README.md

In royfrancis/pophelperSpatial: Spatial plots for q-matrices/qlists

pophelperSpatial 1.0.0

pophelperSpatial is an R package that incorporates spatial/geographic data with qlist or q-matrices such as ADMIXTURE, fastSTRUCTURE, STRUCTURE, TESS etc.

For a detailed demonstration and walkthrough, refer the online vignette.

Installation

You need to have R (> 3.3.2) statistical package installed on your system. R is open-source and freely available to download for Windows, Mac and other OS. Then, install the 'devtools' package and other dependencies.

# install packages from CRAN
install.packages(c("akima","Cairo","devtools","fields","ggplot2","gridExtra","gtable","PBSmapping","spatstat","tidyr"),dependencies=T)

Then, you can install pophelperSpatial and pophelper from github using the devtools package. pophelper package is needed to read in various run files.

#install from GitHub
install_github('royfrancis/pophelper')
install_github('royfrancis/pophelperSpatial')

Note that ggplot2 version must be 2.2.0 or higher. And pophelper version must be 2.0.0 or higher. Then load both libraries as below.

#load library for use
library(pophelper)
library(pophelperSpatial)

pophelperSpatial 1.0.0 has been tested on

• Windows 10 64bit, R 3.3.2
• Windows 7 64bit, R 3.3.2
• Ubuntu Linux 16.04.1 LTS 64bit, R 3.3.2
• Scientific Linux 6.8 (Carbon) 64bit, R 3.3.1

Functions

For help on any function, use ?plotQInterpolate. If inside RStudio press TAB inside a function to view arguments. plotQSpatial(<tab>).

plotQInterpolate()     # Spatially interpolate clusters from a STRUCTURE/TESS run file
plotQSpatial()         # Cluster by max assignment and plot points spatially

Fig. 1: Interpolated plot of a one-element qlist containing 6 clusters (K=6). The default interpolation algorithm (method) used was kriging. In this particular case, it is known that K=2, therefore only cluster 2 has useful information.

Fig. 2: Interpolated plot of one cluster (Cluster 2) containing 6 clusters (K=6) showing different interpolation methods. Row 1 from left: bilinear, bicubic and Inverse distance weighting. Row 2 from left: Nearest neighbour and Kriging.

Fig. 3: Interpolation plots showing some of the available colour palettes.

Fig. 4: Some of the plots created using the function plotQSpatial().

For detailed demonstration and description, refer the vignette.

Disclaimer

The pophelperSpatial R package is offered free and without warranty of any kind, either expressed or implied. I will not be held liable to you for any damage arising out of the use, modification or inability to use this program. Please make sure you verify all your results.

Contact

If you have any comments, suggestions or issues, report on the Github issues page.

2016 Roy M Francis

royfrancis/pophelperSpatial documentation built on May 27, 2019, 11:47 p.m.