Thanks

Each SNP is a single base-pair in the genome at which two alternative versions are measured. Given two possible alleles (say A and B), there are three possible genotypes (AA, AB, BB). The data are genotypes.

The chromosome and base-pair coordinate is given in the map file. These coordinates are with respect to a genome build, such as hg18. http://genome.ucsc.edu/cgi-bin/hgGateway?db=hg18

These SNPs were likely selected because they are otherwise well characterized, so in essence they are standardized.

http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#ped

Are these beds, bims, and fams in a binary or ascii format? I assume binary because I wasn’t able to open them in a text editor.

bed and bim are binary

http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#bed

Besides ADMIXTURE (which I can’t use because like most people in the world, I use Windows ), is there any way to read these files? Could I write a custom binary processor? Is there any ascii version of the data? Is that what the csv is?

you can convert bed/bim to ped/map using plink (see links above)

Cheers

no idea about windows. .bed is binary. the text version is .ped.

What information is actually contained within these files? ADMIXTURE’s page says it’s “multilocus SNP genotype datasets.” What the heck is that? What part of the genome are they examining for single nucleotide polymorphisms? Are these standard points for examination? How many points per individual?

the data have snps and individuals. also stuff like sex, phenotype, etc., but that’s extraneous for our purpose. in these data 27,000 snps per individual.

Or to put it another way, it’s creating K fictitious populations that are as genetically distinct as possible, and showing the proportion each modern population has of these fictitious populations?

yes

4) Is it possible to specify that one of your K populations is completely one of the modern populations? Could you say, as an example, that you want the French and the Moroccans to show up as 100% one of the resultant clusters?

yes. see follow up post.

These bar charts that you end up with are rather hard to follow. Do people ever make pie charts for these things? How about a map of the Earth with the ranges of each of the K populations? You can clearly see in your K=12 map, for example, that the pink population is most prevalent in northeastern Europe and dissipates moving outward from there.

yes. i have thought of that. need to get fluid with R’s map functions. i don’t want to learn GIS. the thematic heat maps are easy with paid software, but i’m not going to shell out $400 for that

1) What does “pedigree formatted” mean? Are these beds, bims, and fams in a binary or ascii format? I assume binary because I wasn’t able to open them in a text editor. Besides ADMIXTURE (which I can’t use because like most people in the world, I use Windows ), is there any way to read these files? Could I write a custom binary processor? Is there any ascii version of the data? Is that what the csv is?

2) What information is actually contained within these files? ADMIXTURE’s page says it’s “multilocus SNP genotype datasets.” What the heck is that? What part of the genome are they examining for single nucleotide polymorphisms? Are these standard points for examination? How many points per individual?

3) If I understand correctly, ADMIXTURE is doing is a cluster analysis? It’s crunching the data, finding the eigenvectors for the given K, and displaying the vector components of each population mapped onto the eigenvectors? Or to put it another way, it’s creating K fictitious populations that are as genetically distinct as possible, and showing the proportion each modern population has of these fictitious populations?

4) Is it possible to specify that one of your K populations is completely one of the modern populations? Could you say, as an example, that you want the French and the Moroccans to show up as 100% one of the resultant clusters?

5) These bar charts that you end up with are rather hard to follow. Do people ever make pie charts for these things? How about a map of the Earth with the ranges of each of the K populations? You can clearly see in your K=12 map, for example, that the pink population is most prevalent in northeastern Europe and dissipates moving outward from there.

Thanks,
Garvan

I’m using Python 2.6.6 as well, on Debian unstable.

Have you ever used Shellfish to do PCA? It lets you create “loadings” for reference populations, so that you can see where samples fall on the dimensions generated by the reference data without changing the dimensions themselves. Basically, it’s like the advanced genetic similarity plot on 23andMe. I’m trying to create a loading for the HGDP populations, but now I may as well add these in.