Qlucore Omics Explorer 3.2 IS released
The new release of Qlucore Omics Explorer, version 3.2, incorporates further enhancements for advanced data analysis packaged with state of the art visualization making it easy to use. The new functionality is in the areas of clustering and classification and will help with improved data exploration and biomarker discovery.
The support of data exploration and identification of potential subgroups and clusters is extensive in Qlucore Omics Explorer. The combination of variance filtering controlled with projection score and visualization using dynamic PCA gives excellent possibilities to identify subgroups and clusters. With the new inbuilt k-means clustering it is possible to get unbiased cluster proposals to further improve the functionality.
The classification functionality is divided into two distinct areas which are reached from two different tabs in the user interface (Build Classifier and Classify). Building and using a classifier belong to the area called supervised methods, as compared to clustering which is unsupervised.
The Build Classifier offers easy access to advanced functionality for creation of a classifier based on the active data set. The objective is to, based on the active data set and a given sample annotation (the Key), create a model that can predict which group a new sample shall belong to. There are three different types of classifiers included; kNN, Support Vector Machines and Random Trees.
The program will do validation automatically.
When the classifier is built it can be used to classify new samples. The variables used in the classifier must be present in the data set to classify. The output from the Classify function is a new sample annotation describing how the sample(s) was classified.
New Plots and improved configuration
The bar plot is a completely new plot type with the option to arrange bars according to two annotations and also combine data from several samples into one bar.
A new option in the line plot library is Kaplan-Meier survival plots based on an arbitrary annotation including survival time.