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PopGenome (version 2.7.5)

neutrality.stats-methods: Neutrality Statistics

Description

This generic function calculates some neutrality statistics.

Usage

# S4 method for GENOME
neutrality.stats(object,new.populations=FALSE,new.outgroup=FALSE,
subsites=FALSE,detail=FALSE, FAST=FALSE, do.R2=FALSE)
# S4 method for 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" --------------------------------------------------------- The following slots will be modified in the "GENOME" object ---------------------------------------------------------

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

Run this code
# NOT RUN {
# 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
# GENOME.class@region.stats

# }

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