Joined: Mar. 2006
|Quote (skeptic @ July 19 2007,17:45)|
|No insults here just looking for some ideas. I have a feeling someone will say something or make a comparison that will push me in the right direction. I'm trying to model this and the vagueness of random is difficult to program.|
We know that mutations do not occur equally across the genome so that throws that out. Eric would always tell me that mutations occurred without regard for the resulting fitness of the organism and thus random. The problem with that is it's a retrospective analysis and again difficult to program.
I could cop-out and just apply a mutation rate arbitrarily but I'd like a better treatment than that and it wouldn't work for my ultimate goal anyway.
So, my main hang up is I'm looking for something more than semantic that I can use. I've found in the past that when I'm confronted by a problem the more opinions I can collect the better likelihood that someone else will say something or use a particular analogy that either inspires me or clarifies the problem. Just wanting to pick you guys brains for my own gains. Sorry if that sounds selfish.
Okay, so you started by querying NCBI for their SNPs and indels, right?
So what exactly do you hope to learn from people on a board that you can't learn from looking at the primary data? Surely you looked at the available empirical data before you decided to start a fight over what "random" mean, right? Surely you'd prefer to draw your conclusions based on the data, and not by analogy, right? Far less "semantic" that way.
What kind of answer are you expecting anyway? Someone to give you a list of every single 10-mer, with all the probabilities of every kind of mutation in every position for each?
Or the whole human genome (or mouse, or fly, or whatever), with every base pair annotated with the odds of every kind of mutation happening there?
If you want, for instance, the percentages of mutations found in ENU-generated mutants, those papers exist. Surely you aren't asking for those.