Reflections on 2023 and outlook

It has been an amazing year of research. I've been at Burnet Institute since August 2023 as Head of Bioinformatics and I've really enjoyed the challenge of serving the many and varied 'omics projects at the Institute and loved discussing new project ideas with everyone here. I'm still active at Deakin in student supervision and project collaborations and this is ongoing.

In terms of research directions, my group has been focused on our three themes: 

1. Bioinformatics collaborative analysis

2. Building better software tools for omics analysis

3. Reproducibility and research rigour

Some of the long-running projects have been completed including methylation analysis of type-1 diabetes complications, which has been about 10 years in the making [1]. The number of collaborative projects has dipped, which is normal when changing institutes and I hope this will lift in the coming years as Burnet work gets completed.

In terms of research directions for 2024, there are many. One thing I hope to share with you soon is our approach to applying functional class scoring (like GSEA) to Infinium array data. This has been tricky since each gene can have many probes, and sometimes probes can be annotated to more than one gene. But I think we have a solution. It will be interesting to apply this to some of the larger EWAS datasets and prospective studies to see if it has any potential for methylation signatures to preceed disease onset. In doing this work we have learned a bit more about the differences between over-representation and functional class scoring tests which I hope to bring back to the transcriptome world.

Reproducibility has become an ever bigger part of my portfolio of projects since last year's paper "Urgent need for consistent standards for functional enrichment analysis" [2], which was very successful and probably my most important work of my career. Since then we have been conducting reproducibility surveys with my new PhD student Anusuiya Bora and we have learned a great deal about what it takes to make bioinformatics research reproducible and reliable. We also put together a review called "The five pillars of computational reproducibility: Bioinformatics and beyond" [3] which outlines the principles of reproducibility that we should be adopting. Along these lines, Anusuiya and I have written a protocol that outlines how to do enrichment analysis using these five pillar principles [4]. Next year we will be going even harder on reproducibility and enrichment analysis. We will have pieces on the utility of web-servers for bioinformatics and how we can make them more robust. We will also be examining some tools that are used by the microRNA community and in particular whether functional enrichment analysis of microRNA targets is something that is useful or not. 

This work on reproducibility is very satisfying as it directly educates emerging researchers on best practices, but the challenging part with this reproducibility agenda is that focused funding in this area is difficult to obtain as our work doesn't seem to fit in any existing grant scheme. We could do a lot more and better work in this direction if the funding issue were resolved.

1. Khurana I, Kaipananickal H, Maxwell S, Birkelund S, Syreeni A, Forsblom C, Okabe J, Ziemann M, Kaspi A, Rafehi H, Jørgensen A, Al-Hasani K, Thomas MC, Jiang G, Luk AO, Lee HM, Huang Y, Thewjitcharoen Y, Nakasatien S, Himathongkam T, Fogarty C, Njeim R, Eid A, Hansen TW, Tofte N, Ottesen EC, Ma RC, Chan JC, Cooper ME, Rossing P, Groop PH, El-Osta A. Reduced methylation correlates with diabetic nephropathy risk in type 1 diabetes. J Clin Invest. 2023 Feb 15;133(4):e160959. doi: 10.1172/JCI160959. PMID: 36633903; PMCID: PMC9927943.

2. Wijesooriya K, Jadaan SA, Perera KL, Kaur T, Ziemann M. Urgent need for consistent standards in functional enrichment analysis. PLoS Comput Biol. 2022 Mar 9;18(3):e1009935. doi: 10.1371/journal.pcbi.1009935. PMID: 35263338; PMCID: PMC8936487.

3. Ziemann M, Poulain P, Bora A. The five pillars of computational reproducibility: bioinformatics and beyond. Brief Bioinform. 2023 Sep 22;24(6):bbad375. doi: 10.1093/bib/bbad375. PMID: 37870287; PMCID: PMC10591307.

4. Ziemann M, Bora A. A recipe for extremely reproducible enrichment analysis. DOI: dx.doi.org/10.17504/protocols.io.j8nlkwpdxl5r/v2


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