Genomics & Transcriptomics

Knowledge:

• Second generation sequencing technology and newer developments
• Single cell technologies
• Applications of sequencing technology
  • Overview of how sequencing can be used / adapted to answer various biological questions
• Analysis strategies and workflows for sequencing data, including
  • Filtering and quality evaluation of raw reads
  • Mapping of sequencing reads
  • Variant and genotype calling from whole-genome DNA sequencing data
  • Gene/transcript expression quantification and differential expression analysis using RNA sequencing data
• Basic knowledge of the various statistical/​computational approaches and tools used when dealing with sequencing data and how and why these differ between sequencing applications
• Basic knowledge of the issues and potential problems with sequencing data and how to deal with those
• Basic knowledge of the impact of study designs and how to avoid and deal with batch effects 
• Genomic annotation and genome browsers
   

Skills:

• Analytical strategies of sequencing data
• Identify differentially expression of gene transcripts between biological samples of different types or conditions
• Identify mutations in an experimental sample by variant calling

Competences:

• Critically evaluate results of sequencing experiments from different perspectives (molecular biology, bioinformatics, genetics)
• Independently analyze and interpret whole-genome DNA sequencing data and RNA-sequencing data