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CIPHER: a flexible and extensive workflow platform for integrative next-generation sequencing data analysis and genomic regulatory element prediction

机译:密码:用于集成下一代测序数据分析和基因组调节元件预测的灵活和广泛的工作流程平台

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摘要

Abstract Background Next-generation sequencing (NGS) approaches are commonly used to identify key regulatory networks that drive transcriptional programs. Although these technologies are frequently used in biological studies, NGS data analysis remains a challenging, time-consuming, and often irreproducible process. Therefore, there is a need for a comprehensive and flexible workflow platform that can accelerate data processing and analysis so more time can be spent on functional studies. Results We have developed an integrative, stand-alone workflow platform, named CIPHER, for the systematic analysis of several commonly used NGS datasets including ChIP-seq, RNA-seq, MNase-seq, DNase-seq, GRO-seq, and ATAC-seq data. CIPHER implements various open source software packages, in-house scripts, and Docker containers to analyze and process single-ended and pair-ended datasets. CIPHER’s pipelines conduct extensive quality and contamination control checks, as well as comprehensive downstream analysis. A typical CIPHER workflow includes: (1) raw sequence evaluation, (2) read trimming and adapter removal, (3) read mapping and quality filtering, (4) visualization track generation, and (5) extensive quality control assessment. Furthermore, CIPHER conducts downstream analysis such as: narrow and broad peak calling, peak annotation, and motif identification for ChIP-seq, differential gene expression analysis for RNA-seq, nucleosome positioning for MNase-seq, DNase hypersensitive site mapping, site annotation and motif identification for DNase-seq, analysis of nascent transcription from Global-Run On (GRO-seq) data, and characterization of chromatin accessibility from ATAC-seq datasets. In addition, CIPHER contains an “analysis” mode that completes complex bioinformatics tasks such as enhancer discovery and provides functions to integrate various datasets together. Conclusions Using public and simulated data, we demonstrate that CIPHER is an efficient and comprehensive workflow platform that can analyze several NGS datasets commonly used in genome biology studies. Additionally, CIPHER’s integrative “analysis” mode allows researchers to elicit important biological information from the combined dataset analysis.
机译:摘要背景下一代测序(NGS)方法通常用于识别驱动转录程序的关键监管网络。虽然这些技术经常用于生物学研究,但NGS数据分析仍然是一个具有挑战性,耗时的,并且经常是不可替代的过程。因此,需要一个全面且灵活的工作流平台,可以加速数据处理和分析,因此可以花功能研究花费更多的时间。结果我们开发了一个集成,独立的工作流平台,命名密码,用于系统分析几种常用的NGS数据集,包括芯片SEQ,RNA-SEQ,MNASE-SEQ,DNASE-SEQ,GRO-SEQ和ATAC- SEQ数据。 CIPTile实现各种开源软件包,内部脚本和Docker容器,以分析和处理单端和配对端的数据集。密码的管道进行广泛的质量和污染控制检查,以及全面的下游分析。典型的密码工作流程包括:(1)原始序列评估,(2)读取修剪和适配器拆卸,(3)读取映射和质量过滤,(4)可视化轨道产生,和(5)广泛的质量控制评估。此外,密码进行下游分析,例如:芯片-SEQ的窄峰呼叫,峰值注释和基序列识别,RNA-SEQ的差异基因表达分析,MNASE-SEQ的核心定位,DNase过敏部位映射,现场注释和DNASE-SEQ的基序鉴定,从全局运行(GRO-SEQ)数据中的新生转录分析,以及从ATAC-SEQ数据集进行染色质可访问性的表征。此外,密码包含一个“分析”模式,完成复杂的生物信息学任务,例如增强器发现,并提供将各种数据集集成在一起的功能。结论使用公共和模拟数据,我们证明了密码是一种高效且全面的工作流平台,可以分析常用于基因组生物学研究中的几个NGS数据集。此外,密码的集成“分析”模式允许研究人员从组合的数据集分析中引出重要的生物信息。

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