proFIA：流动注射分析与高分辨率质谱联用的数据预处理流程
proFIA: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry
摘要：
动机：流动注射-高分辨率质谱联用技术（FIA-HRMS）是一种很有前途的高通量代谢组学方法。然而，FIA-HRMS数据不能用依赖于液相色谱分离的当前软件工具进行预处理，或仅处理低分辨率数据。结果如下：因此，我们开发了proFIA包，它实现了一套创新的算法来预处理FIA-HRMS原始文件，并生成峰强度表。工作流程包括3个步骤：i）噪声估计、峰检测和定量，ii）样品间峰分组，以及iii）缺失值插补。此外，我们还实现了一个新的指标来量化由于基质效应而导致的特征峰形状的潜在变化。预处理速度快（每个文件不到15秒），主要参数（ppm和dmz）的值可以很容易地从仪器的质量分辨率中推断出来。应用到两个代谢组学数据集（包括加标血清样本）显示出高精度（96%）和召回率（98%）相比，手动集成。这些结果表明，proFIA实现了非常有效和稳健的FIA-HRMS数据的检测和定量，并为高通量表型分析提供了新的机会。供货情况：proFIA软件（以及plasFIA数据集）可作为R包在Bioconductor存储库（http：//bioconductor.org/packages/proFIA）上获得，并作为Galaxy模块在主工具箱（https：//toolshed.g2.bx.psu.edu/）和Workflow 4 Metabolomics在线基础设施（http：workflow4metabolomics.org）上获得。联系人：alexis. cea.fr和etienne.thevenot@cea. fr。
英文摘要：
Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. Results: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: i) noise estimation, peak detection and quantification, ii) peak grouping across samples, and iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping. Availability: The proFIA software (as well as the plasFIA data set) is available as an R package on the Bioconductor repository (http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main Toolshed (https://toolshed.g2.bx.psu.edu/) and on the Workflow4Metabolomics online infrastructure (http://workflow4metabolomics.org). Contacts: alexis.delabriere@cea.fr and etienne.thevenot@cea.fr.
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