Assessment
This assessment will allow you to investigate the data acquired. The assessment is broken down in to three separate sections.
The assessment should be submitted as a short scientific report defining (a) the computational methods applied; (b) the data analysis results generated and (c) a discussion/conclusion section. The maximum word count is 800 words.
The data collected is presented in the file named ‘Proteomics data.xls’.
Construct a volcano plot to visualise the changes in fold change and p values from health to sepsis. (By excel)
If you assume p<0.05 is significant and prioritise two-fold increased or decreased: name the two most increased and two most decreased proteins of significant interest.
What are the biological processes for these proteins?
Serum samples were extracted and analysed for 15 subjects diagnosed with sepsis and 15 subjects not diagnosed with sepsis. Plasma was extracted in 50/50 methanol/water (v/v). Each sample was analysed applying a ultra-performance liquid chromatography-mass spectrometry (LC-MS) method followed by raw data processing. Quality Control (QC) samples were also analysed as part of the study.
The processed LC-MS data is presented in the file named ‘Omics_Microbes_Metabolomics_dataset_Case_Study.csv’.
Assess the quality of the data provided applying multivariate analysis methods. Define whether the data is of an adequate quality to perform statistical analysis.
Applying univariate statistical analysis methods, identify the metabolites which show a statistical significance between subjects with sepsis and subjects without sepsis. Report the metabolite and statistical critical p-value for all metabolites with a critical p-value < 0.05 (FDR-corrected).
Identify the metabolite pathway or pathways that are associated with the statistically significant metabolites described in part b.
