Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks...Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.展开更多
基金Foundation items： This study was supported by the National 973 project of China （2011CBA01101） and the National Natural Science Foundation of China （30871343 and 31130051 ） Acknowledgments： We are thankful to Shao-Bin XU （Kunming Institute of Zoology, CAS） for his support on super-computing service, and to Yu-qi ZHAO （Kunming Institute of Zoology, CAS） for his helpful discussion.
文摘Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.
