Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis

CSA: a web service for the complete process of ChIP-Seq analysis

BACKGROUND

Chromatin immunoprecipitation sequencing (ChIP-seq) is a technology that combines chromatin immunoprecipitation (ChIP) with next generation of sequencing technology (NGS) to analyze protein interactions with DNA. At present, most ChIP-seq analysis tools adopt the command line, which lacks user-friendly interfaces. Although some web services with graphical interfaces have been developed for ChIP-seq analysis, these sites cannot provide a comprehensive analysis of ChIP-seq from raw data to downstream analysis.

RESULTS

In this study, we develop a web service for the whole process of ChIP-Seq Analysis (CSA), which covers mapping, quality control, peak calling, and downstream analysis. In addition, CSA provides a customization function for users to define their own workflows. And the visualization of mapping, peak calling, motif finding, and pathway analysis results are also provided in CSA. For the different types of ChIP-seq datasets, CSA can provide the corresponding tool to perform the analysis. Moreover, CSA can detect differences in ChIP signals between ChIP samples and controls to identify absolute binding sites.

CONCLUSIONS

The two case studies demonstrate the effectiveness of CSA, which can complete the whole procedure of ChIP-seq analysis. CSA provides a web interface for users, and implements the visualization of every analysis step. The website of CSA is available at http://CompuBio.csu.edu.cn.

RACS: rapid analysis of ChIP-Seq data for contig based genomes

BACKGROUND

Chromatin immunoprecipitation coupled to next generation sequencing (ChIP-Seq) is a widely-used molecular method to investigate the function of chromatin-related proteins by identifying their associated DNA sequences on a genomic scale. ChIP-Seq generates large quantities of data that is difficult to process and analyze, particularly for organisms with a contig-based sequenced genomes that typically have minimal annotation on their associated set of genes other than their associated coordinates primarily predicted by gene finding programs. Poorly annotated genome sequence makes comprehensive analysis of ChIP-Seq data difficult and as such standardized analysis pipelines are lacking.

RESULTS

We present a one-stop computational pipeline, "Rapid Analysis of ChIP-Seq data" (RACS), that utilizes traditional High-Performance Computing (HPC) techniques in association with open source tools for processing and analyzing raw ChIP-Seq data. RACS is an open source computational pipeline available from any of the following repositories https://bitbucket.org/mjponce/RACS or https://gitrepos.scinet.utoronto.ca/public/?a=summary&p=RACS . RACS is particularly useful for ChIP-Seq in organisms with contig-based genomes that have poor gene annotation to aid protein function discovery.To test the performance and efficiency of RACS, we analyzed ChIP-Seq data previously published in a model organism Tetrahymena thermophila which has a contig-based genome. We assessed the generality of RACS by analyzing a previously published data set generated using the model organism Oxytricha trifallax, whose genome sequence is also contig-based with poor annotation.

CONCLUSIONS

The RACS computational pipeline presented in this report is an efficient and reliable tool to analyze genome-wide raw ChIP-Seq data generated in model organisms with poorly annotated contig-based genome sequence. Because RACS segregates the found read accumulations between genic and intergenic regions, it is particularly efficient for rapid downstream analyses of proteins involved in gene expression.