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DIAlignR 提供了在 DIA 和靶向蛋白质组学中跨远距离运行的精确保留时间对齐。

DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics.

机构信息

From the ‡Department of Molecular Genetics, University of Toronto, Toronto, ON M5G 1A8, Canada;; The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada.

¶Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305.

出版信息

Mol Cell Proteomics. 2019 Apr;18(4):806-817. doi: 10.1074/mcp.TIR118.001132. Epub 2019 Jan 31.

Abstract

Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) is widely used for proteomics analysis given its high throughput and reproducibility, but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human plasma remains challenging. Heterogeneity in large-scale studies can be caused by large time intervals between data acquisition, acquisition by different operators or instruments, and intermittent repair or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and, successively, performance of SWATH-MS data analysis. Here, we present a novel algorithm for RT alignment of SWATH-MS data based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm does not impose a chronological order of elution and allows for alignment of elution-order-swapped peaks. Furthermore, allowing RT mapping in a certain window around a coarse global fit makes it robust against noise. On a manually validated dataset, this strategy outperformed the current state-of-the-art approaches. In addition, on real-world clinical data, our approach outperformed global alignment methods by mapping 98% of peaks compared with 67% cumulatively. DIAlignR reduced alignment error up to 30-fold for extremely distant runs. The robustness of technical parameters used in this pairwise alignment strategy is also demonstrated. The source code is released under the BSD license at https://github.com/Roestlab/DIAlignR.

摘要

序贯窗口采集所有理论片段离子质谱 (SWATH-MS) 因其高通量和可重复性而被广泛用于蛋白质组学分析,但确保在人类血浆等异质样本的大规模研究中分析物的定量一致仍然具有挑战性。大规模研究中的异质性可能是由于数据采集之间的时间间隔较大、不同操作人员或仪器采集、以及间歇性修复或更换部件(如液相色谱柱)引起的,所有这些都会影响保留时间 (RT) 的重现性,进而影响 SWATH-MS 数据分析的性能。在这里,我们提出了一种基于使用混合动态规划方法直接对齐原始 MS2 色谱图的 SWATH-MS 数据 RT 对齐的新算法。该算法不施加洗脱的时间顺序,并且允许对齐洗脱顺序交换的峰。此外,允许在粗略全局拟合的某个窗口中进行 RT 映射,使其具有抗噪能力。在手动验证的数据集上,该策略优于当前最先进的方法。此外,在真实的临床数据上,与累积 67%相比,我们的方法通过映射 98%的峰来优于全局对齐方法。DIAlignR 将对齐错误减少了多达 30 倍,即使是在非常遥远的运行中也是如此。还证明了这种成对对齐策略中使用的技术参数的稳健性。该源代码在 BSD 许可证下发布,网址为 https://github.com/Roestlab/DIAlignR。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e29b/6442363/88121a4077ff/zjw0051959080006.jpg

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