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README
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1/12/14
This repository contains several files that are helpful for reproducing the main figure of the Novembre et al 2008 ``Genes Mirror Geography in Europe'' paper.
The raw POPRES data must be accessed via dbGAP.
File descriptions:
==== Main files for plotting of PCA plot ====
PCA.txt : File with basic results for plotting
ID: The individual ID
plabels: Population labels
alabels: Abbreviated label
longitude: longitude used in study for that population
latitude: latitude used in study for that population
PC1: self-explanatory
PC2: self-explanatory
RotNS: North/South coordinate after rotation of PCA (see methods)
RotEW: East/west coordinate after rotation of PCA (see methods)
POPRESID_Color.txt : Color used for each individual in plot
==== Files for geographic plot ====
world_countries.rda : World polygon data
ColorTablePCmap.txt : Color used for each country in the geographic inset map
To generate the colored geographic map:
library(sp)
library(rgdal)
load("world_countries.rda")
coldatamap=read.table("ColorTablePCmap.txt",sep="\t",as.is=TRUE)
names(coldatamap)=c("cntry","color")
row.names(coldatamap)=toupper(coldatamap$cntry)
plot(worldpolys,xlim=c(-8,35),ylim=c(35,60),col=coldatamap[toupper(worldpolys$names),"color"])
===== Miscellaneous files =====
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.bim : A .bim file in plink format describing the 197,146 markers used in the thinned dataset for the PCA analysis.
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.fam : A .fam file in plink format describing the 1,387 individuals used in the thinned dataset for the PCA analysis.
affyProves-rsid.txt : A mapping of Affymetrix probe names to rsid's.
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.out0-PCA.par : Input file for smartpca
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.out0-PCA.eigs : Smartpca output with individual coordinates
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.out0-PCA.eval : Smartpca output with eigenvalues
POPRES_08_24_01.EuroThinFinal.LD_0.8.exLD.out0-PCA.snpeigs : Smartpca output containing SNP loadings that define the principal components