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Undergraduate Training

Bioinformatics teaching in undergraduate degrees is crucial if we want to better prepare the next generation of graduate students to tackle the challenges of modern science.

We contribute to a number of NST subjects throughout the year and are the organizers of the NST Part II BBS Bioinformatics Minor Subject.

 

NST Part II BBS Bioinformatics minor (128)

This Minor Subject aims at providing an introduction to genomics applications, focusing on the use of next generation sequencing (NGS) for the analysis of gene expression and genomics variation in healthy and diseased individuals. Analytical workflows for processing NGS data are presented and students have the opportunity to familiarize themselves with basic statistics, computational skills, bioinformatics resources and analytical approaches needed to process, analyze and interpret NGS data. Clinical and pharmacological implications are also discussed.

For more information, visit the BBS website or contact the course organizer, Dr. .

 

Learning outcomes

By the end of this course students should be able to:

  1. Discuss the principles applied to quality control of sequencing data, alignment of sequence to the reference genome, calling and annotating sequence variants, and filtering strategies to identify pathogenic mutations in sequencing data;
  2. Identify the challenges associated with the analysis of variation data, how to treat candidate variants given known false positive/negative rates and population frequencies as well as the implications for disease diagnosis;
  3. Interrogate major database sources and be able to integrate this information with clinical data, to assess the potential pathogenic and clinical significance of the identified sequence variants;
  4. Perform basic RNA-seq data analysis and be familiar with open-source software packages for such analysis;
  5. Explain of basic concepts and methods applied in network analysis, phylogenetic analysis, deep learning and structural bioinformatics, and
  6. Gain practical experience of the bioinformatics pipelines for variant calling, RNA-seq, network analysis and structural bioinformatics.

 

2018/19 timetable:

Lecture/practical title

Type*

Lecturer

Date

Introduction to Unix

P

Morgunov

14-Jan

Introduction to bioinformatics and computational biology

L

Durbin

17-Jan

Introduction to R

P

Morgunov

21-Jan

Next generation sequencing data analysis: quality control and alignment

L

Lopez

22-Jan

Next generation sequencing data analysis: variant calling and annotation

L

Lopez

24-Jan

Introduction to NGS analysis (data formats, data manipulation, QC)

P

Lopez

28-Jan

Statistics for large datasets and multiple comparisons

L

Castle

29-Jan

Genetic association methods for rare diseases

L

Turro

31-Jan

Analysis of variants I

P

Lopez

04-Feb

Analyzing variation in cancer

L

Nik-Zainal

05-Feb

Analysis of variants II

P

Lopez

11-Feb

Disease gene discovery through differential expression

L

Enright

12-Feb

Data into knowledge: ontology and biosemantics

L

Schofield

14-Feb

RNA-seq analysis

P

Enright

18-Feb

Evolutionary Tools for Genomics Analysis

L

De Maio

19-Feb

Machine learning: principles and applications

L

Schofield

21-Feb

RNA-seq analysis - focus on downstream analysis

P

Enright

25-Feb

Computational proteomics

L

Lilley / Smith

26-Feb

Network biology

L

Porras

28-Feb

Network analysis

P

Porras

04-Mar

Structural bioinformatics

L

Morgunov

05-Mar

Computational tools and resources for cancer pharmacogenomics

L

Iorio

07-Mar

Structural bioinformatics

P

Morgunov

11-Mar

* L=lecture, P=computer practical