Lipostar2

We use circles in the lipid pathways to display “small molecule nodes”. The pink color means that the node is common to other lipid pathways. A light-grey shadow surrounding a small molecule node means that that node is populated by lipid structures included into the database connected to the session. If you click on a node surrounded by a grey shadow, you can visualize the information of lipids populating that node in the upper tab of the pathways, while the information of the node is reported in the tab in the bottom. The number is the ID Node, it is just an identifier number for nodes.

The format of the report is a docx. The template file is simply a docx file you want to use to generate the report. For instance, you can use as a template a word file with specific settings, such as page headers etc

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

In the lipid pathways the user can open the disease map, where lipids increasing or decreasing in a pathological status are visualized with different colors (e.g., in red species that increase while in blue the decreasing ones). In addition, you can connect your identification to lipid pathways and compare lipids that increase, or decrease based on label comparison.

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

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.