The chromatogram visualized by selecting one sample in the “Sample” tab of the “Data Analysis”page is the sum of the reconstructed chromatographic peaks of all the chemical features detected in the selected sample.

In the data-matrix the cells filled by the gap-filler algorithm are highlighted by light-blue color for positive acquired data and light-red color for negative acquisition. Chemical features with signal above the threshold for processing are instead shown in blue for positive acquired data and red color for negative acquisition.

P values are shown at the end of the process in the table containing the results.

The user can connect the identification results to metabolic pathways and compare metabolites that increase, or decrease based on label comparison. For that you can refer to Tutorial number 6.4.

P-values are Anova p-values. Corr p-values are “adjusted or corrected” p-values based on Benjamini-Hochberg procedure

High means number of identifications with high confidence. P-high (abbreviation of promoted-high) means number of identifications promoted high. The p-high identifications are those found by MARS during the second run of the identification. In this second run, MARS searches for the other adducts included by the user in the identification method ([M+H]+ and [M-H]- are investigated during the first run of the identification) and for in-source fragmentations. More details are reported in MARS publication. (DOI: 10.1021/acs.analchem.3c03620).

Both 4 and 3 stars of confidence are considered high. Therefore, to have a high confidence identification the overall score associated with it should be greater than 60.

The “Save” icon that appears at the end of the MS/MS validator running allows updating the theoretical fragment ions collected in the DB connected to the MARS session for that given compound. The fragment ions that will be saved on the database are only those found by the MS/MS validator. The fragment ions previously collected, will be overwritten.

To generate a library from in-house acquired data, related information must be imported using a .csv file into the DB Manager. The .csv contains different information on the compound/s to be imported (i.e., Id, Common Name, Formula, Classification, RT, Adducts – positive and negative ionization adducts are allowed, SMILES, and the name of the instrument data files from which to import the MS and MS/MS information for each specified compound).

The merged MSMS functionality in the identification method allows to carry out the identification process using as reference for the spectral matching approach the merged spectrum of those included in the database for each single compound. Therefore, it is normal to have only one matched spectrum.

MARS allows the generation of databases for identification purposes by importing the experimental MSMS spectra collected in the HMDB or MoNa repository. Generally, the information of instruments used to acquire the experimental spectrum is reported. Therefore, in MARS the user can perform the identification using different options:

• Use each spectrum included in the database to perform the identification (experimental MSMS vs all the MSMS spectra in the database).
• Use only the MSMS spectra in the database acquired with a user-defined collision energy to perform the identification.
• Use only the MSMS spectra in the database acquired with a specific instrument type that the user can specify in the identification method to perform the identification.
• Use the merged database described above to perform the identification.

The user can filter non-identified data by clicking on the “operation” icon (gear icon) in the “Result” tab of the “Identification” page and then on “Filter results”. In the new window, the user needs to select “Compound Class Filter” and then “Not Identified” in the drop-down menu.

To read Thermo Raw files, the MSFileReader has to be installed in your work station. You can find the software prerequisites for each mass spec instrument data in “Software Prerequisites” of the manual.

Yes, the software generates a log file in txt format. The file is saved in the App Data Folder. To visualize the correct path where the Log is located, you can click on “Help”->”About”,  one of the options in the GUI.

Yes, you can click on “Settings” in the header of the GUI and then on “Preferences”. In the “Visualization” option you can enter the “number of processor to not use” in the dedicated line.

The “MS signal filtering threshold” in the “Instrument” tab is a threshold applied during the import of the instrument data files. MS signals below the threshold are discarded and not included in the session. To rescue MS signal below this threshold, you should import the instrument data from scratch.

Instead, the “Signal filtering threshold” in the “Peak Detection” tab allows discarding MS signal below the specified threshold during the Peak detection step. These signals are discarded for data matrix generation, but they still be saved in the session. So, to rescue signals below the threshold (if needed), you can simply process the data in the session decreasing the threshold in the “Peak detection” tab.

The default settings are optimized for each instrument data based on internal analysis. In any case, deviations can occur. Therefore, the “Automatic” algorithm in the “MS Signal Filtering” is specifically design to inspects noise among the samples and automatically calculates a cut-off threshold to apply for data import. The signal threshold applied to each sample is reported in the “Info” column in the “Load Data” page. The algorithm eliminates noise but it is quite conservative in order to keep signals of low abundant species in the session that may be relevant for the case study. Then, if the user is not interested in this low intensity signals, he/she can process the data with a higher “Signal filtering  threshold” in the “Peak Detection” parameters. We suggest to enter a Signal filtering  threshold  = 2x (MS signal filtering threshold_(Automatic)).

To preserve all MS/MS signals in the software session, you need to set the “Sample MS/MS Signal Filtering Threshold” = 0 in the “Instrument” parameters of the LC-MS settings. In addition, if you are working with DIA acquisition, you should also disable the “MS/MS filtering” option in the “Peak Detection” parameters of the LC-MS settings.

The user has different options to smooth the peaks:

1. None: no smoothing is applied.
2. SDA: the user can choose between LOW, MEDIUM, and HIGH level. The higher the level, the smoother the peak.
3. Savitzky-Golay:
   • Window size: enter the number of scans between the two half-height of peaks. In general, the larger the window size, the more algorithm smooths the peaks.
   • Degree: degree of the polynomial to use to smooth the peak
   • Multi-pass iterations: number of iterations that the algorithm has to apply for smoothing the peaks.

This algorithm performs the Rt correction selecting as reference the chromatogram with highest peak area sum among the entire dataset and adjusting the Rt of each peak in the different samples based on the one of reference. When different labels with the option “Is batch” are assigned to different sample groups, this algorithm allows correcting the Rt of samples belonging to the same batch or different batches independently (when no labels are applied to samples or when the parameter “Is batch” is not selected in the labels, the software considers all the samples in the dataset belonging to the same batch).

• Within batch Rt tolerance: maximum Rt correction for samples of a same batch.
• Between batch Rt tolerance: maximum Rt correction for samples of a same batch.
• Rt window: Rt peak extraction window. Extraction window to detect the same peak into the different samples based on the one of reference.

Yes, the user can use the “chromatogram correlation based Rt correction” to correct the RT of chemical features in different sample batches.

The “sample alignment” algorithm aims to align same chemical features, generating a single column in the Data Matrix for each chemical feature detected within the dataset. The parameters to set are the following:

• m/z tolerance: m/z tolerance to align different chemical features.
• Rt tolerance: maximum retention time tolerance to use to align chemical features within the set m/z
• Dt tolerance: maximum drift time tolerance to use to align chemical features within the set m/z

The software supports the import of the mzML files for Waters instrument settings. Select “Waters Q-TOF (raw file)” in the “Instrument” tab of the LC-MS settings to import mzML file converted from Waters raw file.

Types of data that can be handled are MSe, HMSe, DDA, and centroid.

There is a specific functionality to perform a manual peak reintegration. In the “Data Matrix”, you need to select the peaks you want to reintegrate and click on the button. The EICs of selected peaks appear in a new window. Here, you can use the  button to manually reintegrate the peaks by selecting in the plot the range for integration. Compound areas will be also updated in the “Data Matrix”.

The best approach is to assign a label to different DBs and merge them together into a single one using the specific option “merge compounds DBs” under “Tools” in the DB Manager. Then, the user can connect the merged DB in the software and use it for the ID. In addition, the user can decide whether to carry out the identification with the merged DB or with the “starting DB” by selecting the label assigned to each of them.