I am trying to do a reproducible scientific analysis. My conclusions are not dependent on the random number generator, but the RNG does change the results ~1% between runs. I would like to define starting points for the RNG algorithm to reproduce the same result each time.
I am using the "Mersenne-Twister" algorithm only because it is the default in R.
I am using the RNG to sample parameter values from their distributions and I need about $10^7$ values for the complete analysis.
Are there any consequences of the choice of a starting value? Intuitively, R's
set.seed(0) feels very non-random, but rationally, I can't imagine why this would matter.