New version: Qlucore Omics Explorer 3.2. Improved data insights through clustering and classification

We are delighted to introduce the new version of Qlucore Omics Explorer - 3.2, an exciting release with functionality that helps you analyze your data even easier and more freely.

Version 3.2 focuses on maximizing the outcome of your research by adding:

• extensive classifier capabilities
• unsupervised clustering
• bar plot, Kaplan-Meier plot

Classifiers are used to create a model of your data to predict an outcome. In Qlucore Omics Explorer 3.2 you can build and validate classifiers of various types. Support Vector Machines, Random trees and kNN are supported. Validation is integrated with ROC/AUC plots, internal cross validation scheme and support for validation using an external data set. When a classifier is created it can be used to classify samples in a second data set. 

K-means clustering is added. The k-means clustering nicely complements the hierarchical clustering and the PCA plot. The silhouette plot option is added to support with validation. 

The rich plot options are extended with a bar plot. In the bar plot data can be grouped according to multiple sample annotations for experiments with for instance several doses at different time-points.