Evaluation of the occurrence possibility of SNP in Brassica napus with sliding window features by using RBF networks

Abstract

We extract some physical and chemical features related to the occurrence of single nucleotide polymorphism (SNP) from three groups of sliding windows around SNP site, and then make the predictions about accuracy by using radial basis function (RBF) networks. The result of the forward sliding windows suggests that the accuracies and Matthews correlation coefficient (MCC values) ascend with the increasing of length of sliding windows. The accuracies range from 73.27 % to 80.69 %, and MCC values range from 0.465 to 0.614. The backward sliding windows and the sliding windows with fixed length three are designed to find the crucial sites related to SNP. The results imply that the occurrence possibility of SNP relies heavily on the above physical and chemical features of sites which are at a distance around 20 bases from the SNP site. Compared with the support vector machine (SVM), our RBF network approach has achieved more satisfactory results.