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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

机译:ZINBA将局部协变量与DNA-seq数据整合在一起,即使在扩增的基因组区域内,也能识别出丰富的狭窄区域

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摘要

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.
机译:ZINBA(零负负二项式算法)可识别富含各种ChIP-seq的基因组区域和相关的下一代测序实验(DNA-seq),从而可在一系列信噪比下实现广泛和狭窄的富集模式比率。 ZINBA对与背景或实验信号共同变化的因素(例如G / C含量)进行建模和说明,并识别具有复杂局部拷贝数变异的基因组富集。 ZINBA提供了一个统一的框架,用于在具有挑战性的基因组环境中分析DNA-seq实验。

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