Abstract. In the era of modern sequencing technology, we are collecting a vast amount of biological sequence data. The technology to store, process, and analyze the data is not as cheap as to generate the sequencing data. As a result, the need for devising efficient data compression and data reduction techniques is growing by the day. Although there exist a number of sophisticated general purpose compression algorithms, they are not efficient to compress biological data. As a result, we need specialized compression algorithms targeting biological data. Five different NGS data compression problems have been identified and studied. In this article we propose a novel algorithm for one of these problems. We have done extensive experiments using real sequencing reads of various lengths. The simulation results reveal that our proposed algorithm is indeed competitive and performs better than the best known algorithms existing in the current literature.