detail.stats-methods: Several statistics
In PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses

Description Usage Arguments Value Examples

This generic function calculates some mixed statistics.

## S4 method for signature 'GENOME'
detail.stats(
	object,
	new.populations=FALSE,
	new.outgroup=FALSE,
	subsites=FALSE,
	biallelic.structure=FALSE,
	mismatch.distribution=FALSE,
	site.spectrum=TRUE,
        site.FST=FALSE
        )
## S4 method for signature 'GENOME'
get.detail(object, biallelic.structure=FALSE)

`object`	an object of class `"GENOME"`
`new.populations`	list of populations.
`new.outgroup`	outgroup sequences.
`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.
`biallelic.structure`	fixed and shared polymorphisms (stored in `GENOME.class@region.stats`).
`mismatch.distribution`	statistics based on mismatch distribution
`site.spectrum`	minor allele frequency of each SNP
`site.FST`	computes FST for each SNP

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

——————————————————————
The following Slots will be modified in the "GENOME" object
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`MDSD`	...
`MDG1`	...
`MDG2`	...
`region.stats`	the slot `biallelic.structure` and `minor.allele.freqs` will be filled

The function get.detail(GENOME.class, biallelic.structure=TRUE)
returns a matrix for each region, where

`0`	population is polymorphic, the remaining individuals are polymorphic

`1`	population is polymorphic, the remaining individuals are monomorphic

`2`	population is monomorphic, the remaining individuals are polymorphic

`3`	population is monomorphic, the remaining individuals are monomorphic with the same value

`4`	population is monomorphic, the remaining individuals are monomorphic with different values

# GENOME.class <- readData("\home\Alignments")
# GENOME.class
# GENOME.class <- set.populations(GENOME.class,list(1:10))
# GENOME.class <- detail.stats(GENOME.class)
# show the result:
# mismatch.values   <- get.detail(GENOME.class)
# bial.struc.values <- get.detail(GENOME.class, biallelic.structure=TRUE)
# GENOME.class@region.stats@biallelic.structure
# GENOME.class@region.stats@biallelic.structure[[1]]