New software will deliver flexible and creative data analysis for the life science and biotech industry.
Qlucore Omics Explorer 2.0 will give researchers the speed and flexibility that they need to reveal important new discoveries.
Qlucore, a world leader in the development of bioinformatics software, has today unveiled the Qlucore Omics Explorer 2.0, a newly enhanced data analysis tool that has been developed for the life science and biotech industry. With its highly intuitive user interface, Qlucore Omics Explorer will allow researchers to shorten analysis time and add more creativity to research, thanks to the product's amazing speed and statistical analysis capabilities.
As it provides users with immediate results, this latest version of Qlucore's software (previously known as Qlucore Gene Expression Explorer) will enable researchers to explore different hypothesis and alternative scenarios within seconds. The software will therefore be invaluable for unveiling important new discoveries, as it will allow the actual researchers – the people with the most biological insight – to study the data and to look for patterns and structures, without needing to be a statistics or computer expert.
"Qlucore Omics Explorer 2.0 has been specially designed to improve everyday efficiency and stimulate creative data analysis," says Carl-Johan Ivarsson, President, Qlucore. "As with previous versions of our software, Qlucore Omics Explorer can provide extremely fast analysis of data sets that contain many samples – even those containing more than 100 million data samples – on a regular PC."
The latest enhancements to Qlucore Omics Explorer mean that the software can provide researchers with very powerful (and highly interactive) hierarchal clustering capabilities. The results are presented both as cluster trees and as a heatmap. The heatmap view works in full synchronisation with each of the other four plot types (PCA sample, PCA variable, scatter and data table).
Researchers can work simultaneously with all five plot types – all of which can be fully synchronised – even if the most common usage will include a subset. As such, if a researcher uses the software's powerful statistical filters, or wishes to deselect a sample group, all five plots are immediately updated to reflect this new point in the analysis.
Scatter plots, which can be used to plot how one variable is distributed over a group of samples, represent another new plot type in Qlucore Omics Explorer 2.0. With scatter plots, the grouping is freely selected among the annotations available for samples. Scatter plots are good for quality control and for presenting key findings and results.
Also new in Qlucore Omics Explorer 2.0 is a powerful log function which allows users to restore their research to an earlier point in their analysis. Since many users often work on parallel projects, it is important to keep track of the analysis steps. As a result, Qlucore Omics Explorer 2.0 gives the user full freedom to explore data in their own way, with the log function available to ensure that the user can document exactly which steps have been taken, without being forced to follow a single path.
Qlucore started as a collaborative research project at Lund University, Sweden, supported by researchers at the Departments of Mathematics and Clinical Genetics, in order to address the vast amount of high-dimensional data generated with microarray gene expression analysis. As a result, it was recognised that an interactive scientific software tool was needed to conceptualise the ideas evolving from the research collaboration.
The basic concept behind the software is to provide a tool that can take full advantage of the most powerful pattern recogniser that exists - the human brain. The result is a core software engine that visualises the data in 3D and will aid the user in identifying hidden structures and patterns. Over the last few years, major efforts have been made to optimise the early ideas and to develop a core software engine that is extremely fast, allowing the user to interactively and in real time instantly explore and analyse high-dimensional data sets with the use of a normal PC.
Qlucore was founded in early 2007 and the first product released was the “Qlucore Gene Expression Explorer 1.0”. The latest version of this software, now called "Qlucore Omics Explorer 2.0", was released in May 2009, and represents a major step forward with the added support for hierarchical clustering, scatter plots and powerful log function. The combination of instant visualisation and advanced statistics support gives the user new opportunities. All user action is at most two mouse clicks away. The Company's early customers are mainly from the Life-science and Biotech industries, but solutions for other industries are currently under development.
One of the early key methods used by Qlucore Gene Expression Explorer to visualise data is dynamic principal component analysis (PCA), an innovative way of combining PCA analysis with immediate user interaction. Dynamic PCA is PCA analysis combined with instant user response, a combination which provides an optimal way for users to visualise and analyse a large dataset by presenting a comprehensive view of the data set at the same time, since the user is given full freedom to explore all possible versions of the presented view. Later versions combine PCA analysis with other analysis methods such as hierarchical clustering.
Chaz Brooks, CBC
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