Quantitative data analysis
This module is designed to give supported, hands on experience of computational programming and data analysis within the statistical programming environment R, including the processing and analysis of ‘-omics’ data.
- Introduction to data analysis environments
- Working with R: basic computing skills (for loops, conditional statements, data structures etc.)
- Working with R: reading in and writing out data in R, data manipulations, plotting/data, visualisation.
- Statistical analysis approaches
- Analysis of phenomics (Biolog) data
- Analysis of genomics data (including Galaxy)
- Analysis of transcriptomics data (microarray, RNA-seq, including Galaxy)
- Analysis of interactomics data (ChIP/MeDIP/CLIP)
- Analysis of proteomics data (MASCOT, Scaffold)
- Analysis of metabolomics data
This online module aims to:
- To increase awareness of statistical concepts underpinning quantitative/systems biology research in the biosciences.
- To increase awareness of the utility and need of computational sciences in the biosciences.
- To increase awareness of the major molecular concepts relevant to current systems biology research.
- To enable delegates to evaluate the quality of data.
- To enable delegates to analyse quantitative data using the computing environment R for future independent data analysis in quantitative biosciences research.
- To provide students with hands on experience of analysing -omics data within the R statistical programming environment.
On successful completion of this module, students will be able to:
- Demonstrate an ability to independently programme and analyse data within the statistical programming environment R.
- Demonstrate an ability to identify and critically evaluate approaches for analysing a given –omics data set.
Lecturer in Bioinformatics
At least a 2.2 degree (or equivalent) in a relevant biological sciences discipline. Applicants not possessing these qualifications may be considered, depending on the length and quality of their practical experience and recommendations from employers/supervisors.Apply Now