basic manipulation of SNP arrays for population genetics

Question

[platypus998]

Could you tell me a basic workflow of SNP array manipulations?

Suppose that I have two data sets:

population 1: I have a ped file genotyped by Affymetrix array

population 2: a ped file by Illumina array

My understanding is:

1. run strand_check.py
   1. select a bgl file of reference genome data (all pops or sub-pops in 1000 genomes)
   2. change a format of ped files (target pops) to bgl file format (using ped_to_bgl)
   3. make .markers files from .bim format (writing a script)
   4. split .bgl and .markers files into each chromosome for both reference and target pops (writing a script)
   5. get common SNPs between a reference and a target pop from .bgl and .markers files generated in #1-3 and #1-4. (writing a script)
   6. run strand_check.py for #1-5
2. bgl_to_ped
3. plink merge
4. then do population analyses (pca, admixture, migration etc.)

Does it correct?

Sometimes, an array has genotype data with "0". In that case, which answer should I adopt?

1. replace genotype "0" with a genotype on an annotation file of each platform and run strand_check.py
2. remove "0" genotyped sites from initial ped files before running strand_check.py
3. replace genotype "0" with a genotype on an annotation file and keep positions of replacement before running strand_check.py. To avoid excessive reduction of SNP sites, replace "replaced genotypes" with "0" again after running strand_check.py (1.6 in the example above).