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Explanation on each parameter of MS-Dial 5.html

@@ -212,8 +212,12 @@ <h2 class="anchored" data-anchor-id="importance-of-ms-dial-5">2.0 Importance of
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 <section id="the-differences-between-ms-dial-4-and-ms-dial-5" class="level2">
 <h2 class="anchored" data-anchor-id="the-differences-between-ms-dial-4-and-ms-dial-5">3.0 The differences between MS-DIAL 4 and MS-DIAL 5:</h2>
-<p><strong>Graphical User Interface (GUI):</strong> MS-Dial 4: Functional but slightly less refined. MS-Dial 5: Improved GUI with more intuitive workflows and better user experience.</p>
-<p><strong>Speed and Performance:</strong> MS-Dial 4: Effective but slower on larger datasets. MS-Dial 5: Optimized for faster data processing, especially for large, multi-omics datasets.</p>
+<p><strong>Graphical User Interface (GUI):</strong></p>
+<p>MS-Dial 4: Functional but slightly less refined.</p>
+<p>MS-Dial 5: Improved GUI with more intuitive workflows and better user experience.</p>
+<p><strong>Speed and Performance:</strong></p>
+<p>MS-Dial 4: Effective but slower on larger datasets.</p>
+<p>MS-Dial 5: Optimized for faster data processing, especially for large, multi-omics datasets.</p>
 <p><strong>Annotation Capabilities:</strong></p>
 <p>MS-DIAL 4: Limited to using one database and annotation level in a single analysis. Provides comprehensive annotation of metabolites and lipids through spectral matching using established databases.</p>
 <p>MS-DIAL 5: Enables the use of multiple databases and annotation levels within the same analysis. Significantly improves annotation accuracy by incorporating ion mobility spectrometry (IMS) data and enhanced spectral deconvolution. MS-DIAL 5 also has better integration with larger and more updated databases, improving the annotation of complex molecules like lipids, metabolites, and isomers.</p>
@@ -275,7 +279,8 @@ <h2 class="anchored" data-anchor-id="step-by-step-guide-on-how-to-set-up-a-proje
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-<p>After assigning identifiers to the raw measurement files, click Next to proceed to the Measurement Parameters tab. In this section, you will input the analytical and instrumental parameters that were used during data acquisition. These settings are crucial for ensuring accurate data processing and should align exactly with the experimental conditions under which the measurements were taken (Figure 4). The following sections will offer detailed instructions on how to select and configure each parameter within the Measurement Parameters section</p>
+<p>After assigning identifiers to the raw measurement files, click Next to proceed to the Measurement Parameters tab. In this section, you will input the analytical and instrumental parameters that were used during data acquisition. These settings are crucial for ensuring accurate data processing and should align exactly with the experimental conditions under which the measurements were taken (Figure 4).</p>
+<p>The following sections will offer detailed instructions on how to select and configure each parameter within the Measurement Parameters section</p>
 <p><strong>4.1 Measurement Parameters Section:</strong></p>
 <p><strong>1. Ionization type:</strong> Select the soft ionization type, when you are analyzing the ESI data or select hard ionization type when you are analyzing the EI data.</p>
 <p><strong>2. Separation type:</strong> Select chromatography (for LC, GC, CE, or SFC) or direct infusion method as per your analysis. Additionally, you can check ion mobility box coupled with one of the previous options.</p>
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-<p>After configuring each parameter in the Measurement Parameters section, click “Next” to proceed to the Data Collection tab. In this section, you will need to enter the data collection parameters that were used during the acquisition of your samples. These parameters are essential for accurately processing and analyzing your data according to the conditions of your experiment (Figure 5). The upcoming sections will provide detailed instructions on how to set each parameter in the Data Collection section.</p>
+<p>After configuring each parameter in the Measurement Parameters section, click “Next” to proceed to the Data Collection tab. In this section, you will need to enter the data collection parameters that were used during the acquisition of your samples. These parameters are essential for accurately processing and analyzing your data according to the conditions of your experiment (Figure 5).</p>
+<p>The upcoming sections will provide detailed instructions on how to set each parameter in the Data Collection section.</p>
 <p><strong>4.2 Data collection parameters:</strong></p>
 <p><strong>Mass accuracy (Centroid parameter):</strong> After the initial peak detection in MS-DIAL, mass tolerance defines the acceptable range of mass deviation for both MS1 and MS/MS data. By default, mass tolerance values are set to ±0.01 Da for MS1 and ±0.025 Da for MS/MS. This means that peaks within these ranges around the detected mass are integrated and considered for further analysis. Importantly, the MS/MS tolerance also influences how MS/MS chromatograms are constructed, affecting how closely the detected fragment ions need to match the theoretical masses to be included in the MS2Dec deconvolution process.</p>
 <p><strong>Data collection parameters:</strong> In MS-DIAL, you can define the analysis ranges as per your analysis for retention time (RT), MS1, and MS/MS axis to focus on specific parts of your data. For this demonstration, we have chosen the expected data range as follows: In this demo data RT range is 0 - 100 min, and the MS and MS/MS range is 0 – 2000 Da.</p>
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-<p>Click Next to proceed to the Peak Detection Parameter Settings. In this section, you’ll need to enter the parameters used for peak detection in your mass spectrometry data. This includes specifying values such as the minimum peak height, mass peak width, and exclusion mass list (Figure 6). The following sections will offer detailed guidance on how to configure each parameter within the Peak Detection section</p>
+<p>Click Next to proceed to the Peak Detection Parameter Settings. In this section, you’ll need to enter the parameters used for peak detection in your mass spectrometry data. This includes specifying values such as the minimum peak height, mass peak width, and exclusion mass list (Figure 6).</p>
+<p>The following sections will offer detailed guidance on how to configure each parameter within the Peak Detection section</p>
 <p><strong>4.3 Peak detection parameter:</strong></p>
-<p>MS-DIAL provides two simple thresholds; minimum values for peak width and height. Peaks below these thresholds are ignored.</p>
 <p><strong>Minimum Peak Height:</strong> Set the minimum intensity level required for a peak to be detected in your data. Peaks with heights below this threshold will be ignored, which helps in filtering out noise and focusing only on significant signals for accurate analysis. Ideally, users put values here based on their own experience that you are looking at the trend of your data. However, based on our experience, the minimum peak height may be set to 1000 as a default value for this demo data. Besides, for FT-MS or Orbitrap data, the minimum peak height maybe 10,000 or more.</p>
 <p>Refer to the tutorial on how to determine the minimum peak height for your analysis using the Rawdataviewer tool in the link below.</p>
 <p><a href="https://systemsomicslab.github.io/msdial5tutorial/Determine%20the%20optimal%20minimum%20peak%20height.html">https://systemsomicslab.github.io/msdial5tutorial/Determine%20the%20optimal%20minimum%20peak%20height.html</a></p>
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-<p>Click Next to proceed to the Spectrum Deconvolution Parameter Settings. In this section, you will configure the parameters for deconvoluting your mass spectrometry data. Key settings include the sigma window value, the MS/MS abundance cut-off value, and the option to exclude peaks following the precursor ion (Figure 7). The following sections will provide detailed instructions on how to set each parameter within the Spectrum Deconvolution section.</p>
+<p>Click Next to proceed to the Spectrum Deconvolution Parameter Settings. In this section, you will configure the parameters for deconvoluting your mass spectrometry data. Key settings include the sigma window value, the MS/MS abundance cut-off value, and the option to exclude peaks following the precursor ion (Figure 7).</p>
+<p>The following sections will provide detailed instructions on how to set each parameter within the Spectrum Deconvolution section.</p>
 <p><strong>4.4 Spectrum deconvolution parameter:</strong></p>
 <p><strong>Sigma window value:</strong> The sigma window value is highly affected by the resolution of deconvolutions. A higher value (0.7-1.0) will reduce the peak top resolutions, i.e.&nbsp;the number of resolved peaks will be decreased. On the other hand, a lower value (0.1-0.3) may also recognize many noise chromatographic peaks. In our demo data, we have chosen 0.5.</p>
 <p><strong>MS/MS Abundance Cut-off:</strong> MS/MS Abundance Cut-off refers to the minimum intensity level of the MS/MS (tandem mass spectrometry) signals that must be reached for a fragment ion to be considered significant and included in the analysis. Unless you have data-independent MS/MS data sets, you can skip this part. However, you may set a cutoff value to reduce the MS peak noise levels.</p>
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-<p>Click Next to proceed to the Identification Parameter Settings. In this section, you will configure parameters related to the identification of compounds, including the database type, lipid profiling settings, annotation options, and retention time settings (Figure 8). The following sections will provide detailed instructions on how to set each parameter within the Identification section.</p>
+<p>Click Next to proceed to the Identification Parameter Settings. In this section, you will configure parameters related to the identification of compounds, including the database type, lipid profiling settings, annotation options, and retention time settings (Figure 8).</p>
+<p>The following sections will provide detailed instructions on how to set each parameter within the Identification section.</p>
 <p><strong>4.5 Identification parameter:</strong></p>
 <p><strong>MSP file:</strong> In the case that you selected the ‘lipidomics’ project, select what you want to annotate in your data sets for lipid profiling. For example, we selected all the lipids to analyze in our data. For this tutorial data, in which ammonium acetate was used as a solvent type, select HCOONH4 (ammonium formate) as the solvent type in the window ’Lipid database setting, although nowadays CH3COONH4 (ammonium acetate) is basically used as a solvent type.</p>
 <p>If you are selected as a metabolomics project, insert the MSP file. Several MSP files are downloadable as a starter kit for MS-DIAL using below link</p>
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-<p>Click on Next to proceed to the Adduct Ion Parameter Settings. In this section, you will need to select the adduct ions relevant to your analysis. The following sections will provide detailed instructions on how to choose and configure adduct ions for your analysis (Figure 9).</p>
+<p>Click on Next to proceed to the Adduct Ion Parameter Settings. In this section, you will need to select the adduct ions relevant to your analysis.</p>
+<p>The following sections will provide detailed instructions on how to choose and configure adduct ions for your analysis (Figure 9).</p>
 <p><strong>4.6 Adduct ion parameters:</strong></p>
 <p><strong>Adduct ion setting:</strong> You can tick the adduct ions and charge values which is suitable for your analysis.</p>
 <p><strong>Adduct ion format:</strong> Adduct ion information should be formatted as described in this section: [M+Na]+, [M+2H]2+, [M-2H2O+H]+, [2M+FA-H]-, etc.</p>
@@ -386,13 +395,7 @@ <h2 class="anchored" data-anchor-id="step-by-step-guide-on-how-to-set-up-a-proje
 <p>The beginning figure of organic formula like ’2’H2O is recognized as the H2O × 2. Again, do not use 2(H2O) to specify this.</p>
 <p>Sequential equations are acceptable: [2M+H-C6H12O5+Na]2+.</p>
 <p>MS-DIAL accepts some abbreviations or common organic formulas for adduct types as follows.</p>
-<p>For Acetonitrile: ACN, CH3CN</p>
-<p>For Methanol: CH3OH</p>
-<p>For Isopropanol: IsoProp, C3H7OH</p>
-<p>For Dimethyl sulfoxide: DMSO</p>
-<p>For Formic acid: FA, HCOOH</p>
-<p>For Acetic acid: Hac, CH3COOH</p>
-<p>For Trifluoroacetic acid: TFA, CFCOOH</p>
+<p>For Acetonitrile: ACN, CH3CN For Methanol: CH3OH For Isopropanol: IsoProp, C3H7OH For Dimethyl sulfoxide: DMSO For Formic acid: FA, HCOOH For Acetic acid: Hac, CH3COOH For Trifluoroacetic acid: TFA, CFCOOH</p>
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-<p>Click Next to proceed to the Alignment Parameter Settings. In this section, you’ll need to configure various parameters including the reference file, RT tolerance, RT factor, features based on blank information, and peak count filter for adduct ions (Figure 10). The following sections will provide detailed instructions on how to set each of these parameters for optimal alignment of your data.</p>
+<p>Click Next to proceed to the Alignment Parameter Settings. In this section, you’ll need to configure various parameters including the reference file, RT tolerance, RT factor, features based on blank information, and peak count filter for adduct ions (Figure 10).</p>
+<p>The following sections will provide detailed instructions on how to set each of these parameters for optimal alignment of your data.</p>
 <p><strong>4.7 Alignment parameters:</strong></p>
 <p><strong>Result name:</strong> The name will be the name of each alignment shown at the tab of ‘Alignment navigator’ in the main window.</p>
 <p><strong>Reference file:</strong> If you already have suitable quality control (QC) data, typically mixed sample data, then specify the QC file in the reference file. All sample data will be aligned to this QC file.</p>
 <p><strong>RT and MS1 tolerances:</strong> The RT and MS1 of the peak will be compared with the library RT and MS spectra. Typically, give the default setting values.</p>
 <p><strong>Retention time factor and MS1 factor:</strong> These values indicate the importance of either RT or MS1 to compare and evaluate the similarity of the spectra among samples based on RT and MS1 tolerance.</p>
-<p>Equation to calculate the RT factor: =exp(-0.5*(sample1(RT)-sample2(RT))/RT tolerance)^2)</p>
-<p>Equation to calculate the m/z factor: =exp(-0.5*(sample1(m/z)-sample2(m/z))/m/z tolerance)^2)</p>
+<p>Equation to calculate the RT factor: =exp(-0.5<em>(sample1(RT)-sample2(RT))/RT tolerance)^2) Equation to calculate the m/z factor: =exp(-0.5</em>(sample1(m/z)-sample2(m/z))/m/z tolerance)^2)</p>
 <p><strong>Peak count filter:</strong> If you want to remove specific peaks that are not fully detected in the alignment, specify the peak count filter.</p>
 <p>For example, if you have 3 biological replicates with the same peak information and the total number of data is 24. Then, you may set the peak count filter as (3/24)∗100. This means peaks will be removed when they include missing values for more than the entered peak count filter (%). In the tutorial data we have only 3 samples.</p>
 <p><strong>N% detected in at least one group:</strong> The filtering is done within each sample group. If it is set to 100%, the peaks should be detected in all of the samples of a class.</p>
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-<p>Click Next to proceed to the Isotope Tracking Settings. In this section, you will configure the settings to enable isotope tracking in your data (Figure 11). The following sections will provide detailed instructions on how to set up the isotope tracking parameters for your analysis.</p>
+<p>Click Next to proceed to the Isotope Tracking Settings. In this section, you will configure the settings to enable isotope tracking in your data (Figure 11).</p>
+<p>The following sections will provide detailed instructions on how to set up the isotope tracking parameters for your analysis.</p>
 <p><strong>4.8 Isotope tracking parameter:</strong></p>
 <p><strong>Tracking of isotope labels:</strong> If you check this box, it will identify and monitor the isotopically labeled lipids or metabolites in your sample. This is especially useful in lipidomics or metabolomics experiments where stable isotopes like 13C or 2H are incorporated into lipids or metabolites in your study.</p>
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 <p>Then you can click Run for the processing of your MS data in MS-Dial 5 and click Save to save the project.</p>
-<p>Once you finished the data processing like peak picking, peak identification, and peak annotation. You can click the export icon to export the results in different forms (Figure 12). The following sections will provide detailed instructions on how to export your results.</p>
+<p>Once you finished the data processing like peak picking, peak identification, and peak annotation. You can click the export icon to export the results in different forms (Figure 12).</p>
+<p>The following sections will provide detailed instructions on how to export your results.</p>
 <p><strong>4.9 Export:</strong> Here, in this case, we are using the alignment results export option to get all the spectral information of lipids.</p>
 <p>The following options are used to export the results:</p>
 <p><strong>Peak list export:</strong> You can get the peak list information of each sample including retention time, m/z, MS/MS spectra information, and so on. Available formats are MSP, MGF, or Text.</p>