Single Individual Haplotype Reconstruction Using Fuzzy C-Means Clustering With Minimum Error Correction

Abstract

Evolution of human genetics is one of the most interesting areas for researchers. Determination of Haplotypes not only makes valuable information for this purpose but also performs a major role in investigating the probable relation between diseases and genomes. Determining haplotypes by experimental methods is a time-consuming and expensive task. Recent progress in high throughput sequencing allows researchers to use computational methods for this purpose. Although, several algorithms have been proposed but they are less accurate when the error rate of input fragments increases. In this paper, first, a fuzzy conflict graph is constructed based on the similarities of all input fragments and next, the cluster centers are used as initial centers by fuzzy c-means (FCM) algorithm. The proposed method has been tested on several real datasets and compared with some current methods. The comparison with the existing approaches shows that our method can be a complementary role among the others.