Converting raw data from GC-MS instrument to a peak table that can be handled using statistical and data analysis methods is a key point in the chemical forensics data analysis process.<br/>A methodological study was done to assess the behavior of data pretreatment tools commonly used in the metabolomics field.<br/>Firstly, a ROP standard solution (Quality Control mixture from OPCW blue book) was analyzed at its original concentration level (10 µg/mL) and at two dilution levels (1 & 0.1 µg/mL) on a GC-MS system equipped with a 5ms type chromatographic column. Raw data pretreatment was done using MZmine [1]. After optimization of its main parameters, almost all peaks of interest were detected even at the lowest concentration level (0.1 µg/mL ).<br/>Then a data set composed of standard solutions and complex samples analyzed by GC-MS in 5 different laboratories on SolGelWax column had been analyzed with MZmine and another commonly used pretreatment tool, XCMS [2]. As before, parameters were optimized and integration value compared with reference ones obtained by a targeted study of peaks of interest. The results showed that integration values from automated tools such as MZmine and XCMS were really close to the reference, even in complex matrices (~80% of peaks with relative error below 20% for both tool).

From raw data to peak table: a methodogical study for chemical forensics

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ACS Fall 2022

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