This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
For further information about this project, please contact:
This project aims to characterise the cellular landscape of the human inner ear by integrating single-cell RNA sequencing datasets from developmental and tumour contexts. The project will integrate existing developmental inner ear single-cell data with single-cell profiles derived from vestibular schwannoma tissue.
By comparing the transcriptional programmes of schwannoma cells against normal developmental cell types, the project seeks to identify the cellular origins and molecular mechanisms underlying schwannoma formation and growth.
This is a preliminary exploratory project and may expand in scope as additional datasets become available, and as analyses complete.
Python / Jupyter notebooks for use of single cell RNA sequencing tools including scanpy, scVI, cell2location.
Analysis is performed in Python using Jupyter notebooks. The primary analytical framework is the scanpy ecosystem for single-cell data processing, including quality control, normalisation, batch integration, dimensionality reduction, and clustering. Data is stored and manipulated in AnnData (h5ad) format. Dataset integration across developmental and tumour contexts will require batch correction methods (e.g., scVI, Harmony, or scanorama). Additional Python libraries include numpy, scipy, pandas, matplotlib, and seaborn. Compute requirements include high-memory nodes for loading and integrating multiple large h5ad objects.