MetaboLink

Median Across Samples

Median Across QCs

Class Plot

Select which column plot to display:

Violin Plot

Median Across Groups

Select group

Principal Component Analysis

Check log-transfomed checkbox if data is already log-transformed.

PCA 1

Data is log-transformed.

Scree plot 1

PCA 2

Data is log-transformed.

Scree plot 2

Select dataset to compare with

Select Feature

Settings

Title

Log

None ln log2 log10

Y axis log

None log2 log10

K-means Analysis Information

Evaluate cluster validity using methods silhouette, WSS, or gap statistic.
Optionally, restrict clustering to selected groups for enhanced analysis.
Results are visualized with plots and an outlier table displaying potential anomalies.

Data & Evaluation Selection

Choose PCA Results:

Select Specific Groups

Choose Evaluation Method:

K-means Parameters

Number of Clusters (k):

Percentile Threshold:

K-means Results

Hierarchical Clustering Analysis Information

Hierarchical clustering builds a dendrogram based on the distance between samples.
Users can specify the clustering method, number of clusters, and dendrogram threshold.
It supports group selection to focus on subsets of the data.
Dendrogram and cluster plots along with outlier tables help identify unusual samples.

Data Selection

Choose PCA Results:

Select Specific Groups

Clustering Parameters

Select Clustering Method:

Number of Clusters (k):

Dendrogram Threshold (Distance):

Hierarchical Results

DBSCAN Analysis Information

DBSCAN is a density-based algorithm that groups samples based on local point density.
Requires setting epsilon(eps) and minimum points (minPts) parameters to define cluster boundaries.
Filters out samples with low density as potential outliers.

Data Selection

Choose PCA Results:

Select Specific Groups

Choose k for kNN Distance Plot:

DBSCAN Parameters

Choose epsilon for DBSCAN:

Choose minPts for DBSCAN:

DBSCAN Results

HDBSCAN Analysis Information

HDBSCAN extends DBSCAN by converting it into a hierarchical clustering approach.
Uses a minimum points parameter and an outlier threshold to classify data points.
Allows selection of groups to refine the clustering process.
Plots and outlier tables provide a detailed view of anomalous samples.

Data Selection

Choose PCA Results:

Select Specific Groups

HDBSCAN Parameters

Choose minPts for HDBSCAN:

Outlier Threshold for HDBSCAN:

HDBSCAN Results

OPTICS Analysis Information

OPTICS orders samples based on reachability distances to reveal cluster structure.
Generates reachability and threshold plots for visualizing cluster boundaries.
Parameters such as eps, minPts, and eps cl can be adjusted to fine-tune analysis.
The results help identify outliers and are displayed through multiple visualizations.

Data Selection

Choose PCA Results:

Select Specific Groups

OPTICS Parameters

Choose minPts for OPTICS:

Choose eps for OPTICS (optional):

Choose cutoff (eps_cl) for OPTICS:

OPTICS Results

LOF Analysis Information

LOF measures the local density deviation of a sample relative to its neighbors.
Uses a threshold and a k parameter to compute an outlier score for each sample.
Highlights samples with significantly lower local density as outliers.
Interactive LOF plots and a summary table help in interpreting and identifying anomalies.

Data Selection

Choose PCA Results:

Select Specific Groups

LOF Parameters

Threshold for LOF:

k for LOF:

LOF Results

Over-Representation Analysis (ORA)

Pathway Enrichment Information

Pathway enrichment analysis identifies over-represented biological pathways in your data.
Set appropriate thresholds and select the correct groups to reveal significant pathways.

Data & Identifier Selection

Select Dataset for Identifier Gathering

Select InChI Column

Select Compound Column

Pathway Enrichment

Module Enrichment

Group of Interest

Reference Group

Enrichment Settings

Number of Top Features:

Adjusted P-value Threshold:

P-Adjust Method:

Color based on Method:

min GS Size Threshold:

max GS Size Threshold:

Q-value Threshold:

Network Graph Customizations

Choose Layout:

Node Size Multiplier:

Node Text Size:

Edge Transparency:

Edge Width Scale:

Color Nodes By:

Instructions

Upload Sequence File

Add RefMet Information

Clean Lipid Names

Remove Unannotated Features

Edit Data Columns

Group Nicknames

Download Sequence File

Median Across Samples

Median Across QCs

Class Plot

Select which column plot to display:

Violin Plot

Median Across Groups

Principal Component Analysis

PCA 1

Scree plot 1

PCA 2

Scree plot 2

Select Feature

Settings

K-means Analysis Information

Data & Evaluation Selection

K-means Parameters

K-means Results

Hierarchical Clustering Analysis Information

Data Selection

Clustering Parameters

Hierarchical Results

DBSCAN Analysis Information

Data Selection

DBSCAN Parameters

DBSCAN Results

HDBSCAN Analysis Information

Data Selection

HDBSCAN Parameters

HDBSCAN Results

OPTICS Analysis Information

Data Selection

OPTICS Parameters

OPTICS Results

LOF Analysis Information

Data Selection

LOF Parameters

LOF Results

Heatmap Analysis

Heatmap Controls

Heatmap Customizations

Heatmap Plot

Heatmap Results

Circular Barplot Information

Circular Barplot Settings

Circular Barplot

User guide

Data Frame and group selection:

Group of Interest Table

Reference Group Table

Plot Settings

Settings

Volcano Plot Information

Data & Group Selection

Volcano Plot Customization

Individual Feature Selection

Group Selection

Volcano Plot & Results

Odds Ratio plot Information

Data & Group Selection

OR Plot

OR Results Table

Pathway Enrichment Information

Data & Identifier Selection

Enrichment Settings

Network Graph Customizations

Data summary

Enrichment Barplot and Dotplot

Enrichment Network Graph

Enrichment Table

Guide

Local test

Export to PolySTest