Module Descriptors

Bioinformatics

MA570: Introduction to Genomics (5 ECTS)

This module will give students skills associated with high-throughput processing, investigation and interpreting the output of genomics data using bioinformatic tools.

Taught in Semester(s) 2. Examined in Semester(s) 2.

Workload: 109 hours (12 Lecture hours, 12 Lab hours, 85 Self study hours).

Module Learning Outcomes. On successful completion of this module the learner should be able to:

  1. Discuss key historical developments in genomics research.
  2. Access and apply core programming interfaces for bioinformatic analyses.
  3. Discover differential expression in gene transcript sequencing data.
  4. Compare new high-throughput sequencing experiments to other published results.
  5. Evaluate functional genomics experimental datasets.

Indicative Content

  1. Introduction to Linux & the R Statistical Computing Environment
  2. Perl and The BioConductor project
  3. Microarrays: Experimental design and analysis issues
  4. Analysis of microarray data using BioConductor, including a. Pre-processing & quality control b. Differential expression and geneset enrichment analyses c. Case studies
  5. Next-generation sequencing technologies and their applications a. Variant screening and discovery
  6. RNA-seq: Gene expression analysis using next-generation sequencing, including a. Quality control using the fastq pipeline b. Mapping short-reads to reference genomes c. Gene expression metrics and caveats d. Case studies
  7. Chromatin Immuno Precipitation and next-generation sequencing (ChIP-seq), including a. Design and analysis of ChIP-seq experiments b. Peak-finding c. Case studies (including the Encode project)

Module Resources

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