Big O notation is a little woolly all by itself. I think you know this, so I won't drive the point into the ground. For some value of "faster" (where faster is not better), an O(N²)-bounded algorithm grows faster than an O(N)-bounded one. That doesn't ensure the latter is always preferred; it only indicates.

I stated a range to exclude the possibility of better (for some value of "better") algorithms than O(N) (or worse than O(N²)). This is not a sophisticated or advanced node. This is a pretty basic introduction to thinking about how to attack a problem set.

As stated clearly in my FINAL WARNING, the script shown is not any sort of solution to the bioinformatics exercise, here only hinted at. It's a demonstration of technique, only loosely related to the preceding essay. There are only ten simple records; almost anything would work. If we wait, somebody may golf it down to a one-liner.

The difference between my code and your code is that, as the data set gets larger and the problem set more complex, my editing may go a bit more smoothly. I don't doubt that you'll wind up with a really efficient script; you're good. But as the stress piles on, I'll accommodate it; my pieces are flexible and modular (in the wider sense). To put it another way, I would fear to maintain your code, while you would only hate to maintain mine.