I'm pretty well a newcomer to this beautiful boundless world of Bioinformatics.
So far, I've learned R, Bioconductor, Python and a little bit of Biopython. And I wanna just know which tool makes sense to use when it comes down to dealing with basic genomic data analysis tasks, Bioconductor or Biopython ?
Personally, I find using Bioconductor.is much easier than using Biopython.
I'd argue they aren't as comparable/interchangeable as they first appear.
Sure, R and Python can accomplish much the same thing as one another, and each have different strengths (R has great data viz and stats, python has more powerful infrastructure tools etc).
BioPython and Bioconductor are a bit different though IMO. Bioconductor is much more suited to data analysis, particularly of large -omic datasets. You can certainly do this in python too, but much less of this already exists, or is made of slightly dodgy ports of things (e.g. there's still no good python alternative to DESeq2 AFAIK).
I'd suggest python is much friendlier to use from a data wrangling/manipulation perspective in a remote terminal environment, and its a nice scripting language for automating repetitive tasks etc, but if you're really trying to get to grips with data analysis, bioconductor is probably the better choice (and I say that as a primarily python user). Where BioPython in particular really shines is taking the hard work out of futzing with tricky file formats (looking at you Genbank 😡) and extracting data/info for you to use downstream in friendly ways.
Got it. Many thanks.