Competency information

Details

Perform appropriate analysis, e.g. mapping to reference, de novo assembly.

Considerations

  • Quality metrics for NGS data.
  • Open source and commercial NGS tools.
  • Ethical and governance frameworks.

Next Generation Sequencing platforms

  • The genome science behind NGS – random fragments, sequencing, assembly.
  • Different sequencing platforms and the physical technologies they deploy, including semiconductor, optical, nanopore.
  • Applications of NGS.

Sequence assembly

  • The problems of aligning short reads.
  • Next generation alignment strategies, e.g. Bowtie, Short Oligonucleotide Analysis Package (SOAP), Burrows-Wheeler Alignment (BWA), de Bruijn graphs.
  • Data formats for next generation data, e.g. BAM, SAM, fastq.
  • Sequence interpretation.
  • SNP detection, CNV detection.
  • Oral and written communication skills.

Relevant learning outcomes

# Outcome
# 2 Outcome Analyse NGS data through base calling, filtering, quality control, data validation and read mapping (eukaryotic and prokaryotic) in a clinical setting.(The clinical setting could include Clinical Genetics, Microbiology, Virology, Clinical Diagnostics, for example targeted oncology treatments/classical genetics.)