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Bioinformatics. 2004 Oct 12;20(15):2421-8. Epub 2004 Apr 15.

How independent are the appearances of n-mers in different genomes?

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  • 1Department of Computer Science, University of Houston, TX 77204-3010, USA. yfofanov@uh.edu



Analysis of statistical properties of DNA sequences is important for evolutional biology as well as for DNA probe and PCR technologies. These technologies, in turn, can be used for organism identification, which implies applications in the diagnosis of infectious diseases, environmental studies, etc.


We present results of the correlation analysis of distributions of the presence/absence of short nucleotide subsequences of different length ('n-mers', n = 5-20) in more than 1500 microbial and virus genomes, together with five genomes of multicellular organisms (including human). We calculate whether a given n-mer is present or absent (frequency of presence) in a given genome, which is not the usually calculated number of appearances of n-mers in one or more genomes (frequency of appearance). For organisms that are not close relatives of each other, the presence/absence of different 7-20mers in their genomes are not correlated. For close biological relatives, some correlation of the presence of n-mers in this range appears, but is not as strong as expected. Suppressed correlations among the n-mers present in different genomes leads to the possibility of using random sets of n-mers (with appropriately chosen n) to discriminate genomes of different organisms and possibly individual genomes of the same species including human with a low probability of error.

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