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A short survey of computational analysis methods in analysing ChIP-seq data

机译:ChIP-seq数据分析中的计算分析方法简短概述

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Chromatin immunoprecipitation followed by massively parallel next-generation sequencing (ChIP-seq) is a valuable experimental strategy for assaying protein-DNA interaction over the whole genome. Many computational tools have been designed to find the peaks of the signals corresponding to protein binding sites. In this paper, three computational methods, ChIP-seq processing pipeline (spp), PeakSeq and CisGenome, used in ChIP-seq data analysis are reviewed. There is also a comparison of how they agree and disagree on finding peaks using the publically available Signal Transducers and Activators of Transcription protein 1 (STAT1) and RNA polymerase II (PolII) datasets with corresponding negative controls.
机译:染色质免疫沉淀后再进行大规模并行的下一代测序(ChIP-seq),是测定整个基因组中蛋白质-DNA相互作用的有价值的实验策略。已经设计了许多计算工具来找到对应于蛋白质结合位点的信号的峰。本文综述了ChIP-seq数据分析中使用的三种计算方法:ChIP-seq处理管道(spp),PeakSeq和CisGenome。还比较了它们在使用公开的信号转导子和转录蛋白1(STAT1)和RNA聚合酶II(PolII)数据集以及相应的阴性对照获得峰时,如何同意和不同意。

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