eMSTAT Solution™
eMSTAT(easy mass spectrometric statistical) Solution enables easy statistical analysis of MALDI-TOF MS/DPiMS measurement data by anyone.
- Описание
- Features
- Specifications
Описание
Features
Statistical Analysis Mode
Users can easily differentiate samples and identify marker peaks using univariate and multivariate analysis tools.
Discriminant Analysis Mode
Implement discoveries from Statistical Analysis Mode to discriminate unknown samples.
Flexible Dynamic Grouping Function
Flexible sample grouping based on registered quality information facilitates biomarker discovery.
Features
Statistical Analysis Mode
Users can easily differentiate samples and identify marker peaks using univariate and multivariate analysis tools.
Discriminant Analysis Mode
Implement discoveries from Statistical Analysis Mode to discriminate unknown samples.
Polystyrene (heated and unheated) polymers were separated into two groups (heated or unheated) by multivariate analysis (PLS-DA) of the MALDI mass spectrum (Score Plot). A Loading Plot can be used to confirm which peaks (marker peaks) affect the differences between the two groups.
Using marker peaks identified by multivariate analysis to create a discriminant model and discriminate (SVM) between heated and unheated polymers in a polystyrene mass spectrum, obtained separately, resulted in correct discrimination of all polymers. By using eMSTAT Solution in combination with MALDI mass spectrometry, which can easily measure samples with large molecular weight, in addition to synthetic polymers, a wide variety of samples, such as protein, fat, or sugar samples, can be easily differentiated.
Flexible Dynamic Grouping Function
Easy Differentiation for Beef Classification
Flexible sample grouping based on registered quality information facilitates biomarker discovery.
Extracts from commercial beef (Tasmanian and A5/A4 grade Wagyu beef) were analyzed in a DPiMS-2020 mass spectrometer. The resulting spectra were then analyzed by PLS discriminant analysis. A Score Plot confirms grouping into three groups and a Loading Plot confirms which metabolite peaks affect grouping.
With eMSTAT Solution, spectra obtained by convenient metabolite analysis in a DPiMS-2020 spectrometer can be used to easily differentiate between differences in food, plant, and other samples, and screen for information about metabolites that contribute to differentiation.
Supports a Variety of Data Formats from MALDI-TOF and DPiMS Analyses
JCAMP, ASCII and mzML data input are all supported.
Specifications
| Item | Description | |
|---|---|---|
| Analysis functions | Univariate analysis | t-test Mann-Whitney U test ANOVA (analysis of variance) |
| Multivariate analysis | PCA (Principal Component Analysis) PLS-DA |
|
| Discriminant analysis | Support Vector Machine（SVM） Random Forest |
|
| Other | Dynamic grouping | |
| Display functions | Multivariate analysis | Peak Matrix Box Plot ROC AUC Score/Loading Plot Dendrogram |
| Discriminant analysis | Discriminant analysis results (group and score) Unknown samples superimposed on Score Plot |
|
| Input-output data | Input | ASCII format peak lists JCAMP format peak lists mzML format peak lists (only supports Centroid mode, 1 scan/per file, data uncompressed) Note: File name must only contain half-width alphanumeric characters. |
| Output | Peak lists (txt format) Analysis results (xlsm format) Graph screenshot |
|
| Operating system | OS | Windows® 10 Pro, 64-bit (English/Chinese) |
