Computational prediction of nucleosome positioning by calculating the relative fragment frequency index of nucleosomal sequences

Abstract 

We developed an accurate method to predict nucleosome positioning from genome sequences by refining the previously developed method of Peckham et al. (2007) [19]. Here, we used the relative fragment frequency index we developed and a support vector machine to screen for nucleosomal and linker DNA sequences. Our twofold cross-validation revealed that the accuracy of our method based on the area under the receiver operating characteristic curve was 81%, whereas that of Peckham’s method was 75% when both of two nucleosomal sequence data obtained from independent experiments were used for validation. We suggest that our method is more effective in predicting nucleosome positioning.

Abbreviations: SVM, support vector machine, ChIP, chromatin immunoprecipitation assay, ROC, receiver operating characteristic, AUC, the area under the ROC curve, HMM, hidden Marcov model, RFFI, relative fragment frequency index

Keywords: Nucleosome, Computational prediction, Support vector machine