Univariate analysis methods (Fold change, t-test and Volcano plot are suitable only for analysing two groups (see Diet effect or Platform differences in Analysis).
Other methods (Boxplot, Heatmap, PCA, PLS-DA, Chord diagram) accept various combinations of matrices and diets inputs (see Combinations in Analysis).
Example plots are based on real data and support interactive tools for controlling the plot (zoom, pan, hover).
Boxplot allows simple comparison of groups in the dataset. For each group it displays its median, the first and the third quartile, minimal and maximal values.
Heatmap shows dataset values as colors in 2D matrix. Rows and columns of the matrix can be clustered based on their similarity.
Volcano plot shows significance (t-test p-value) vs. fold change (ratio of group averages). Groups can be defined by different diets for one matrix or different matrices for one diet. Datapoints with high fold change and low p-value represent analytes that have large magnitude changes between groups and are also statistically significant. All p-values are FDR adjusted.
Chord diagram shows significant correlations between analytes in different matrices. Red linkage indicate positive correlation, blue is for negative correlation. Analytes are organised in groups based on their structure.
Outer circle legend items are bold.
Plot shows fold change (ratio of group averages). Groups can be defined by different diets for one matrix or different matrices for one diet.
Principal Component Analysis allows visualization of multidimensional dataset by representing the dataset with new combined variables with maximal variability.
The aim of Partial Least Squares Discriminant Analysis is to achieve maximum separation among classes by rotating the coordinates. It allows visualization of multidimensional dataset and identification of analytes that contribute to the diversity of groups.
Plot shows t-test p-value that reflect significance of analyte level difference between groups. Groups can be defined by different diets for one matrix or different matrices for one diet. All p-values are FDR adjusted.
Sunburst diagram visualizes hierarchical data in concentric circles. You can change the root circle by clicking on one of the sections.
Bubble plot is an extended scatter plot. Additional information is represented by the size of the dots. In MetaboAtlas21 bubble plot is used to compare number of carbon atoms and double bonds of analytes in a lipid class. Size of the points represents normalized intensity.
This scatter plot is used to compare number of carbon atoms and double bonds of analytes in a lipid class in different organs.