Date: 31 March - 3 April 2020

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The course covered content for these learning objectives:

To write your own custom functions
To use for loops, apply functions and if statements
To analyse large matrices of data in a semi-automated way
To normalise data
To quantify and correct batch effect
To undertake the most common clustering algorithms including k-means and hierarchical
To perform variable selection and present these results in different plots including heatmaps
To do 2-way ANOVA
To undertake multivariate modelling
A brief introduction to machine learning.

The course included brief theoretical introductions followed by hands on exercises based on real life research examples.

Contact: Computational Biology Facility (cbf@liverpool.ac.uk)

Keywords: R Programming, Statistical-model, Statistics, Pre-processing, Transcriptomics, Metabolomics, Proteomics

Venue: University of Liverpool

City: Liverpool

Region: Merseyside

Country: United Kingdom

Postcode: L69 3GH

Organizer: Computational Biology Facility

Host institutions: University of Liverpool

Eligibility:

  • Registration of interest

Capacity: 20

Event types:

  • Workshops and courses

Scientific topics: Bioinformatics, Statistics and probability


Activity log