

Content

The programme begins with an introduction to fundamental programming concepts, data management and essential bioinformatics computational tools. You will then receive in-depth training on analysing raw sequencing data from Next-Generation Sequencing (NGS) and Oxford Nanopore Technologies (ONT), covering file formats, quality control, alignment, variant calling and metagenomic pipelines. The final module focuses on interpreting sequencing results in biological and clinical contexts, including gene expression profiling, variant annotation, and integration with public datasets.

Module 1: Computer and Software Development

You will acquire fundamental programming skills essential for modern bioinformatics. The focus is on Python programming, version control using Git, and working within Unix-based operating systems. You will also gain experience in using tools such as Jupyter for interactive coding and scripting. This module builds the solid foundation required for the bioinformatics approaches covered later in the course.

  • Essential programming skills for bioinformatics
  • Python programming
  • Version control with Git
  • Coding and scripting with Jupyter
Module 2: Bioinformatics Data Pre-Processing and Analysis

This module introduces core techniques for handling raw sequencing data, including relevant file formats, quality control, read alignment, variant calling, and metagenomics analysis.

  • File formats: FASTQ, BAM, VCF
  • Genome Analysis Toolkit (GATK)
  • Quality control procedures
  • Read alignment techniques
  • Variant calling workflows
  • Metagenomics pipelines
Module 3: Bioinformatics Data Interpretation

You will learn to interpret NGS results in biological and clinical contexts, applying statistical and visualization methods. Topics include differential gene expression, pathway analysis and variant annotation.

  • Databases: Ensembl, ClinVar, Kraken
  • Network and pathway analysis
  • Enrichment analysis
  • Assessing clinical relevance

Overview

Target audience

This programme is for you if you work in life sciences, healthcare or research and want to build practical skills in bioinformatics. It is particularly relevant if you:

  • Work with or plan to work with next-generation and nanopore sequencing data
  • Are in life sciences or research, looking to analyse genomic or transcriptomic data
  • Are a clinician who wants to interpret sequencing data in a clinical or translational context
  • Work in biotech, pharma, or a related industry where sequencing analysis is becoming essential

You should have a basic understanding of molecular biology, some hands-on experience with a programming language such as Python, and strong motivation to strengthen your computational skills.

Admission

At least one of the following admission requirements must be met:

  • Tertiary educational qualification (at least Bachelor’s degree level) and relevant professional experience.
  • Federal Diploma of Higher Education (from a Swiss “Höhere Fachschule” or “eidg. HFP” or “eidg. BP”), and at least 3 years of relevant professional experience in a subject relevant to or related to the continuing training programme.
  • Interested persons without tertiary educational qualification can be admitted, if they have a minimum of 5 years professional experience in a subject relevant to or related to the continuing education programme and if they have successful completed various continuing training courses (in-company or CAS/MAS/DAS) or discontinuation of tertiary education with advanced participation or partial achievement (> 50%).

As the instruction and training materials are in English, proficiency in English (minimum level C1) is a prerequisite.

A personal notebook/laptop is required for the course.

Learning Outcomes

Upon successful completion of this programme, you will be able to:

  • Apply foundational programming and computational skills within a bioinformatics framework
  • Perform pre-processing and primary analysis of raw sequencing data generated from next-generation and nanopore sequencing technologies
  • Interpret and visualize sequencing results with consideration of biological and clinical relevance
  • Integrate publicly available databases and annotation resources to support in-depth genomic interpretation
  • Develop reproducible and well-documented analysis pipelines using scripting tools

As part of the programme, you will independently complete a project, using your own dataset or one provided by your institution, encompassing the full bioinformatics workflow from raw data processing to final interpretation.

Format

The programme includes:

  • 12 instruction days, held on Thursdays
  • An individual project

On completing the programme, you will submit a written report and give a brief presentation summarizing the methodology, tools, and key findings of your project.

All lessons are online, with the option of attending the first and last day in person at FHNW Campus Muttenz.

Lecturers

The programme is conducted by lecturers from the university as well as recognized experts in the field.

Downloads

Programme specific

  • Factsheet CAS Applied Bioinformatics: Next-Generation Sequencing Data Analysis FHNW
  • Programme Description CAS Applied Bioinformatics: Next-Generation Sequencing Data Analysis FHNW

General Documents

  • Conditions of Admission Continuing Education Programmes HLS
  • Programme Regulations CAS HLS
  • Directives for Continuing Education in the FHNW School of Life Sciences

Continuing Education

Life Sciences
Overview Continuing Education
Abdullah Kahraman

Prof. Dr. Abdullah Kahraman

Team leader, Data Science in Life Sciences

Telephone

+41 61 228 62 23

E-mail

abdullah.kahraman@fhnw.ch

Address

School of Life Sciences FHNW Institute for Chemistry and Bioanalytics Hofackerstrasse 30 4132 Muttenz

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Elzbieta Lehmann und Nicole Widmann
Telephone

+41 61 228 55 40

E-mail

weiterbildung.lifesciences@fhnw.ch

Address

Hochschule für Life Sciences FHNW Hofackerstrasse 30 4132 Muttenz

Weiterbildung Englischint_wb_casoverview_kurs_seminar

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