Qlucore, a world leader in the development of bioinformatics software, has unveiled Qlucore Omics Explorer 2.2, the latest version of its advanced data analysis software, now featuring a new built-in functionality to import and normalise miRNA data, mRNA data and DNA methylated data.
Qlucore Omics Explorer 2.2 (OE 2.2) now allows also the direct import of data generated with Agilent equipment. Data generated with the Agilent Feature Extraction software can be directly imported into Qlucore Omics Explorer 2.2, so that scientists, biologists and other researchers benefit from a more streamlined workflow. The import functionality included with Qlucore Omics Explorer 2.2 also features inbuilt pre-settings for well-defined data types, as well as a flexible interface for the normalisation of other data types.
For the first time, Qlucore Omics Explorer 2.2 is now also available in a 64bit version for researchers using a 64bit operating system. Benefits of this version include higher performance, as well as the ability to utilise additional RAM memory. As such, Qlucore Omics Explorer 2.2 can now be used to work with datasets containing up to 150 samples and 2 million variables, using just a regular computer.
“Qlucore Omics Explorer 2.2 makes it very easy to import data generated with both Agilent and Affymetrix, which means that the entire data analysis process can be handled much more efficiently,” says Carl-Johan Ivarsson, president, Qlucore. “Qlucore Omics Explorer has always been a very powerful tool for conducting advanced data analysis. However, the latest enhancements that we’ve included in Qlucore Omics Explorer 2.2 will make it even easier for researchers, biologists and scientists to import and analyse their own data, as well as data produced by their peers, both quickly and easily.”
Qlucore Omics Explorer 2.2 supports instant data analysis. As a result, this latest version of the software will enable scientists and biologists to explore different hypotheses 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.