Meta-Analysis

Meta-research is an emerging discipline, whose goal is to evaluate and improve research practices. This research theme includes work on research methods, reproducibility, evaluation, and communicating science.

Whilst there is a push for research data to be made open and avaliable to all, the standardisation of how data is processed or even metadata on recording how data has been processed remains limited.

In order to overcome this, I have generated several modular bioinformatic pipelines that allow us to process numerous datasets in an identical manner, allowing us to devel further into the data and make comparative analysis. Often there is a distinct communication gap between data scientists and biologists. By providing detailed analysis reports for both the data exploration and interpretation, complete with interactive visualisations, I overcome this by providing tools that allow reseachers from all backgrounds to explore the data in a meaningful way. I have extensive molecular and cellular experience which enables me to ensure that any data interpretation is comprehensive to key bench researchers and can guide future experimental design. Appropriate communication is vital within MDTs (multi disciplinary teams) that often are needed for large research projects.

Some of the most intriguing meta-analysis recently has involved cross-species comparisons of epigenetics and transcriptomics. Using disease model systems we have been able to look at conserved gene expression patterns within eye tissues, across species ranging from zebrafish, chicken, mouse and human. This provides an invaluable insight into both the conserved and divergent molecular pathways involved.