数据分辨率对三维结构推断方法的影响。

Impact of data resolution on three-dimensional structure inference methods.

作者信息

Park Jincheol, Lin Shili

机构信息

Department of Statistics, Keimyung University, 1095 Dalgubeol-daero, Dalseo-gu, Daegu 42601, South Korea.

Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH, USA.

出版信息

BMC Bioinformatics. 2016 Feb 6;17:70. doi: 10.1186/s12859-016-0894-z.

DOI:10.1186/s12859-016-0894-z

PMID:26852142

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4744395/

Abstract

BACKGROUND

Assays that are capable of detecting genome-wide chromatin interactions have produced massive amount of data and led to great understanding of the chromosomal three-dimensional (3D) structure. As technology becomes more sophisticated, higher-and-higher resolution data are being produced, going from the initial 1 Megabases (Mb) resolution to the current 10 Kilobases (Kb) or even 1 Kb resolution. The availability of genome-wide interaction data necessitates development of analytical methods to recover the underlying 3D spatial chromatin structure, but challenges abound. Most of the methods were proposed for analyzing data at low resolution (1 Mb). Their behaviors are thus unknown for higher resolution data. For such data, one of the key features is the high proportion of "0" contact counts among all available data, in other words, the excess of zeros.

RESULTS

To address the issue of excess of zeros, in this paper, we propose a truncated Random effect EXpression (tREX) method that can handle data at various resolutions. We then assess the performance of tREX and a number of leading existing methods for recovering the underlying chromatin 3D structure. This was accomplished by creating in-silico data to mimic multiple levels of resolution and submit the methods to a "stress test". Finally, we applied tREX and the comparison methods to a Hi-C dataset for which FISH measurements are available to evaluate estimation accuracy.

CONCLUSION

The proposed tREX method achieves consistently good performance in all 30 simulated settings considered. It is not only robust to resolution level and underlying parameters, but also insensitive to model misspecification. This conclusion is based on observations made in terms of 3D structure estimation accuracy and preservation of topologically associated domains. Application of the methods to the human lymphoblastoid cell line data on chromosomes 14 and 22 further substantiates the superior performance of tREX: the constructed 3D structure from tREX is consistent with the FISH measurements, and the corresponding distances predicted by tREX have higher correlation with the FISH measurements than any of the comparison methods.

SOFTWARE

An open-source R-package is available at http://www.stat.osu.edu/~statgen/Software/tRex.

摘要

背景

能够检测全基因组染色质相互作用的分析方法已产生了大量数据，并极大地增进了我们对染色体三维（3D）结构的理解。随着技术变得越来越复杂，正在产生分辨率越来越高的数据，从最初的1兆碱基（Mb）分辨率提升到当前的10千碱基（Kb）甚至1 Kb分辨率。全基因组相互作用数据的可用性使得开发用于恢复潜在3D空间染色质结构的分析方法成为必要，但挑战也很多。大多数方法是为分析低分辨率（1 Mb）数据而提出的。因此，它们在更高分辨率数据下的行为尚不清楚。对于此类数据，关键特征之一是在所有可用数据中“0”接触计数的比例很高，换句话说，就是零值过多。

结果

为了解决零值过多的问题，在本文中，我们提出了一种截断随机效应表达（tREX）方法，该方法可以处理各种分辨率的数据。然后，我们评估了tREX和一些现有的领先方法在恢复潜在染色质3D结构方面的性能。这是通过创建模拟多种分辨率水平的虚拟数据并将这些方法进行“压力测试”来实现的。最后，我们将tREX和比较方法应用于一个有荧光原位杂交（FISH）测量数据的Hi-C数据集，以评估估计准确性。

结论

所提出的tREX方法在所有考虑的30种模拟设置中均表现出一致的良好性能。它不仅对分辨率水平和潜在参数具有鲁棒性，而且对模型错误设定不敏感。这一结论是基于在3D结构估计准确性和拓扑相关结构域保存方面的观察得出的。将这些方法应用于14号和22号染色体上的人类淋巴母细胞系数据进一步证实了tREX的优越性能：由tREX构建的3D结构与FISH测量结果一致，并且tREX预测的相应距离与FISH测量结果的相关性高于任何一种比较方法。