With the rapid development of high-throughput sequencing technologies, genome-wide profiling of nucleosome positioning has become increasingly affordable. Many future studies will investigate the dynamic behavior of nucleosome positioning in cells in different states or exposed to different conditions. However, a robust method to effectively identify the regions of differential nucleosome positioning (RDNPs) was not previously available. We develop a novel computational approach, DiNuP, that compares the nucleosome profiles generated by high-throughput sequencing between different conditions. DiNuP provides a statistical p-value for each identified RDNP based on the difference of read distributions. DiNuP also empirically estimates the FDR as a cutoff when two samples have different sequencing depths and differentiate reliable RDNPs from the background noise. Evaluation of DiNuP showed it to be both sensitive and specific for the detection of changes in nucleosome location, occupancy and fuzziness. RDNPs that were identified using publicly available datasets revealed that nucleosome positioning dynamics are closely related to the epigenetic regulation of transcription. Please cite: Fu K, Tang Q, Feng J, Liu XS, Zhang Y. DiNuP: a systematic approach to identify regions of differential nucleosome positioning. Bioinformatics 2012; 28(15):1965-71.