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BMC Genomics. 2018 Jul 31;19(1):563. doi: 10.1186/s12864-018-4943-z.

ATAC2GRN: optimized ATAC-seq and DNase1-seq pipelines for rapid and accurate genome regulatory network inference.

Author information

1
National Institute of Dental and Craniofacial Research, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20816, USA.
2
National Institute of Dental and Craniofacial Research, National Institutes of Health, 10 Center Drive, Bethesda, MD, 20816, USA. jchiorini@dir.nidcr.nih.gov.

Abstract

BACKGROUND:

Chromatin accessibility profiling assays such as ATAC-seq and DNase1-seq offer the opportunity to rapidly characterize the regulatory state of the genome at a single nucleotide resolution. Optimization of molecular protocols has enabled the molecular biologist to produce next-generation sequencing libraries in several hours, leaving the analysis of sequencing data as the primary obstacle to wide-scale deployment of accessibility profiling assays. To address this obstacle we have developed an optimized and efficient pipeline for the analysis of ATAC-seq and DNase1-seq data.

RESULTS:

We executed a multi-dimensional grid-search on the NIH Biowulf supercomputing cluster to assess the impact of parameter selection on biological reproducibility and ChIP-seq recovery by analyzing 4560 pipeline configurations. Our analysis improved ChIP-seq recovery by 15% for ATAC-seq and 3% for DNase1-seq and determined that PCR duplicate removal improves biological reproducibility by 36% without significant costs in footprinting transcription factors. Our analyses of down sampled reads identified a point of diminishing returns for increased library sequencing depth, with 95% of the ChIP-seq data of a 200 million read footprinting library recovered by 160 million reads.

CONCLUSIONS:

We present optimized ATAC-seq and DNase-seq pipelines in both Snakemake and bash formats as well as optimal sequencing depths for ATAC-seq and DNase-seq projects. The optimized ATAC-seq and DNase1-seq analysis pipelines, parameters, and ground-truth ChIP-seq datasets have been made available for deployment and future algorithmic profiling.

KEYWORDS:

ATAC-seq; DNA footprinting; DNase1-seq; Optimization; Pipeline; Regulation

PMID:
30064353
PMCID:
PMC6069842
DOI:
10.1186/s12864-018-4943-z
[Indexed for MEDLINE]
Free PMC Article

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