autocorrelation: Spatial Autocorrelation

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/RClone.R

Description

autocorrelation computes kinship coefficients (Loiselle or Ritland) between pairs of individuals within specific ranges of geographic distance.

Usage

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autocorrelation(data1, haploid = FALSE, coords = NULL, vecpop = NULL, listMLL = NULL, 
	Loiselle = FALSE, Ritland = FALSE, 
	genet = FALSE, central_coords = FALSE, random_unit = FALSE, weighted = FALSE, 
	class1 = FALSE, class2 = FALSE, d = NULL, vecdist = NULL, 
	graph = FALSE, nbrepeat = NULL, export = FALSE)

Arguments

data1

a Rclone table with one allele per column.

haploid

logical, option, haploid indicates the ploidy level of data1.

coords

a table with coordinates of every units in data1.

vecpop

vector, option, vecpop indicates the population name of each unit of data1, if data1 contains several populations. If data1 contains only one population, leave vecpop = NULL.

listMLL

option, a custom list of MLL.

Loiselle

logical, if TRUE, Loiselle kinship coefficients are computed.

Ritland

logical, if TRUE, Ritland kinship coefficients are computed.

genet

option, TRUE keeps only MLG of data1.

central_coords

option, if genet = TRUE, central_coords computes central coordinates for each MLG/MLL.

random_unit

option, if genet = TRUE, random_unit keeps coordinates of only one unit per MLG/MLL.

weighted

option, if genet = TRUE, weighted computes a weighted matrix over ramets.

class1

option, if TRUE, computes distance classes of d equidistant classes.

class2

option, if TRUE, computes distance classes of d classes with the same number of units pairs each.

d

numeric, option, number of distance classes. By default, d = 10.

vecdist

option, a custom vector distance to construct distance classes.

graph

option, if TRUE, displays kinship coefficient between pairs plotted against distance.

nbrepeat

numeric, option, if pvalue = TRUE, nbrepeat is the number of resampling to enable pvalues computation.

export

option, if TRUE, graph is saved as .eps into working directory.

Details

By default, d = 10 and autocorrelation computes 10 equidistant distance classes for all the ramets pairs.
The function proposes 3 others options:

The function computes one of the two average kinship coefficients: Loiselle and Ritland.

Autocorrelation can be compute on ramets level, or genet level with:

A permutation approach could be perform to assess pvalue and confidence intervals by permutation of the geographic coordinates among units.
For the re-sampling approach, a unit of each MLG/MLL is randomly picked at each permutation.
The p-value of mean kinship coefficients is related with the overall mean kinship coefficient: upper p-value (Monte Carlo) if greater or equal to the overall; otherwise, lower p-value.
For b and Sp, their p-value correspond to upper p-value.

Value

autocorrelation returns a list (one population) or lists of list (several populations) of:

Author(s)

Creator/Author: Diane Bailleul <[email protected]>
Author: Sophie Arnaud-Haond <[email protected]>
Contributor: Solenn Stoeckel

The R implementation of RClone was written by Diane Bailleul.

The design was inspired by GenClone program described in Arnaud-Haond & Belkhir (2007).

References

Loiselle et al., 1995, Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae).

Ritland, 1996, A marker-based method for inferences about quantitative inheritance in natural populations.

Arnaud-Haond et al., 2007, Standardizing methods to address clonality in population studies.

Vekemans & Hardy, 2004, New insights from fine-scale spatial genetic structure analyses in plant populations.

See Also

kinship_Loiselle, kinship_Ritland

Examples

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data(posidonia)
data(coord_posidonia)

distGC <- c(0,10,15,20,30,50,70,76.0411073)

#res1 <- autocorrelation(posidonia, coords = coord_posidonia, Loiselle = TRUE, nbrepeat = 1000)

#res2 <- autocorrelation(posidonia, coords = coord_posidonia, Loiselle = TRUE, 
#class2 = TRUE, d = 7)

#res2[[1]] #Main_results
#res1[[2]] #Slope_and_Sp_index
#res2[[3]] #Slope_and_Sp_index

#res3 <- autocorrelation(posidonia, coords = coord_posidonia, Loiselle = TRUE, 
#vecdist = distGC, graph = TRUE)

dbailleul/RClone documentation built on May 12, 2017, 8:56 p.m.