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Forum: PhD Bioinformatics on GWAS

Can a PhD thesis in bioinformatics be done within the area of Genome wide association studies alone. Is it robust enough?

snp gwas genome phd

Is it robust enough?

What does this mean?

Based on current trends, is it a highly valued area or I would be required to add more components in order to improve its depth of content

I've moved this to a forum post as this is more of a discussion than a question with a finite number of "correct" answers. Your question is about GWAS and PhD, why are the tags in the post just "snp" and "genome"?

I mean i am considering GWAS of a disease and population that has been understudied.

Have you seen GWAS papers? The list of authors is enormous. It requires a huge amount of effort and usually is not within the scope of a PhD. You can do follow-up analyses like chasing genes down or study the disease otherwise, GWAS is just one tool in statistical genomics, if that's the path you want to walk.

It is good that it requires a huge amount of effort and that makes it enticing for me. If you say it is just one tool does that not mean that it is lacking in depth?

The effort is in genotyping the population, the computational side is not the major issue, it's more statistics than it is computational biology.

If the major content is in statistics, does that not mean that it may not be robust enough for Bioinformatics doctorate?. Can there me other methods (e.g. post-gwas) that can be added to improve quality and depth?

1 answer

A PhD thesis can be done on any topic that the candidate, supervisors, and finally the opponents or evaluation committee, and faculty agree on. There is no general requirement known to me that the topic be broad, narrow, or robust, etc. It should mark a significant scientific advancement in its field, which is pretty lenient enough a definition to allow for any serious topic and is a matter of subjective evaluation.

I mean specific for the field of bioinformatics

It is hard to give a more specific answer without a specific topic. Just naming GWAS is way too broad. Have your supervisors been working in the field before, have they published on topic? Have they had other successful PhD-candidates? Do you have experience with the field? Do they have data to analyze? Should you develop a tool?

Maybe, some subjective comment also, GWAS, in my opinion, is a mine-field, with a lot of opportunities to step on someone's toes. Data-sets are noisy, and statistics often do not reach genome-wide significance. So, maybe not a good idea.

I get your perspective. Thanks for the advice, this will inform further decision.

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