R or Biopython for Natural Product Research?

Question

[dicenhour]

I am a natural product chemist interested in learning how to use bioinformatics to conduct my search for interesting biosynthetic gene clusters more efficiently, but I'm not sure where to start.

Which would be the best language to learn; python or R? I have started to learn both but I need to devote my attention to one instead of half heartedly learning two.

For starters, I would like to simply access a genome; search for a pfam; determine how many times it appears in the genome; determine its neighboring genes.

If anyone has advice regarding the matter, I would greatly appreciate it.

[Joe]

I think the short answer to this is it really doesn't matter - both are pretty functional, so take your pick :)

FWIW, I think python has more 'general purpose' modules for regular computing. Certainly, for gluing pipelines of other tools together, interacting with generic APIs etc, it will likely win out over R - but I am biased.

Answer 1

[Jean-Karim Heriche]

For the tasks you describe, I use perl and in particular the Ensembl perl API if the genome is annotated in Ensembl. Otherwise, I use R for statistics, machine learning and some computational biology. I had to go with R because what I needed a few years ago wasn't available in python or perl. My impression is that nowadays, python can do a decent bit of both bioinformatics and machine learning (but maybe not so much statistics and computational biology compared to R). If you know one well, you won't need the other for most of what you need to do. So the choice should be to go for what you think will take you furthest for the least amount of time invested.