When studying a dataset, it is common practice to examine it from many perspectives. In GeneLinkerô, this is done by displaying the dataset values in a table or color matrix plot, or by performing experiments (such as clustering) on the data and displaying the results in different types of plots.
Shared selection is the process by which selecting one or more elements of the same type (such as genes, samples, or clusters) in one table or plot, selects the same element or elements in all other applicable tables or plots instantaneously. This powerful facility makes the features you want to study distinct in all locations concurrently.
For example, if you have a table view and a color matrix plot of a dataset, and a matrix tree and cluster plot of a clustering experiment based on that dataset, selecting a gene in the table viewer instantly selects the same gene in all the other plots.
A gene has global scope. This means that if a gene is present in more than one dataset, selecting it in a table or plot of one dataset selects it in the tables or plots of the other dataset.
A sample is relevant to all datasets and experiments derived from a single source dataset. In the Experiments navigator, this means the scope of a sample is a single branch of the tree.
A cluster is relevant only to the experiment it was created within.
A principal component is relevant only to the experiment it was created within.
If you have a gene selected, and you display another table or plot that contains that gene, the gene will be highlighted when the new table or plot is displayed.
Highlight a gene on any table or plot or in the Genes, or Gene Lists navigator. The gene is highlighted wherever it exists (tables, plots, navigators).
Highlight a sample in a table or plot. The sample and all samples related by sample merging are highlighted on all other tables or plots of datasets or experiments derived from the same dataset.
Highlight a cluster (or node) on a centroid or SOM plot (either in the legend or on the plot). One or more of the genes or samples in that cluster are highlighted on any other plots derived from the same source dataset.
Creating a Table View of Gene Expression Data
Creating a Color Matrix Plot