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Education and training

We are keen on increasing a deep understanding on bioinformatics and statistical analysis. Therfore we are involved in arranging courses and workshops with a focus on NGS data analysis, expression analysis and software training (IPA). We can also offer customized training sessions if you e.g. want education in analyzing your own data.

For special inquiries, please contact us.

Master's thesis projects

A list of currently available master's thesis projects in bioinformatics can be found here.

Courses and workshops

  • Workshops on demand

In addition to the courses listed below, Bioinformatics Core Facility offers workshops customized to fit the needs of our customers. The workshops can cover e.g. IPA, Plink, metaanalysis, power analysis, multiple correction, experimental design, and many other bioinformatics/statistics related topics.

  • Bioinformatics in genomics (SC00027), 4,5 higher education credits, given in spring.

This course is aimed to PhD students who are interested in performing bioinformatics analyses on genomic data. It consists of lectures and computer exercises covering the following topics:

  1. Use of molecular biology databases available at NCBI, Ensembl and UCSC
  2. Theory and practice on sequence analysis methods to understand features, functions, structure and evolution of DNA, RNA and peptide sequences, including sequence alignment, profiles, and phylogeny
  3. Data analysis of NGS data: Exome-seq, RNA-seq, ChIP-seq, Methyl-seq and Metagenomics
     
  • Analysis of next generation sequencing data (SC00024), 2 higher education credits, given in autumn

This course is aimed to PhD students who are directly performing bioinformatics analysis on NGS data. We will focus on developing practical skills beyond the quality assessment of raw data; therefore you need to have experience within the Linux environment. Teaching will be performed through lectures and computer exercises covering topics of Targeted resequencing (exome-seq) and Differential expresson (RNA-seq).

  • Microarray analysis using R (SC00029), 1.5 higher education credits, given in autumn

This is a hands-on course that covers the basics in microarray data analysis by using R, a language and environment for statistical computing and graphics. The course includes a combination of lectures and practical sessions that introduce different applications of microarrays such as: gene expression, methylation, association between SNP’s and traits (GWAS) and copy number variations (CGH). You will learn the basic R statements to analysis and visualization this type of data. The course targets researchers with little or no prior knowledge in R that need computational skills to handle microarray data.

  •  Unix with applications to NGS data (SC00025), 1.5 higher education credits, given twice a year

This course aims to give an introduction to researchers with little or no prior knowledge in Unix that need computational skills to handle large datasets. The course will consist of lectures, on-site exercises and a home assignment to introduce Unix as a tool for handling NGS data. You will benefit from this course when applying for our Python Courses.

  • Python programming for life science researchers (SC00026), 1.5 higher education credits, given twice a year 

This course aims to give an introduction to researchers with little or no prior knowledge in Python that need computational skills to handle large datasets. The course will consist of lectures, on-site exercises and a home assignment. Some Unix experience is recommended.

  • Multivariate statistics, 5 higher education credits, given in spring, in collaboration with Health Metrics

The goal of the course is to present the student with the most common multivariate techniques used in the study of health related data and in other disciplines, such as clustering, classification, dimension reduction, ensemble methods and regularization. The student will become familiar with the types of data and the nature of the questions that multivariate statistics can address. An applied approach will provide the student with the knowledge to successfully perform multivariate analysis and interpret the results.

Contact Information

Bioinformatics Core Facility

Box 413, 405 30 Göteborg

Visiting Address:
Medicinaregatan 3B, Floor 1000

Page Manager: Sanna Abrahamsson|Last update: 6/20/2017
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