ABSTRACT

Accurately detecting genome-wide nucleosome positions is important to understanding chromatin remodeling events in gene regulation. NPS is a widely used software package for detecting nucleosome positions from MNase-seq data, but its accuracy needs much improvement. We developed the improved NPS (iNPS) algorithm by adding two major modifications to NPS to precisely determine the boundary of nucleosomes and to merge or separate shoulder peaks based on their relationship to neighboring major peaks. iNPS achieved significantly better performance compared with NPS: it unambiguously detects 60% more nucleosomes; the detected nucleosomes display significantly more uniform distributions of nucleosome 'widths' and neighboring center-center distances, give rise to sharper wave-like patterns and better phasing of average nucleosome profiles at key regulatory regions, and show higher consistency between independent subsets of input data than NPS. Furthermore, iNPS identifies sharper nucleosome profiles with higher quality and lower false positive rates than other published methods. Consequently, only iNPS, but not NPS, detected differentially positioned nucleosomes between resting and activated CD4+ T cells that display clear enrichment for pathways relevant to T cell activation, and enrichment for binding motifs of densely interacting transcription factors. Finally, iNPS has the unique advantage of detecting different types of nucleosomes that are associated with different biological properties based on nucleosome shapes.

Download: The iNPS package and user mannual are freely downloadable from the following links: Latest version: 'iNPS_V1.2.2.zip' (Some minor changes)

Earlier versions: 'iNPS_V1.2.1.zip' (Some minor changes)

'iNPS_V1.2.0.zip' (This version can address paired-end sequencing data.)

'iNPS_V1.1.2.zip' (Some minor change)

'iNPS_V1.1.zip' (This version can automatically split the input data by chromosomes.)

'iNPS_V1.0.zip'