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

Abstract

BackgroundNext-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.ResultsWe 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.ConclusionsUsing 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1770-1) contains supplementary material, which is available to authorized users.

NGseqBasic - a single-command UNIX tool for ATAC-seq, DNaseI-seq, Cut-and-Run, and ChIP-seq data mapping, high-resolution visualisation, and quality control

“…Many of the currently available chromatin accessibility and ChIP sequencing analysis pipelines generate the output data to make such a "checkpoint data set" [3][4][5][6][7][8] . However, they do not collect the data to a single-click loadable visualisation, including all the metrics and analysis reports (for tool comparisons, see Supplementary Table 1) and therefore are more time consuming and require higher levels of computational expertise of the user.…”

YAMP: a containerised workflow enabling reproducibility in metagenomics research

“…YAMP is developed in Nextflow, a workflow management system that allows the effortlessly developing, deploying, and executing of complex distributed computational workflows [6], and which has been used in several life-science projects (e.g., [31,32,33]). Nextflow allows for user-transparent high-level parallelisation, and offers out-of-the-box support for distributed computational environments, ensuring the scalability of large projects.…”

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

“…There are several tools designed for NGS analysis. Galaxy [47], Taverna [48], Snakemake [49], Nextflow [50], CIPHER [51], and bcbio-nextgen [52] all provide NGS data analysis infrastructure in various computer language environments. For example, tools such as VIPER [2], TRAPLINE [53], HppRNA [54], and QuickRNASeq [55] are RNA-Seq pipelines based on the Snakemake framework, combining tools in numerous languages including R, Python, Perl, C++, or Java.…”