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.