Screendump-GEE10-Synchronized-samples-and-variables(1)

Synchronized plots of samples and variables
The genes highly expressed for a group of samples (in this example the blue group) is positioned in the same place in space as the group of samples. The higly expresssed genes are coloured with red.
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Screendump-GEE10-Finding-variables-which-best-discriminates-groups-1-step-2(1)

Finding discriminating variables
By easily scrolling on the ANOVA bar you can select the variables (genes) that are the best discriminators for the three classes (sample groups). To the left, the three classes E2A/PBX1 (blue), MLL (mauve), and TEL/AML1 (green) are displayed. To the right, the genes obtained through the interactive ANOVA analysis are shown. The genes with a more intense red colour are the best discriminators.
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Screendump-GEE10-Using-Isomap-to-identify-groups(1)

Using isomap to identify groups
With only one key press an isomap graph is created. This is a good method to identify groups. The identified groups very well matches the coloring, which is done based on an annotation.
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Screendump-GEE10-Finding-correlated-variables-to-one-highy-expressed-in-blue-group(1)

Finding correlated variables
By a mouse click on any variable both the positively and negatively correlated variables can be found. When the correlation coefficient slider is changed the plot is instantly updated.
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Screendump-GEE10-showing-label-function(1)

Label interesting samples and genes
Each sample or variable can be marked and labelled with any annotation. This is valuable when results shall be communicated.
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Screendump-GEE10-showing-graphs-for-variables(1)

Connect variables with graph function
Connect samples and variables to find clusters and groups. In the right plot, each variable has been connected with its two nearest neighbours.
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Screendump-GEE10-colouring-using-different-annotations-in-paralell(1)

Synchronized sample plots with different annotations
Coloring two or more  synchronized sample plots based on different annotations helps in analysing data.
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Screendump-GEE10-higher-order-PCA-components(1)

Higher order PCA components
Through one mouse click it is possible to select higher order PCA components.
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Screen shots

Below you find a number of screen shots from Qlucore Omics Explorer. Click on a thumbnail and explore the user interface.

Heatmap 

Heatmap

Finding variables that best discriminates the blue group

Finding variables that best discriminates the blue group

Using ISOMAP to identify subgroups 

Using isomap to identify groups

Finding correlated variables 

Finding correlated variables

Generating list with p, q-values and fold change 

Create a variable list with p, q-values and fold change.

Connect samples to a network 

Connect samples to form a network

5 synchronized plots

5 Synchronized plots 

Higher order PCA components

Higher order PCA components