K-Mer Index of DNA Sequence Based on Hash Algorithm

K-mer frequency statistics of biological sequences is a very important and important problem in biological information processing. This paper addresses the problem of index k-mer for large scale data reading DNA sequences in a limited memory space and time. Using the hash algorithm to establish index, the index model is set up to base pairing, and get the length of k-mer statistic information quickly, so as to avoid searching all the sequences of the index. At the same time, the program uses hash table to establish index and build search model, and uses the zipper method to resolve the conflict in the case of address conflict. Algorithm of time complexity analysis and experimental results show that compared with the traditional indexing methods, the algorithm of the performance improvement is obvious, and very suitable for to be used in the k-mer length change with a wide range