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ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment, even within amplified genomic regions

Naim U Rashid1, Paul G Giresi2, Joseph G Ibrahim1, Wei Sun13* and Jason D Lieb2*

Author affiliations

1 Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

2 Department of Biology, Carolina Center for Genome Sciences, and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

3 Department of Genetics and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

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Citation and License

Genome Biology 2011, 12:R67  doi:10.1186/gb-2011-12-7-r67

Published: 25 July 2011

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.

Software website: http://code.google.com/p/zinba/ webcite