Statistics Question

Overview

Introduction

The gut microbiome has a significant impact on human health status and the development of non-communicable diseases including inflammatory bowel disease (IBD). IBD affects 1 in every 123 people in the UK.

Study Design

A recent study has acquired samples of faecal samples from 18 healthy individuals and 18 individuals with inflammatory bowel disease. These samples have been analysed by proteomics and metabolomics methods to identify changes in proteins and metabolites.

Assessment

This assessment will allow you to investigate the data acquired. The assessment is broken down in to three separate sections. However, 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, synthesizing the different analyses. The maximum word count is 800 words. Do not include this outline in your report.

1. Proteomics - visualisation and identification (30% of the mark)

For evaluation of the changes happening in IBD, proteins from the samples donated by three patients with IBD and 3 age and gender matched healthy controls were prepared for quantitative proteomics.

The data collected is presented in the file named ‘Proteomics data 2025.xls’.

Analyse the data and include in the report:

a volcano plot to visualise the changes in fold change and p values from health to IBD.

the two most increased and two most decreased proteins of significant interest, assuming p<0.05 is significant and prioritise two-fold increased or decreased

the biological processes (GO BP) for the four proteins identified in the point above

2. Proteomics - interpretation (30% of the mark)

Protein ASCL (24,454 Da) was identified in the proteomics dataset. The protein was purified and analysed by native mass spectrometry, however, its mass was measured to be 25 kDa rather than 24.4 kDa.

In your report:

Draw (in detail) what the native mass spectrum would look like for the 25 kDa protein ASCL. Describe your reasoning for the spectrum in the report.

Explain briefly why the measured mass might be different to the mass determined from the proteomics database.

3. Mass Spectrometry-based Metabolomics (30% of the mark)

Faecal samples were extracted and analysed for 18 subjects diagnosed with IBD and 18 subjects not diagnosed with IBD. Each sample was extracted in 50/50 methanol/water (v/v). Each sample was analysed applying an 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_2025.csv’.

In your report cover the following items:

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 above.

In final 10% of the mark is given for the construction of the report and how the different elements are drawn together.