Last data update: 2014.03.03

R: Compute isometric log ratio coordinates.
HWIlrR Documentation

Compute isometric log ratio coordinates.

Description

HWIlr computes isometric log ratio coordinates for genotypic compositions (AA, AB, BB)

Usage

HWIlr(X, zeroadj = 0.5)

Arguments

X

A matrix of genotype counts, markers in rows, counts for AA, AB and BB in three columns

zeroadj

Adjustment for zeros (0.5 by defaults)

Value

A matrix of log ratio coordinates.

Author(s)

Jan Graffelman (jan.graffelman@upc.edu)

References

Egozcue, J.J., Pawlowsky-Glahn, V., Mateu-Figueras, G. and Barcelo-Vidal, C. (2003) Isometric Logratio Transformations for Compositional Data Analysis. Mathematical Geology 35(3), pp. 279-300.

Graffelman, J. and Egozcue, J. J. (2011) Hardy-Weinberg equilibrium: a non-parametric compositional approach. In: Vera Pawlowsky-Glahn and Antonella Buccianti (eds.) Compositional Data Analysis: Theory and Applications, John Wiley & Sons, Ltd, pp. 207-215

See Also

HWAlr,HWClr

Examples

X <- HWData(100,100)
Y <- HWIlr(X)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(HardyWeinberg)
Loading required package: mice
Loading required package: Rcpp
mice 2.25 2015-11-09
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HardyWeinberg/HWIlr.Rd_%03d_medium.png", width=480, height=480)
> ### Name: HWIlr
> ### Title: Compute isometric log ratio coordinates.
> ### Aliases: HWIlr
> ### Keywords: misc
> 
> ### ** Examples
> 
> X <- HWData(100,100)
> Y <- HWIlr(X)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>