eMSTAT Solution

Statistical Analysis Software for Direct Ionization Mass Spectrometry

Enabling statistical analysis of chromatography and direct ionization mass spectrometry data regardless of user expertice

Sample group differentiation—such as when comparing against benchmark products in the product development phase or in sample pass/fail assessment during quality control—can be difficult when relying on conventional qualitative and quantitative analytical techniques. The process typically involves multivariate analysis using large amounts of chromatogram or MS spectrum data to search for markers that can help differentiate between sample groups, and to visualize sample characteristics using these markers. It also requires modeling using training data and discriminant analysis to scientifically determine the characteristics of unknown samples, including their condition (e.g., deterioration), type, and place of origin. The eMSTAT Solution statistical analysis software is equipped with a range of features that make multivariate analysis more accessible and user-friendly for everyone—even when analyzing large volumes of data from various analytical techniques (LC-MS, DI MS, or other MS spectra and chromatograms).

Features

Statistical Analysis Mode for Intuitive Data Analysis Operations

The software’s Statistical Analysis Mode contains extensive, easy-to-use functions for univariate and multivariate analysis that enable even users without statistical analysis expertise to identify marker peaks for sample differentiation and discrimination.
Dynamic Grouping Function for Flexible Sample Grouping

Leveraging the software’s quality information library, the dynamic grouping function facilitates marker discovery by enabling fexible sample grouping in various combinations.
Discriminant Analysis Mode Supports Grouping of Unknown Samples

Discriminant models for discrimination of unknown samples can be created using marker peaks identified in Statistical Analysis Mode. With single-step mode switching, statistical data obtained in Statistical Analysis Mode can be used Discriminant Analysis Mode.

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