A great effort has been made to identify and map a large set of single nucleotide polymorphisms. The goal is to determine human DNA variants that contribute most significantly to population variation in each trait. Different algorithms and software packages, such as PolyBayes and PolyPhred, have been developed to address this problem. We present strategies to detect single nucleotide polymorphisms, using chromatogram analysis and consensi of multiple aligned sequences. The algorithms were tested using HIV datasets, and the results were compared with those produced by PolyBayes and PolyPhred using the same dataset. Our algorithms produced significantly better results than these two software packages.