Report for Standardized Analysis

E Errors and/or missing values detected in input data

E.1 Duplicate values in Metabolite Name Key

E.2 Unknown pathways in Metabolite Name Key

The following pathway names were found in the Metabolite Name Key but are not defined in the pathways database:

E.3 Unknown metabolites in data

The following metabolite names were found in the data but are not defined in the Metabolite Name Key:

E.4 Unknown metabolites in Pathway Diagrams

E.5 Metabolites not shown in any Pathway Diagram

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MD Anderson Cancer Center Metabolomics Core, Houston, TX February 04, 2026

Report Information
Study Number	Weinstein_01152026_19475
PI	John Weinstein
Institution	MD Anderson Cancer Center
Assay Type	Standardized
Samples	cell
NGCHM Viewer Version	2.26.0
NGCHM R Version	1.0.4
MBatch Version	1.7.6
Template Version	v2.0.0

1 Experimental Details

1.1 Multi-Omic Profiling (general)

Method details are available upon request. This is a general report format typically used for custom assays.

2 Sample Table

The sample table contains metadata for the samples in the cohort. ID represents the sample name, and other column headers indicate additional metadata (e.g., time point, treatment group).

3 Normalization

No Normalization: The peak area (raw relative abundance) of each metabolite is presented directly without normalization.

3.1 Data Table

The data table provides normalized metabolite relative abundance. The tables are interactive and each column can be sorted in ascending or descending order. Users can search for a specific metabolite using the search bar and copy or download the data in CSV or Excel format.

3.2 Normalized Data Distribution

Click the button below to show/hide the data distribution plots.

Show/Hide Data distribution

3.2.1 With Respect to Samples

3.2.1.1 Linear scale

3.2.1.2 Log10 scale

4 Data Analysis

4.1 Data Clustering

4.1.1 Group Clustering: PCA-Plus

This plot presents Principal component analysis (PCA), with PC1 on the x-axis and PC2 on the y-axis, as is customary. Additionally, the median values are calculated and plotted for each group. The plot is interactive.

Dispersion Separability Criterion (DSC): DSC metric has been designed to quantify the dissimilarity between groups within the data, and can also be used to quantify batch effects. DSC is a ratio of dispersion across batches (Db) vs. dispersion within batches (Dw). A DSC value greater than one means that there is greater dispersion, or dissimilarity, across batches than within batches, whereas a DSC of zero means there is no dissimilarity across batches. Typically, values greater than 0.3 indicate the presence of moderate batch effects, whereas a value greater than 0.6 indicate severe batch effects.

DSC p-value: The p-value is derived empirically, using permutation tests. One thousand or more permutations are typically run on each data set, using different random permutations of the data each time. DSC values are computed for each permutation and at the end of all the runs, the proportion of values greater than the actual DSC value is computed to yield the p-value. The null hypothesis is that there are no batch effects and the data set is homogeneous in terms of batches. A p-value less than some significance threshold (usually 0.05) rejects the null hypothesis.

Plots created with MBatch from the Batch Effects Package

Please see https://pubmed.ncbi.nlm.nih.gov/38260566/.

4.1.2 MS1 Abundance Clustering: Next-Generation Clustered Heatmap (NG-CHM)

4.1.2.1 Hierarchical clustering

Next-generation clustered heatmap (NG-CHM) software was used to process the data. NG-CHM plots are interactive and can be used for zooming, panning, searching, covariate bars, and link-outs that enable deep exploration of patterns and associations in heat maps. Note: if you do not have a wheel mouse, you can use two-finger swiping upward/downward on a touchpad to zoom.

The NG-CHM Heat Map Viewer contains two panels. The Summary Panel on the left provides a full view of your heat map. The Detail Panel on the right provides a zoomed-in view of a portion of the heat map. Click anywhere on the summary picture to see the detail of that portion of the map. The green box on the Summary Panel indicates the portion of the heat map currently displayed in the Detail Panel. You may zoom in or out with the mouse scroll wheel or zoom in/out buttons to see smaller or larger portions of the map in the Detail View. Double-clicking on a cell in the Detail Panel will also zoom in and center on that cell and shift-double click will zoom out. When the zoom level permits, row and column labels will be displayed in the Detail Panel. You may also use arrow keys to move up/down/left/right one row in the Detail Panel. The divider bar may be moved by clicking on it and dragging left or right to change the relative size of the Summary and Detail Panels. There are a variety of buttons on the header bar as well to manipulate the heat map view.

NG-CHMs created with the NG-CHM R package.

Please see https://pubmed.ncbi.nlm.nih.gov/32269754/.

Bidirectional Median Centering

A bidirectional median centered, or simply median centered, data matrix is where the column medians are subtracted from each column, then the row medians are subtracted from each row. Such normalization is performed to make patterns in the data matrix stand out in a heatmap. Without such normalization, one would typically observe some rows or columns that are saturated entirely by one color (red or blue) making patterns difficult to observe. However, a side-effect of visualizing median centered data is that because the data are altered, they may not directly correspond with patterns in other plots (like box plots) derived from non-median centered data. To circumvent that, we have included the option of visualizing non-median centered data in the NG-CHM as well by toggling to another layer using the “layer” button () in the upper right corner of the NG-CHM below.

Choose a clustering method: Hierarchical Clustering

Supervised Clustering by Group

4.1.2.2 Hierarchical Clustering

4.1.2.3 Supervised Clustering by Group

4.2 Fold Change

Fold change allows the user to comprehensively identify significantly modulated metabolites based on biological significance. The table is highly dynamic. You can use the dropdown buttons to choose the covariate, groups to compare, and additional comparison parameters in the ‘limit comparison’ dropdown. The data can also be downloaded from the table.

Covariate:
Select groups to compare:

Limit comparision in:

The log₂ fold change is the log₂ of the ratio between the average values across samples of two conditions. Click on the table header to sort the data.
Click on a table row to zoom to the corresponding compound in the waterfall plot.

5 Plots of Individual Compounds

To display the plot for a compound, click that compound’s name in the list below. This list is scrollable, and the search box can be used to refine the list of compounds shown. You can select multiple compounds using shift- or command-click to display multiple plots at once.

Generating PowerPoint file of individual compound plots.

6 Pathways

Version: 2.0.0 Hide pathway table Show table editor Hide table editor

Column name:

Method:

Covariate:

Group 1: Group 2:

Name:

Remove Reset Apply

To display a pathway, click that pathway’s entry in the table below. Click on a column heading to sort entries by that column. Click on the column heading again to toggle the sort direction. If you enter a search term in the search box, only matching pathways will be included in the table. The table is paginated. You can move between pages using the controls at the lower right. You can also change the page size (number of pathways included per page).

Show pathway table Selected pathway:

Save as SVG

Sample order: Show: ReplicatesCategories Color scaling:

Low color: High color:

Compound:

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