Department of Statistics, Macquarie University, North Ryde, NSW 2109, Australia.
BMC Bioinformatics. 2011 Jan 31;12:39. doi: 10.1186/1471-2105-12-39.
The use of high-throughput sequencing in combination with chromatin immunoprecipitation (ChIP-seq) has enabled the study of genome-wide protein binding at high resolution. While the amount of data generated from such experiments is steadily increasing, the methods available for their analysis remain limited. Although several algorithms for the analysis of ChIP-seq data have been published they focus almost exclusively on transcription factor studies and are usually not well suited for the analysis of other types of experiments.
Here we present ChIPseqR, an algorithm for the analysis of nucleosome positioning and histone modification ChIP-seq experiments. The performance of this novel method is studied on short read sequencing data of Arabidopsis thaliana mononucleosomes as well as on simulated data.
ChIPseqR is shown to improve sensitivity and spatial resolution over existing methods while maintaining high specificity. Further analysis of predicted nucleosomes reveals characteristic patterns in nucleosome sequences and placement.
高通量测序与染色质免疫沉淀(ChIP-seq)的结合使用,使得在高分辨率水平上研究全基因组蛋白结合成为可能。虽然此类实验产生的数据量在稳步增加,但可用的分析方法仍然有限。虽然已经发表了几种用于分析 ChIP-seq 数据的算法,但它们几乎专门针对转录因子研究,并且通常不适合于分析其他类型的实验。
本文提出了 ChIPseqR,这是一种用于分析核小体定位和组蛋白修饰 ChIP-seq 实验的算法。该新方法的性能在拟南芥单核小体的短读测序数据以及模拟数据上进行了研究。
ChIPseqR 被证明在保持高特异性的同时,提高了灵敏度和空间分辨率。对预测核小体的进一步分析揭示了核小体序列和位置的特征模式。