Metabolomics-NEG

We converted the original data into mzXML format using ProteoWizard software. We used an internal program for processing, developed by R for peak extraction, calibration and integration based on XCMS. We further processed the data matrix by removing more than 50% of the peaks of missing values in the samples. Using half of the minimum of the simulation method to simulate and fill in some missing values of the original data. The new standardized data matrix was produced by the internal standard (IS). And an in-house MS2 database (BiotreeDB), KEGG(www.genome.jp/kegg) and online database of HMDB (www.hmdb.ca) were applied to metabolite annotation. The cutoff value for comments was 0.3. In order to compare the differences of metabolomic characteristics between healthy people and IgAN patients, we used multivariate statistical analysis, including orthogonal projections to latent structures-discriminant analysis (OPLS-DA) and the method of principal component analysis (PCA).

本研究使用ProteoWizard软件将原始数据转换为mzXML格式。采用基于XCMS包、由R语言开发的自研程序完成数据处理，具体包括峰提取、校准与积分操作。随后对数据矩阵进行进一步处理：剔除样本中缺失值占比超过50%的峰。通过最小值一半的模拟方法，对原始数据中的部分缺失值进行模拟填充。借助内标（internal standard, IS）完成标准化处理，生成标准化后的全新数据矩阵。同时采用自研MS2数据库（BiotreeDB）、KEGG（www.genome.jp/kegg）以及HMDB在线数据库（www.hmdb.ca）开展代谢物注释工作，并将注释阈值设定为0.3。为比较健康人群与IgA肾病（IgAN）患者的代谢组学特征差异，本研究采用多元统计分析方法，包括正交偏最小二乘判别分析（OPLS-DA）与主成分分析（PCA）。