Abstract: Monte Carlo simulations are useful to verify the significance of
data. Genomic regularities, such as the nucleotide correlations or the not
uniform distribution of the motifs throughout genomic or mature mRNA sequences,
exist and their significance can be checked by means of the Monte Carlo test.
The test needs good quality random sequences in order to work, moreover they
should have the same nucleotide distribution as the sequences in which the
regularities have been found. Random DNA sequences are also useful to estimate
the background score of an alignment, that is a threshold below which the
resulting score is merely due to chance. We have developed RANDNA, a free
software which allows to produce random DNA or RNA sequences setting both their
length and the percentage of nucleotide composition. Sequences having the same
nucleotide distribution of exonic, intronic or intergenic sequences can be
generated. Its graphic interface makes it possible to easily set the parameters
that characterize the sequences being produced and saved in a text format file.
The pseudo-random number generator function of Borland Delphi 6 is used, since
it guarantees a good randomness, a long cycle length and a high speed. We have checked the quality of sequences generated by the software,
by means of well-known tests, both by themselves and versus genuine random
sequences. We show the good quality of the generated sequences. The software,
complete with examples and documentation, is freely available to users from:
http://www.introni.it/en/software.
Keywords: Random nucleotides, entropy, information theory, pseudo-random generator
