Highlights of the Latest Version
Get the Wizard! – If you’re upgrading from an older version or a new user, you will find MarkerView Software and its ‘Import Wizard’ functionality highly intuitive, requiring less effort to remember pull down menus and steps between screens. MarkerView’s Import Wizard is a guided workflow tour, requiring less knowledge and skill.
T-Test View – This new feature provides an additional “common” view which is less cumbersome and more productive. Previous versions require more steps and user intervention, including the need to sort on “P” value, look at the top rows, click on a circle and a table of numbers. With the new T-Test View, there is lessjumping around and manual user intervention, making the entire process more productive.
Box & Whiskers Plots – This is a new feature and standard functionality for data analysis when comparing two samples that are frequently taken at different times. When measuring biological samples from two cell lines or subjects, they are used to plot differences between the samples. The workflow will clearly show the differences in a more standardized format which enables clear comparison and provides a more rigorous comparison view. Previous workflows only provide a bottom left quadrant making the judging process challenging for samples with subtle differences. The new Box & Whiskers Plotting functionality provides a standardized way of plotting data and best practices methodology for analysis used in many other applications.
Powerful statistical analysis tools: With MarkerView Software, you can process data acquired from non-classified workflows using Principal Component Analysis (PCA) or Principal Component Analysis-Discriminant Analysis (PCA-DA). This method compares data across multiple samples, reveals any trends amongst the data, and graphically shows the groupings in a Scores plot. The Loadings plot provides valuable insight into the variables responsible for the sample clusters in the Scores plot and illustrates metabolites or biomarkers that being are up- or down-regulated. Principal Component Variable Grouping (PCVG) helps to discover relationships between peaks and assigns related peaks to specific groups, manually or automatically. To highlight relationships, these related peaks groups are displayed in different colors on the Loadings plot (see figure). The t-test statistical test is useful to compare two groups of samples and can help determine which compounds lead to significant differences between the groups.
Information-rich reports: MarkerView Software allows you to see the traditional Scores and Loadings plots generated from PCA and PCA-DA and generate profile plots to confirm the behavior of selected variables across all samples. Profiles can link directly to mass spectra and chromatographic data, providing you with a simple way to review multiple data files simultaneously and confirm correlations. During data review, MarkerView Software lets you create a list of potential biomarkers that can be annotated and used to generate a custom report based on criteria you specify. Figure 1: Principal Component Variable Grouping (PCVG). When using PCVG, MarkerView Software color codes variables in the Loadings Plot (right) that are related to one another, streamlining and simplifying processing.