seqinr (version 1.0-1)

dinucleotides: Statistical over- and under- representation of dinucleotides in a sequence

Description

These two functions compute two different types of statistics for the measure of statistical dinculeotide over- and under-representation : the rho statistic, and the z-score, each computed for all 16 dinucleotides.

Usage

rho(sequence)
zscore(sequence, simulations = NULL, modele, ... )

Arguments

sequence

A nucleic acids sequence

simulations

If NULL, analytical solution is computed when available (models base and {codon}). Otherwise, it should be the number of permutations for the z-score computation

modele

A string of characters describing the model chosen for the random generation

...

Optional parameters for specific model permutations are passed on to permutation function.

Value

• a table containing the computed statistic for each dinucleotide

Details

The rho statistic, as presented in Karlin S., Cardon LR. (1994), can be computed on each of the 16 dinucleotides. It is the frequence of dinucleotide xy divided by the product of frequencies of nucleotide x and nucleotide y. It is equal to 1.00 when dinucleotide xy is formed by pure chance, and it is superior (respectively inferior) to 1.00 when dinucleotide xy is over- (respectively under-) represented.

The zscore statistic, as presented in Palmeira, L., Gu�guen, L. and Lobry JR. (in prep.). The statistic is the normalization of the rho statistic by its expectation and variance according to a given random sequence generation model, and follows the standard normal distribution. This statistic can be computed with several models (cf. permutation for the description of each of the models). We provide analytical calculus for two of them: the base permutations model and the codon permutations model. The base model allows for random sequence generation by shuffling (with/without replacement) of all bases in the sequence. Analytical computation is available for this model.

The position model allows for random sequence generation by shuffling (with/without replacement) of bases within their position in the codon (bases in position I, II or III stay in position I, II or III in the new sequence.

The codon model allows for random sequence generation by shuffling (with/without replacement) of codons. Analytical computation is available for this model.

The syncodon model allows for random sequence generation by shuffling (with/without replacement) of synonymous codons.

References

citation("seqinr") Karlin S. and Cardon LR. (1994) Computational DNA sequence analysis. Annu Rev Microbiol, 48, 619--54.

Palmeira, L., Gu�guen, L. and Lobry JR. (in prep) UV-targeted dinucleotides are not depleted in light-exposed Prokaryotic genomes.

See Also

permutation

Examples

sequence=sample(s2c('acgt'),6000,rep=TRUE)
rho(sequence)
zscore(sequence,modele='base')
zscore(sequence,modele='codon')
zscore(sequence,1000,modele='syncodon')

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