ckaksAA: Compute the conditional kaks(conditional selection pressure)...

In superkits/CorMut: Detect the correlated mutations based on selection pressure

Description

Compute the conditional kaks(conditional selection pressure) among codons, the amino mutation in a site will be treated as whole in computation.

Usage

ckaksAA(seq_formated, kaks = T, lod_cut = 2, setPosition = c())

Arguments

seq_formated	Formated alignment sequence. i.e. the result after the treatment of DataFormatCorMut.
kaks	A logical variable to indicate whether kaks is turn on or off, if kaks is TRUE, conditional kaks will be computed only among positive seelction sites, or if kaks is FALSE, conditional kaks will be computed only among all sites of sequence.
lod_cut	The LOD confidence score cutoff, the default value is 2. If lod is larger than 2, it means the positive selection of individual site or the conditional selection pressure among sites are significant.
setPosition	The positions of sequence to compute. setPosition should be a vector of interger type.

Value

An ckaks instance will be returned. ckaks includes two slots of matrix type:ckaks and lod, which indicate the conditional kaks and LOD confidence score respectively.

Author(s)

Zhenpeng Li

References

Chen, L., Perlina, A. & Lee, C. J. Positive selection detection in 40,000 human immunodeficiency virus (HIV) type 1 sequences automatically identifies drug resistance and positive fitness mutations in HIV protease and reverse transcriptase. Journal of virology 78,3722-3732 (2004).

See Also

filterSites,plot.ckaks,ckaksCodon

Examples

examplefile=system.file("extdata","PI_treatment.aln",package="CorMut")
example=seqFormat(examplefile)
result=ckaksAA(example)

superkits/CorMut documentation built on May 8, 2019, 11:59 p.m.