LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations.
LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations.
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DOI：
10.1093/nar/gkv803
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发表时间：
2015-09-30
影响因子：
14.9
通讯作者：
Gerstein M
中科院分区：
文献类型：
--
作者：
Lochovsky L;Zhang J;Fu Y;Khurana E;Gerstein M
在癌症研究中，在编码区对突变率的背景模型进行了广泛的校准，从而识别出许多经常发生突变的驱动基因。非编码区也与疾病相关；然而，对它们的背景模型还没有进行过详细的研究。这在一定程度上是由于有限的非编码功能注释。此外，巨大的突变异质性和相邻位点之间的潜在相关性会导致突变计数的大量过度分散，导致背景率估计有问题。在这里，我们将使用一种名为LARVA的新计算框架来解决这些问题。它将变体与一组全面的非编码功能元件集成在一起，用β-二项分布对元件的突变计数进行建模，以处理过度分散。此外，幼虫使用区域基因组特征，如复制时机，以更好地估计局部突变率和突变热点。我们证明了幼虫在760个全基因组肿瘤序列上的有效性，表明它识别了众所周知的非编码驱动因素，例如TERT启动子的突变。此外，Larva强调了几个新的高度突变的调控位点，它们可能是潜在的非编码驱动因素。我们将Larva作为软件工具提供，并将高度突变的注释作为在线资源发布(larva.gersteinLab.org)。
In cancer research, background models for mutation rates have been extensively calibrated in coding regions, leading to the identification of many driver genes, recurrently mutated more than expected. Noncoding regions are also associated with disease; however, background models for them have not been investigated in as much detail. This is partially due to limited noncoding functional annotation. Also, great mutation heterogeneity and potential correlations between neighboring sites give rise to substantial overdispersion in mutation count, resulting in problematic background rate estimation. Here, we address these issues with a new computational framework called LARVA. It integrates variants with a comprehensive set of noncoding functional elements, modeling the mutation counts of the elements with a β-binomial distribution to handle overdispersion. LARVA, moreover, uses regional genomic features such as replication timing to better estimate local mutation rates and mutational hotspots. We demonstrate LARVA's effectiveness on 760 whole-genome tumor sequences, showing that it identifies well-known noncoding drivers, such as mutations in the TERT promoter. Furthermore, LARVA highlights several novel highly mutated regulatory sites that could potentially be noncoding drivers. We make LARVA available as a software tool and release our highly mutated annotations as an online resource (larva.gersteinlab.org).