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ChIP-R:从多个重复样本中组装可重复的ChIP-seq和ATAC-seq峰集。

ChIP-R: Assembling reproducible sets of ChIP-seq and ATAC-seq peaks from multiple replicates.

作者信息

Newell Rhys, Pienaar Richard, Balderson Brad, Piper Michael, Essebier Alexandra, Bodén Mikael

机构信息

School of Chemistry and Molecular Biosciences, The University of Queensland, Cooper Road, QLD 4072, Australia.

School of Biomedical Science, The University of Queensland, QLD, Australia.

出版信息

Genomics. 2021 Jul;113(4):1855-1866. doi: 10.1016/j.ygeno.2021.04.026. Epub 2021 Apr 18.

Abstract

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the primary protocol for detecting genome-wide DNA-protein interactions, and therefore a key tool for understanding transcriptional regulation. A number of factors, including low specificity of antibody and cellular heterogeneity of sample, may cause "peak" callers to output noise and experimental artefacts. Statistically combining multiple experimental replicates from the same condition could significantly enhance our ability to distinguish actual transcription factor binding events, even when peak caller accuracy and consistency of detection are compromised. We adapted the rank-product test to statistically evaluate the reproducibility from any number of ChIP-seq experimental replicates. We demonstrate over a number of benchmarks that our adaptation "ChIP-R" (pronounced 'chipper') performs as well as or better than comparable approaches on recovering transcription factor binding sites in ChIP-seq peak data. We also show ChIP-R extends to evaluate ATAC-seq peaks, finding reproducible peak sets even at low sequencing depth. ChIP-R decomposes peaks across replicates into "fragments" which either form part of a peak in a replicate, or not. We show that by re-analysing existing data sets, ChIP-R reconstructs reproducible peaks from fragments with enhanced biological enrichment relative to current strategies.

摘要

染色质免疫沉淀测序(ChIP-seq)是检测全基因组DNA-蛋白质相互作用的主要方法,因此也是理解转录调控的关键工具。包括抗体特异性低和样品细胞异质性在内的多种因素,可能导致“峰”识别工具输出噪声和实验假象。即使峰识别工具的准确性和检测一致性受到影响,对来自相同条件的多个实验复制品进行统计合并,也能显著提高我们区分实际转录因子结合事件的能力。我们采用秩积检验来统计评估任意数量的ChIP-seq实验复制品的可重复性。我们通过多个基准测试证明,我们改进的方法“ChIP-R”(发音为“chipper”)在ChIP-seq峰数据中恢复转录因子结合位点的性能与同类方法相当或更好。我们还表明,ChIP-R可扩展用于评估ATAC-seq峰,即使在低测序深度下也能找到可重复的峰集。ChIP-R将复制品中的峰分解为“片段”,这些片段要么是复制品中峰的一部分,要么不是。我们表明,通过重新分析现有数据集,ChIP-R相对于当前策略,能从片段中重建具有增强生物学富集的可重复峰。

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