Abstract
BackgroundTranscription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation. ChIP-seq and DNase-seq have become the standard techniques for studying protein-DNA interactions and chromatin accessibility respectively, and comprehensive quality control (QC) and analysis tools are critical to extracting the most value from these assay types. Although many analysis and QC tools have been reported, few combine ChIP-seq and DNase-seq data analysis and quality control in a unified framework with a comprehensive and unbiased reference of data quality metrics.ResultsChiLin is a computational pipeline that automates the quality control and data analyses of ChIP-seq and DNase-seq data. It is developed using a flexible and modular software framework that can be easily extended and modified. ChiLin is ideal for batch processing of many datasets and is well suited for large collaborative projects involving ChIP-seq and DNase-seq from different designs. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. To the best of our knowledge, this atlas represents the most comprehensive ChIP-seq and DNase-seq related quality metric resource currently available. These historical metrics provide useful heuristic quality references for experiment across all commonly used assay types. Using representative datasets, we demonstrate the versatility of the pipeline by applying it to different assay types of ChIP-seq data. The pipeline software is available open source at https://github.com/cfce/chilin.ConclusionChiLin is a scalable and powerful tool to process large batches of ChIP-seq and DNase-seq datasets. The analysis output and quality metrics have been structured into user-friendly directories and reports. We have successfully compiled 23,677 profiles into a comprehensive quality atlas with fine classification for users.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1274-4) contains supplementary material, which is available to authorized users.
Highlights
Transcription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation
ChiLin quality metrics evaluation We first evaluated the influence of read length on the stability of ChiLin quality control (QC) metrics
Only in DNaseseq is Fraction of reads in peaks (FRiP) anti-correlated with estimated fragment size, indicating that shorter fragment length help obtain higher signal-to-noise ratio for DNase-seq (Additional file 3: Figure S3a-d)
Summary
ChiLin quality metrics evaluation We first evaluated the influence of read length on the stability of ChiLin QC metrics. The cumulative distributions of these metrics (Additional file 4: Figure S4) reveal that >85 % of samples are characterized by sequence quality score >25, uniquely mapped read ratio >0.5 and PBC >0.8 This observation suggests that users may use these cutoffs in assessing the quality of their ChIP-seq data and deciding whether to investigate further. For numerous R-based ChIP-seq analysis tools including CHIPQC, htseqtools, ChIP-seeker and the phantompeakqualtools package used in ENCODE program, quality control is their main concerns and alignment and/or peak files are required as input They can only provide a specific and less comprehensive evaluation based on only a small number of the metrics available in ChiLin. ChiLin has been designed to address all the needs for both data processing and quality control. In combination with the data quality atlas we have assembled, ChiLin is a powerful tool for supporting ChIP-seq and DNase-seq studies of any size
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