Choose Files for Analysis
PROJECT
DATA FOLDER
METADATA FILE
OPTIONS
FEATURE DETECTION OPTIONS
When reading the data, the peak detection will be performed.
Options for the feature (peak) detection in the chromatographic time domain
Commonly, 30 for LC-MS spectra and 4 for GC-MS spectra.
Commonly, 30 for LC-MS spectra and 5 for GC-MS spectra.
METADATA FILE OPTIONS
OPTIONAL INFORMATION:
DATA OPTIONS
When reading the data, the peak detection will not be performed. To do so, you will have to go to the pre-processing page.
Note that the formats supported are Processed BRUKER or Raw VARIAN. See the help page for more information on how the data folders should be formatted in each format.
Note that the formats supported are Processed BRUKER or Raw VARIAN. See the help page for more information on how the data folders should be formatted in each format.
Options for processing the fid spectra into an intensity vs ppm spectra:
METADATA OPTIONS
OPTIONAL INFORMATION:
DATA FILES OPTIONS
METADATA FILE OPTIONS
OPTIONAL INFORMATION:
Error:
ALIGNMENT OF PEAKS OPTIONS
There are two methods available to perform alignment of peaks. The specmine algorithm does not allow overlapping of windows, being the size of the window equal to the step. The MetaboAnalyst method allows overlapping of windows, being the step half the size of the window. The step size for the MetaboAnalyst method has a default of 0.015 for NMR peaks and 0.125 for GC/LC-MS peaks. The bandwidth, used in this method, has the values 10, 30 and 5 for NMR, LC/MS and GC/MS peaks, respectively.
DATA FILE OPTIONS
METADATA FILE OPTIONS
OPTIONAL INFORMATION:
DATA OPTIONS
METADATA OPTIONS
OPTIONAL INFORMATION:
Error:
New Project
DATA OPTIONS
Note that only the formats .mzXML, .netCDF, mzData are supported.
When reading the data, the peak detection will be performed.
Options for the feature (peak) detection in the chromatographic time domain:
Commonly, 30 for LC-MS spectra and 4 for GC-MS spectra.
Commonly, 30 for LC-MS spectra and 5 for GC-MS spectra.
METADATA OPTIONS
OPTIONAL INFORMATION:
DATA OPTIONS
Note that the formats supported are Processed BRUKER or Raw VARIAN.
See the help page for more information on how the data folders should be formatted in each format.
When reading the data, the peak detection will not be performed. To do so, you will have to go to the pre-processing page.
Options for processing the fid spectra into an intensity vs ppm spectra:
METADATA OPTIONS
OPTIONAL INFORMATION:
DATA OPTIONS
METADATA OPTIONS
OPTIONAL INFORMATION:
Error:
ALIGNMENT OF PEAKS OPTIONS
There are two methods available to perform alignment of
peaks. The specmine algorithm does not allow overlapping
of windows, being the size of the window equal to the step.
The MetaboAnalyst method allows overlapping of windows,
being the step half the size of the window. The step size
for the MetaboAnalyst method has a default of 0.015 for
NMR peaks and 0.125 for GC/LC-MS peaks. The bandwidth,
used in this method, has the values 10, 30 and 5 for NMR,
LC/MS and GC/MS peaks, respectively.
DATA OPTIONS
METADATA OPTIONS
OPTIONAL INFORMATION:
DATA OPTIONS
METADATA OPTIONS
OPTIONAL INFORMATION:
Error:
Submit the New Samples
Options for the feature (peak) detection in the chromatographic time domain
Commonly, 30 for LC-MS spectra and 4 for GC-MS spectra.
Commonly, 30 for LC-MS spectra and 5 for GC-MS spectra.
OPTIONAL INFORMATION:
Options for processing the fid spectra into an intensity vs ppm spectra:
OPTIONAL INFORMATION:
OPTIONAL INFORMATION:
OPTIONAL INFORMATION:
New samples submited must have the data variables used to predict the model chosen.
Options to align peaks after their detection: The specmine algorithm does not allow overlapping of windows, being the size of the window equal to the step.
The samples will be further pre-processed similarly as the dataset used for
model training.
Convert to factor, Remove data, Remove data by NAs, Low-level fusion, Flat pattern filters
and
Aggregate samples
are not available to process new samples.
Error:
Error:
Save Workspace Data
All the data and results regarding the current data folder from the current project can be saved on your account, so it can be uploaded at a different time and the analysis continued.
Current Project:
Current Data Folder from the project above:
Current Project:
Current Data Folder from the project above:
Error:
The workspace you want to save is from a public project you haven't yet copied to
your account. Copy the public project and then save the workspace.
Public project to copy to your account
The workspace you want to save cannot be saved because it is not
associated with a project from your account neither with a public project.
Load Workspace Data
There are no workspaces available.
Error:
WebSpecmine
Metabolomics and Spectral Data Analysis and Mining
WebSpecmine
Metabolomics and Spectral Data Analysis and Mining
WHAT'S NEW
June, 2018
- Some projects from the Metabolights database are now available to analyse.
May, 2018 - NMR spectra with BRUKER or VARIAN format is now supported. See help page for more information.
May, 2018 - Pathway analysis is now available.
October, 2017 - WebSpecmine, a tool for metabolomics and spectral data analysis and mining.
May, 2018 - NMR spectra with BRUKER or VARIAN format is now supported. See help page for more information.
May, 2018 - Pathway analysis is now available.
October, 2017 - WebSpecmine, a tool for metabolomics and spectral data analysis and mining.
My Projects
My Projects
Public Projects
Public Projects
Community projects
Project description:
You must select a project first.
View project files in:
Data Folders:
Files in Metadata folder:
Files in Reports folder:
Metabolights Projects
Metabolights Projects
List of Metabolights Studies Available
Click in a row to see more detailed information on the study selected.
Run Analysis
Run Analysis
To Start the analysis of your Metabolomic Data, choose one of the analysis boxes bellow.
Boxes in grey represent unavailable boxes.
(This occurs when the dataset data type is unsupported or the dataset has missing values (treat them on "Pre-Processing" tab)).
Univariate Analysis
- One-way and multifactor ANOVA
- Kruskal-Wallis and Komolgorov-Smirnov tests
- Fold Change analysis
Principal Component Analysis (PCA)
- Both classical and robust approaches available
Clustering Analysis
- Hierarchical Clustering
- K-Means Clustering
Machine Learning
- Predict new samples with the models trained previously or a model saved in user's account.
Feature Selection
- Recursive Feature Elimination.
- Selection by Filter
Metabolite Identification
- LC-MS technique
- NMR Peaks
Regression Analysis
- Regression analysis
- Correlation analysis
Pathway Analysis
- Metabolites identified through 'Metabolite Identification' box
- Concentrations data whose variables names are in HMDB OR KEGG codes
Run Analysis
Feature Selection
Run Analysis
Feature Selection
Error:
Analysis name already exists or it contains spaces, please write another one.
For Model validation:
Run Analysis
Metabolite Identification
Run Analysis
Metabolite Identification
The metabolite identification is performed using the MAIT package.
Peaks are first annotated, by using the default MAIT table for adducts in positive polarization.
Next, statistically significant features are detected, followed by the identification of biontransformations between features, as well as looking for adducts.
Finally, the metabolite identification for the significant features is performed, by using the Human Metabolome Database (HMDB), version 2009/07. The peak tolerance value is set to 0.005.
Peaks are first annotated, by using the default MAIT table for adducts in positive polarization.
Next, statistically significant features are detected, followed by the identification of biontransformations between features, as well as looking for adducts.
Finally, the metabolite identification for the significant features is performed, by using the Human Metabolome Database (HMDB), version 2009/07. The peak tolerance value is set to 0.005.
ANALYSIS OPTIONS
Construction of clusters parameters:
Filtering of reference metabolites:
There are no reference metabolites with all the features selected.
Error:
Analysis name already exists or it contains spaces, please write another one.
Run Analysis
Machine Learning
Run Analysis
Machine Learning
Feature only available when you have trained models.
TRAIN MODELS OPTIONS
Parameter Optimization:
Model validation:
Error:
Analysis name already exists or it contains spaces, please write another one.
PREDICT SAMPLES OPTIONS
Please note that the dataset currently being used, chosen in the tab 'Dataset being used', must be the same one used for the model training.
Error:
Analysis name already exists or it contains spaces, please write another one.
Run Analysis
Run Analysis
Univariate Analysis
T-Test
Error:
One-Way Analysis Of Variance (ANOVA)
Error:
Multi-Factor Analysis Of Variance (ANOVA)
Error:
Kruskal-Wallis Test
Error:
Kolmogorov-Smirnov Test
Error:
Fold Change Analysis
Error:
Run Analysis
Run Analysis
Principal Component Analysis
Normal PCA
Error:
Robust PCA
Error:
Run Analysis
Run Analysis
Cluster Analysis
Hierarchical Clustering
Error:
K-means Clustering
Error:
Run Analysis
Run Analysis
Regression Analysis
Linear Regresssion Analysis
Error:
Correlation Analysis
Error:
Run Analysis
Run Analysis
Pathway Analysis
1. Choose the group of organisms where the organism wanted is:
2. Choose the organism:
3. Further options and Submit:
Error:
Pre-Processing
Pre-Processing
Missing Values
Your data has no missing values.
Data Transformation
Scaling
Correction
Smoothing interpolation
Convert to factor
Mean-Centering
First derivative
Multiplicative Scatter Correction
Data Normalization
Detect NMR Peaks
Options to align peaks after their detection: There are two methods available to perform alignment of peaks. The specmine algorithm does not allow overlapping of windows, being the size of the window equal to the step. The MetaboAnalyst method allows overlapping of windows, being the step half the size of the window. The step size for the MetaboAnalyst method has a default of 0.015 for NMR peaks and 0.125 for GC/LC-MS peaks. The bandwidth, used in this method, has the values 10, 30 and 5 for NMR, LC/MS and GC/MS peaks, respectively.
Error:
Subset Dataset
Remove data
Remove data by NAs
Low-level data fusion
Only the samples from the new data provided that have the same name as samples in the current dataset will be joined.
Note that only the formats .mzXML, .netCDF, mzData are supported.
When reading the data, the peak detection will be performed.
Options for the feature (peak) detection in the chromatographic time domain:
Commonly, 30 for LC-MS spectra and 4 for GC-MS spectra.
Commonly, 30 for LC-MS spectra and 5 for GC-MS spectra.
Note that the formats supported are Processed BRUKER or Raw VARIAN.
See the help page for more information on how the data folders should be formatted in each format.
When reading the data, the peak detection will not be performed. To do so, you will have to go to the pre-processing page.
Options for processing the fid spectra into an intensity vs ppm spectra:
Aggregate samples
Samples can be aggregated according to the classes of a certain metadata variable. Samples in the same class will be aggregated together.
Flat Pattern Filter
Name for the new dataset
Analysis Results
Metabolite Identification
Analysis Results
Metabolite Identification
Scores
Cluster Peaks
Top Metabolites
Reference Peaks
Matched Peaks
Cluster Peaks
No metabolites matched this cluster
Analysis Results
Model Training
Analysis Results
Model Training
Model Performance
Best Model's Parameters
Confusion Matrix
Analysis Results
Analysis Results
Pathway Analysis
Loading...
Metabolites with no KEGG code ('-') were not used in the pathway analysis, as it is necessary a KEGG code to do so.
Pathways Results Table
Metabolites Analyzed Information Table
Analysis Results
Analysis Results
T-Test Analysis
Analysis Results
Analysis Results
One-way ANOVA
Analysis Results
Analysis Results
Multifactor ANOVA
Analysis Results
Analysis Results
Kruskal-Wallis Test Analysis
Analysis Results
Analysis Results
Kolmogorov-Smirnov Test Analysis
Analysis Results
Analysis Results
Fold Change Analysis
Analysis Results
Analysis Results
Hierarchical Clustering
Analysis Results
Analysis Results
K-means Clustering
Analysis Results
Analysis Results
Normal PCA
Error:
Error:
Error:
Error:
Error:
Error:
Error:
Analysis Results
Analysis Results
Robust PCA
Error:
Error:
Error:
Error:
Error:
Error:
Error:
Analysis Results
Analysis Results
Correlation Analysis
Data Visualization
Data Visualization
Dataset Visualization Report (html):
Download
The data you are exploring in this tab is the data selected in the sidebar section 'Dataset being used'.
If a metadata variable is not available to choose in the boxplots and/or spectra plots, it means that it needs to be converted to a factor (Pre-Processing page).
Help Page
Help Page