The Challenge

The faculty sought to understand how feed size and gastric microbiota contribute to ulcer development in pigs. Identifying causal relationships required advanced biostatistics and careful handling of complex microbiome data.

Our Approach

We built causal models, ensured rigorous quality control and derived insights to understand microbiome‑driven ulceration.

• Hypothesis modelling & causal inference: Created a causal DAG from the client’s hypotheses and analysed relationships between feed size, microbial diversity, abundance and ulceration.
• Quality control & annotation: De‑noised samples, annotated species and abundances, and produced publication‑ready visualisations.
• Insights & publication: Performed mediation and differential abundance analyses to identify causal factors and suggest treatment strategies.

The Outcome

• Provided interactive visualisations and causal insights that informed subsequent studies.
• Published findings in a peer‑reviewed journal and extended academic collaboration.
• Highlighted the importance of quality control and causal frameworks in microbiome research.

Why It Matters

Combining causal models with advanced biostatistics helps disentangle complex host–microbiome interactions. Such analyses guide interventions and improve understanding of disease mechanisms.