Comp bio is a super fun field to be in. For me it's mostly using computers to do biology. But it’s a mixture of domain knowledge in bio, a good grasp of stats, and a whole lot of programming (usually not terribly difficult tasks, though).
Basic python and R are what you absolutely need to know (I started with intermediate python, no R). To do comp bio well, you need to learn computational statistics. I can’t stress enough how much knowing statistics matters in this case because there are so many assumptions that all sorts of libraries make about sequencing data and you need to decide for yourself how you’ll go about things and produce good science.
On a practical level for comp bio, I suggest: 1. Learning python & R 2. Basic knowledge 3. Knowing what your fave labs use for techniques (eg NGS? What kind of NGS?) and learning how it works, 4. Learning probability & statistics (lin alg always helps too) 5. If you got bored, learn clustering methods... Because, good god people in this field love seeing pretty tSNE figures and 98% of them have no idea how they just produced what they did but make biological assumptions based on it. You’ll probably have to learn them anyway
But as broad advice:
If you know a broad technique you're interested in, see which immunology lab does that and go from there.
If you already know the types of immunology questions you wanna go after, find the lab that studies that question, then see which techniques they use and learn those.
If biology, you need to focus on bio, stats, Python, R, and a hundred other specialized tools for working with data.
If you're more interested in programming, you can get away with much less bio/stats knowledge, unless you're working on developing low-level algorithms. A lot of the work has more to do with efficiently storing, moving, and visualizing large datasets. Bonus here is that much of this knowledge is transferable to other (much higher paying) domains if you get burned out or want to sell out.
My current job could be described as bio-aware web development, with an emphasis in data visualization. I need to know a decent amount of biology, but I can almost always defer stats to others in the lab with more expertise.
There’s a ton of courses online and https://www.edx.org/bio/rafael-irizarry is a good start.
Also, I'm a founder at Immunai and this is literally what we do. Please dm if you have further questions. Happy to help however I can.
Wow, incredible resource! Thanks for linking it up. Looks like the raw dataset is compact enough to run experimental inference right on your laptop ;)
A somewhat related, but certainly left-field question: is there a similar tutorial / library for exploring the frontiers of quantum computing and neuroscience?
Quantum Computing at the Frontiers of Biological Sciences
A brief search for comp immunology turns up things like data mining and mathematical modeling, I would assume Python and R would be a good place to start. You may even be able to find some lectures that cover some of the basics online.
And then
dn/ds
Learn everything that leads to and comes from these two equations.