Field of Science

Two views of the same data

Here is some data from a series of runs where I simultaneously varied the lengths and numbers of the recombining fragments, so that the total amount of recombination remained the same (e.g. 1000 fragments 100 bp long or 50 fragments 2 kb long). I concluded that the runs were close to equilibrium and that the runs that got their recombination with the shortest fragments reached the highest equilibrium score.

But wait! This is the same data, now with the X-axis on a log scale. Now I see something quite different - after the first few cycles, the scores of all the runs are going up at the same rate (same slope), and their rate of increase is very log-linear. None of the runs show any sign of approaching equilibrium (i.e. of leveling off).

I had said I would always do runs both from above (a seeded genome) and from below (a random-sequence genome) and take as equilibrium the score the up and down runs converged on. I didn't do that here, but I see I should have.

I don't know whether I've done any runs that went long enough that the score obviously leveled off when plotted on a log scale. If not I should.

***Later: Some of the runs I've done clearly do level off even on the log scale. This is good. But some of the runs that I've been treating as at equilibrium (runs for which I've done an up run but not a down run) haven't leveled off at all, so I'm not justified in making any assumptions about where they'll stop. Time to run them longer, and do some down run counterparts.

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