neutrality.stats-methods: Neutrality Statistics

In pievos101/PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses

Neutrality Statistics

Description

This generic function calculates some neutrality statistics.

Usage

## S4 method for signature 'GENOME'
neutrality.stats(object,new.populations=FALSE,new.outgroup=FALSE,
subsites=FALSE,detail=FALSE, FAST=FALSE, do.R2=FALSE)
## S4 method for signature 'GENOME'
get.neutrality(object,theta=FALSE,stats=TRUE)

Arguments

object	an object of class "GENOME"
new.populations	list of populations. default:FALSE
new.outgroup	vector of outgroup sequences. default:FALSE
subsites	"transitions": SNPs that are transitions. "transversions": SNPs that are transversions. "syn": synonymous sites. "nonsyn": non-synonymous 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	default:FALSE, TRUE for some detailed statistics. Note: slows down calculations!
FAST	Fast computation. only works if there is no outgroup defined.
do.R2	Ramos-Onsins' & Rozas' R2
stats	show the results of each statistic. default:TRUE
theta	show the theta values. default:FALSE

Value

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.	n.segregating.sites		Total number of segregating sites
2.	Tajima.D	[1]	Tajima's' D statistic 1989
3.	Fu.Li.F	[3]	Fu & Li's' F* statistic 1993
4.	Fu.Li.D	[3]	Fu & Li's D* statistic 1993
5.	Fay.Wu.H	[6]	Fay & Wu's H statistic 2000
6.	Zeng.E	[7]	Zeng's E statistic 2006
7.	Strobeck.S	[5]	Strobeck's S statistic 1987 (if detail==TRUE)
8.	Fu.F_S	[4]	Fu's F$_S$ statistic 1997 (if detail==TRUE)
9.	Rozas.R_2	[2]	Ramos-Onsins' & Rozas' $R_2$ statistic 2002
10.	theta_Tajima	[1]
11.	theta_Watterson
12.	theta_Fu.Li	[3]
13.	theta_Achaz.Watterson
14.	theta_Achaz.Tajima
15.	theta_Fay.Wu	[6]
16.	theta_Zeng	[7]

References

[1] Tajima, F.(1989) Statistical Method for Testing the Neutral Mutation Hypothesis by DNA Polymorphism. Genetics, 123(3): 585-595.

[2] Ramos-Onsins, S.E. and J.Rozas (2002). Statistical Properties of New Neutrality Tests Against Population Growth. Mol.Biol.Evol.19(12),2092-2100

[3] Fu, Y.X. and W.H.Li (1993). Statistical Tests of Neutrality of Mutations. Genetics 133(3),693-709

[4] Fu, Y.-X.(1997). Statistical Tests of Neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147(2),915-925.

[5] Strobeck, C. (1987). Average number of nucleotide differences in a sample from a single subpopulation: a test for population subdivision. Genetics 117, 149-153

[6] Fay, J.C. and C.-I. Wu (2000). Hitchhiking under positive Darwinian selection. Genetics 155 (3),1405-1413

[7] Zeng, K., Y.-X. Fu, S. Shi, and C.-I. Wu (2006). Statistical tests for detecting positive selection by utilizing high-frequency variants. Genetics 174, 1431-1439

Examples

# GENOME.class <- readData("\home\Alignments")
# GENOME.class
# GENOME.class <- neutrality.stats(GENOME.class, FAST=TRUE)
# GENOME.class <- neutrality.stats(GENOME.class,list(1:4,5:10),subsites="syn")
# GENOME.class <- neutrality.stats(GENOME.class,list(c("seq1","seq5","seq3"),
# c("seq2","seq8")))
# GENOME.class <- neutrality.stats(GENOME.class,detail=TRUE)
# show the result:
# get.neutrality(GENOME.class)
# GENOME.class@Tajima.D --> population specific view
# detail = TRUE
# [e-mail]

pievos101/PopGenome documentation built on May 23, 2024, 7:31 p.m.