GenEx Packages
GenEx comes in three different packages to fulfill different customer needs: Standard, which has all features for basic analyses, Professional which also includes classification methods, and Enterprise, which has all functionalities including advanced expression profiling analyses. The features available in the three packages are indicated in the analysis list.
GenEx Standard
GenEx Standard makes pre-processing of data easy! There are options to calibrate samples with interpolate calibrators, a number of ways of handling missing data, and you can correct for primer-dimers and PCR efficiencies. Samples can also be normalized against reference genes or reference samples, the sample amounts, or a spike. If technical replicates have been made, they are easily normalized as well.
The data editor in GenEx lets you arrange, sort and pre-process the data.
There are statistical analyses to determine differences between two or more groups. This includes Student's t-test for paired and unpaired studies, corresponding non-parametric test, and an ANOVA test for one factor. You can also cluster your genes or samples in a dendrogram to see for example which samples show similar expression profiles. There are several options of letting you visualize the data in a plot including scatter plots, line plots, a bar plot, as well as a box and whiskers plot. The plots can be used to efficiently compare expression profiles of different samples or genes.
Immunoglobulin light chain λ plotted against κ, where green represents healthy
individuals and red lymphoma positive individuals.
A 3D line plot showing how the target genes' expressions in yeast changes over
time after glucose has be added to the growth medium.
GenEx Standard is often sufficient when only one gene is studied at a time. It can be used within for example biochemistry or infection diagnostics. The package includes even more, as can be seen in the analysis list.
GenEx Professional
GenEx Professional includes all analyses in the Standard package and much more. There are advanced multidimensional analyses such as principal component analysis (PCA) and self-organized maps (SOM) that lets you use the expression of several genes to cluster or classify samples. There are also more advanced statistical tests to determine difference of means, such as two-way ANOVA which is used when the effect that two separate factors has on the gene expression. It can be used to investigate if for instance the studied treatments influence the gene expression in a set of age groups differently.
The same data shown in the 3D line plot above is here classified in a SOM. Genes
associated with glycogenesis are shown in red, glycolysis genes in blue and
reference genes in green.
The package also includes several calibration analyses, such as a standard curve, reverse calibration to calibrate unknown samples to a standard curve, and a function to determine the limit of detection (LOD) for your assay.
A standard curve has been fitted to measured data (blue line) and is shown with
a confidence interval (red lines). The red dots represent unknown samples.
This package is recommended when you are analyzing more than one gene in for example an exploratory study. This is often done within the medical field of research. Information of all analysis is included in the analysis list.
GenEx Enterprise
Our most advanced package is the GenEx Enterprise that includes all of the available analyses. The powerful multidimensional methods artificial neural networks (ANN) and support vector machines (SVM) let you build a model of your data that can be used to classify unknown samples in for example diagnostics. The models are easily shared with other GenEx users. P-curve is a form of principal component analysis (PCA) that also lets you classify unknown samples.
Two genes have been used to classify unknown samples with SVM, where red
indicates breast cancer and green indicates no breast cancer.
Several genes have been used to classify samples from breast cancer patients
and healthy patients with p-curves.
One of the new features in GenEx 5 is the experimental plan optimization. It can take data from a previous trial with replicates on each level (subject, sample, RT, qPCR), estimate the noise that is added at each level, and suggest an optimal experimental plan for future trials with minimum total variance under the given budget.
The optimum number of replicates at each level is presented together with the estimated total variance and total cost.
GenEx is excellent tool for predictive studies, when the end product is a model that can classify or calibrate unknown samples. Typical applications include diagnostics of complex diseases, and typical users are pharmaceutical companies. See the analysis list for complete overview of the included analyses.
Learn more
For further information of the analyses in GenEx, see the online manual of the program or contact us.
|
