Metabolomics data analyses rely on the use of bioinformatics tools. Many integrated multi-functional tools have been developed for untargeted metabolomics data processing and have been widely used. More alternative platforms are expected for both basic and advanced users. Integrated mass spectrometry-based untargeted metabolomics data mining (IP4M) software was designed and developed. The IP4M, has 62 functions categorized into 8 modules, covering all the steps of metabolomics data mining, including raw data preprocessing (alignment, peak de-convolution, peak picking, and isotope filtering), peak annotation, peak table preprocessing, basic statistical description, classification and biomarker detection, correlation analysis, cluster and sub-cluster analysis, regression analysis, ROC analysis, pathway and enrichment analysis, and sample size and power analysis. Additionally, a KEGG-derived metabolic reaction database was embedded and a series of ratio variables (product/substrate) can be generated with enlarged information on enzyme activity. A new method, GRaMM, for correlation analysis between metabolome and microbiome data was also provided. IP4M provides both a number of parameters for customized and refined analysis (for expert users), as well as 4 simplified workflows with few key parameters (for beginners who are unfamiliar with computational metabolomics). The performance of IP4M was evaluated and compared with existing computational platforms using 2 data sets derived from standards mixture and 2 data sets derived from serum samples, from GC–MS and LC–MS respectively. IP4M is powerful, modularized, customizable and easy-to-use. It is a good choice for metabolomics data processing and analysis. Free versions for Windows, MAC OS, and Linux systems are provided.

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IP4M：用于基于质谱的代谢组学数据挖掘的集成平台

代谢组学数据分析依赖于生物信息学工具的使用。已经开发了许多集成的多功能工具用于非目标代谢组学数据处理，并已得到广泛使用。预计基本用户和高级用户都将拥有更多替代平台。设计并开发了基于集成质谱的非靶向代谢组学数据挖掘（IP4M）软件。IP4M具有62个功能，分为8个模块，涵盖了代谢组学数据挖掘的所有步骤，包括原始数据预处理（比对，峰反卷积，峰选择和同位素过滤），峰注释，峰表预处理，基本统计描述，分类和生物标志物检测，相关性分析，聚类和子聚类分析，回归分析，ROC分析，途径和富集分析，以及样本量和功效分析。此外，嵌入了KEGG衍生的代谢反应数据库，可以生成一系列比率变量（产物/底物），并提供有关酶活性的更多信息。还提供了一种新的方法GRaMM，用于代谢组和微生物组数据之间的相关性分析。IP4M提供了许多用于自定义和精细分析的参数（适用于专家用户），以及4个简化的工作流程，这些工作流程具有很少的关键参数（适用于不熟悉计算代谢组学的初学者）。分别使用GC-MS和LC-MS，使用标准混合物的2个数据集和血清样品的2个数据集对IP4M的性能进行了评估，并与现有的计算平台进行了比较。IP4M功能强大，模块化，可自定义且易于使用。它是代谢组学数据处理和分析的不错选择。提供了Windows，MAC OS和Linux系统的免费版本。