# Consequences of choice of a seed for random number generating algorithm?

Background

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.

Question

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.

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