BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes
BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes
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DOI：
10.1186/s13059-017-1165-7
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发表时间：
2017-02-24
期刊：
影响因子：
12.3
通讯作者：
Markowetz, Florian
中科院分区：
文献类型：
--
作者：
de Santiago, Ines;Liu, Wei;Markowetz, Florian
来自ChIP-seq数据的转录因子结合的等位基因特异性测量是剖析非编码变体的等位基因效应及其对表型多样性的贡献的关键。然而，大多数检测等位基因不平衡的方法假设二倍体基因组。这一假设严重限制了它们对DNA拷贝数频繁变化的癌症样本的适用性。在这里，我们提出了一种称为BaalChIP的贝叶斯统计方法，以校正背景等位基因频率对观察到的ChIP-seq读取计数的影响。BaalChIP允许跨单个变体联合分析多个ChIP-seq样本，并在模拟中优于竞争方法。使用548个ENCODE ChIP-seq和6个靶向FAIRE-seq样本，我们表明BaalChIP有效地纠正了拷贝数变异的等位基因特异性分析，并提高了检测癌症基因组中推定顺式作用调控变体的能力。
Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods of detecting an allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy-number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and six targeted FAIRE-seq samples, we show that BaalChIP effectively corrects allele-specific analysis for copy-number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.