Clustering and variance maps for cryo-electron tomography using wedge-masked differences
Clustering and variance maps for cryo-electron tomography using wedge-masked differences
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DOI：
10.1016/j.jsb.2011.05.011
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发表时间：
2011-09-01
影响因子：
3
通讯作者：
Mastronarde, David N.
中科院分区：
文献类型：
--
作者：
Heumann, John M.;Hoenger, Andreas;Mastronarde, David N.
冷冻电子断层扫描以纳米分辨率对冷冻水合生物样品进行 3D 成像。重建体积存在低信噪比 (SNR)(1) 和系统性缺失断层扫描数据导致的伪影。这两个问题都可以通过组合具有不同方向的多个子体积来解决，假设它们包含相同的结构。需要聚类（无监督分类）来确保或验证群体同质性，但这个过程由于信噪比差和数据缺失的问题而变得复杂，这些问题首先导致考虑多个子卷。在这里，我们描述了一种面对这些困难的聚类和方差映射的新方法。组合子体积被视为真实子体积的估计，并且针对各个子体积计算缺失数据的影响。然后根据预期子体积和观察到的子体积之间的差异进行聚类和方差映射。我们证明，这种新方法比两种当前广泛使用的技术更快、更准确。 (C) 2011 Elsevier Inc. 保留所有权利。
Cryo-electron tomography provides 3D imaging of frozen hydrated biological samples with nanometer resolution. Reconstructed volumes suffer from low signal-to-noise-ratio (SNR)(1) and artifacts caused by systematically missing tomographic data. Both problems can be overcome by combining multiple subvolumes with varying orientations, assuming they contain identical structures. Clustering (unsupervised classification) is required to ensure or verify population homogeneity, but this process is complicated by the problems of poor SNR and missing data, the factors that led to consideration of multiple subvolumes in the first place. Here, we describe a new approach to clustering and variance mapping in the face of these difficulties. The combined subvolume is taken as an estimate of the true subvolume, and the effect of missing data is computed for individual subvolumes. Clustering and variance mapping then proceed based on differences between expected and observed subvolumes. We show that this new method is faster and more accurate than two current, widely used techniques. (C) 2011 Elsevier Inc. All rights reserved.