3.0 years ago by
In my opinion education in statistics or computation gives you a solid foundation for the analysis of ngs data. Msc might also be a good time point to choose this topic. You have the option to develop your own perspective on the topic and learn about the origin of the data on the way using analytical skills that align with your background in math and statistics. It will be helpful to know some biology relevant to the data type. Planning for little bit of extra time for learning biology definitely also helps. Knowledge in using linux is a plus to run some tools, but R is mostly platform independent.
You will find a lot of questions and answers already here or on seqanswers and elsewhere online, and I am sure everyone here will be willing to answer new questions. One of the most important points to consider is to define a good topic together with your supervisor before starting the thesis.
This brings me to the few risks of the endeavor, which come from the fact that there is, as you state, nobody else working on the same topic. So you would possibly not be able to discuss much in detail with other researchers in your group. Writing to strangers on the internet is not always an easy drop in for personal communication and good supervision (not taking the experience of your supervisor into doubt), but I think it is possible in principle, and feasible. This might not necessarily hold for a PhD thesis. On the other hand, your qualification will be in high demand after you have finished.
Trying to come up with the most important contributing factors for a successful thesis, I think I would rank them:
- Group - environment
- Knowledge-skills (means you know something about the topic already)
As I see it, if the topic is very interesting to you, then it will be a very likely path. There are possibly some steep learning curves involved, but imho, a computational education prepares you better for NGS bioinformatics than a biological education.
I hope this helps, good luck.