SKM-SNP, SNP markers detection program, is proposed to identify a set of relevant SNPs for the association between a disease and multiple marker genotypes. We employ a subspace categorical clustering algorithm to compute a weight for each SNP in the group of patient samples and the group of normal samples, and use the weights to identify the subsets of relevant SNPs that categorize these two groups. The experiments on both Schizophrenia and Parkinson Disease data sets containing genome-wide SNPs are reported to demonstrate the program. Results indicate that our method can find some relevant SNPs that categorize the disease samples. The online SKM-SNP program is available at http://www.math.hkbu.edu.hk/~mng/SKM-SNP/SKM-SNP.html.