title: ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions.
abstract: ZINBA (Zero-Inflated Negative Binomial Algorithm) identifies genomic regions enriched in a variety of ChIP-seq and related next-generation sequencing experiments (DNA-seq), calling both broad and narrow modes of enrichment across a range of signal-to-noise ratios. ZINBA models and accounts for factors that co-vary with background or experimental signal, such as G/C content, and identifies enrichment in genomes with complex local copy number variations. ZINBA provides a single unified framework for analyzing DNA-seq experiments in challenging genomic contexts.
authors.affiliation: Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: Naim U
authors.initials: NU
authors.lastname: Rashid
authors.forename: Paul G
authors.initials: PG
authors.lastname: Giresi
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
authors.forename: Wei
authors.initials: W
authors.lastname: Sun
authors.forename: Jason D
authors.initials: JD
authors.lastname: Lieb
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D056915:DNA Copy Number Variations; D023281:Genomics / Q000379:methods*; D008957:Models, Genetic; D015233:Models, Statistical; D017422:Sequence Analysis, DNA; D012984:Software