Grouping germplasm lines and assisting plant breeding using large number of SNP marker have become well accepted due to constant price drops of SNP markers brought about by the advance at high-throughput sequencing technology. How to handle the large SNP datasets becomes an increasing interest, and the user-friendly statistical methodologies are in demand. In this study, four grouping procedures (NJ, SNPhylo , ADMIXTURE + SNPs, and the ADMIXTURE + TagSNPs which we modified from ADMIXTURE + SNPs), were deployed to group 490 corn inbreds into 3 and 6 subgroups using 525,141 SNP markers and their performance were evaluated with four criteria (PCA Scatter Plot, GD, PIC, and BIC). The result showed that PCA Scatter Plot and BIC （BICBW, SBIC）among the four criteria are more powerful in revealing between-subgroup variation, whereas GD and PIC showed less powerful. All four grouping procedures were effective and could be adopted in grouping germplasm. Particularly, ADMIXTURE+TagSNPs was the most effective in delineating subgroups with clear boundary and very little between-group mixing, while SNPhylo was the least effective. ADMIXTURE + TagSNPs required fewer SNP markers thus would cost less than other three procedures, and therefore was highly recommended for germplasm study and marker-assisted breeding.