Visualization as a tool for better findings

Visualization for new findings

Visualization techniques have been used to simplify and focus complex messages and content for as long as we know. In the 'Omics' areas it is difficult to work with research without using software tools. Many tools use visualization as the last step in a work flow whereas visualization is presented from the start with Qlucore Omics Explorer.

Visualization provides several benefits:

• An immediate and easily understood data overview
• Visual and clear feedback on analysis actions taken
• An option to discuss data and content with a colleague
• Support in data mining and data exploration

Users frequently choose visualization techniques when data mining or data exploration is the study’s key objective, but for a study with other objectives it can be tempting to directly apply a statistical test to verify the outcome. However, this approach can be non-optimal since new and unknown signals can be missed. Instead we suggest that analysis always should be started with an exploration phase, with Qlucore Omics Explorer this a quick process and the time required is minimal.

The combination of Principal Component Analysis visualization and Projection Score is an excellent way to easily explore a data set for unknown information. At www.qlucore.com/documentation you can download the 'Generate hypotheses assisted by projection score and enable new discoveries' document. This is a step by step example on how important an exploration phase can be.

The required steps for data exploration with Qlucore are:

1. Load the data in Qlucore Omics Explorer
2. Use variance filtering to find the maximum Projection Score.
3. Create a sample annotation to describe any new groups. Go back to step 2. If no new groups can be identified continue to step 4.
4. Investigate the identified patterns and structures and compare them with known annotations by using one-click coloring option. If they are explained by the main hypothesis, then you are fine. If not, then continue the analysis to try to understand what the source of the pattern and structures are.

With Qlucore Omics Explorer you have the capability to undertake explorative analysis as well as hypothesis testing, which means that you can continue with the analysis after step 3 without having to reload any data. The program includes a wide range of statistical tests for the analysis and you can also write statistical tests in R and run them from the program – all without reloading data.