linkage.stats-methods: Linkage Disequilibrium
In PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses

Description Usage Arguments Details Value References Examples

A generic function to calculate some linkage disequilibrium statistics.

## S4 method for signature 'GENOME'
linkage.stats(object,new.populations=FALSE,subsites=FALSE,detail=FALSE,
			do.ZnS,do.WALL=TRUE)
## S4 method for signature 'GENOME'
get.linkage(object)

`object`	An object of class `"GENOME"`
`new.populations`	list of populations. default=`FALSE`
`subsites`	`"transitions"`: SNPs that are transitions. `"transversions"`: SNPs that are transversions. `"syn"`: synonymous sites. `"nonsyn"`: nonsynonymous sites. `"exon"`: SNPs in exon regions. `"intron"`: SNPs in intron regions. `"coding"`: SNPs in coding regions (CDS). `"utr"`: SNPs in UTR regions. `"gene"`: SNPs in genes. default:`FALSE`
`detail`	if you want to calculate some detailed statistics. This can be considerably slower! default:`FALSE`
`do.ZnS`	calculate ZnS, ZA and ZZ
`do.WALL`	calculate Wall's B/Q

Note, the pairwise comparisons are computed via combn(n.snps,2).

The return value is a modified object of class "GENOME"

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The following slots will be modified in the "GENOME" object
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	Slot	Reference	Description
1.	`Wall.B`	[2]	Wall $B$ statistic (only adjacent positions are considered)
2.	`Wall.Q`	[2]	Wall $Q$ statistic (only adjacent positions are considered)
3.	`Kelly.Z_nS`	[3]	Kelly $Z_nS$ statistic (if detail==`TRUE`)
4.	`Rozas.ZA`	[1]	Rozas $ZA$ statistic (adjacent positions, if detail==`TRUE`)
5.	`Rozas.ZZ`	[1]	Rozas $ZZ$ statistic ($ZZ=ZA-Z_nS$, if detail==`TRUE`)

[1] Rozas, J., M.Gullaud, G.Blandin, and M.Aguade(2001). DNA variation at the rp49 gene region of Drosophila simulans: evolutionary inferences from an unusual haplotype structure. Genetics 158(3),1147-1155

[2] Wall, J.(1999). Recombination and the power of statistical tests of neutrality. Genet Res 74, 65-79

[3] Kelly,J.K. (1997). A test of neutrality based on interlocus associations. Genetics 146: 1197-1206

# GENOME.class <- readData("\home\Alignments")
# GENOME.class
# GENOME.class <- linkage.stats(GENOME.class)
# GENOME.class <- linkage.stats(GENOME.class,list(1:4,5:10),subsites="syn")
# GENOME.class <- linkage.stats(GENOME.class,list(c("seq1","seq5","seq3"),
# c("seq2","seq8")))
# GENOME.class <- linkage.stats(GENOME.class, detail=TRUE)
# show the result:
# get.linkage(GENOME.class)
# GENOME.class@Wall.B --> population specific view
# GENOME.class@region.stats