The presented study focused on SNP data analysis of 2,645 individuals of two dam, two sire breeds and one national genetic resource. The DNA was sequenced using three commercial chips. The common panel was distinguished as set of markers included in each SNP chip. Markers were distributed over 18 autosomal chromosomes plus chromosome X. There were observed disproportion in number of SNPs per chromosomes, almost twelve percent in chromosome one and less than two percent in chromosome twelve. Finally, the SNPs of 1195 Czech large white, 450 Czech landrace, 92 Duroc, 187 Pietrain and 349 Přeštice black pied animals were analysed. Three methods were used for determining panels of the most informative SNPs: Wright’s fixation index (FST), principal component analysis (PCA) and random forest (RF) method. It was found that the SNPs in the generated panels overlapped to some extent between the methods, with the greatest number of common markers found between principal component analysis and the fixation index. In conclusion, all three methods were generally effective in identifying reduced panels of the most informative SNPs. The best predictive performance was achieved for the random forest.