Olink Statistical Services
Statistical analysis and data visualization.
Group comparisons presented in a volcano plot
This provides fast and easy testing of a single hypothesis for all proteins analyzed in the study. The test can establish associations between protein levels and the variable of interest. Available tests include, but are not limited to T-tests, ANOVA and linear regressions.
Example of a volcano plot with significance on the y-axis and difference on the x-axis. The color indicates significance (multiple testing corrected p-value<0.05) and the line indicates raw p-value = 0.05. Top 10 proteins are labelled with protein names.
Linear mixed effect models presented in a point-range plot
To study within patient protein level changes over time that is different between groups, linear mixed effect model can be used. Significant proteins are visualized in point-range plots.
Example of point-range plots with NPX on y-axis and Time points on x-axis. The points are the marginal mean estimated by the model and the vertical bars are the 95% confidence intervals. The color indicates the groups.
Data overview and patterns by hierarchical clustering
Hierarchical clustering can be used to get an overview of data, and to identify subgroups of similar samples or proteins based on protein profiles.
Example of a heatmap based on hierarchical clustering analysis where similar proteins and samples are placed next to each other and the protein level is represented by a color gradient.
2947
Biomarker assays
~881 million
Protein data points generated
1182
Publications listed on website