ZINBA integrates local covariates with DNA-seq data to identify broad and narrow regions of enrichment,even within amplified genomic regions |
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| Authors: | Naim U Rashid Paul G Giresi Joseph G Ibrahim Wei Sun Jason D Lieb |
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| Institution: | (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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| 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. |
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