Digital Differential Display Guide
Try in DDD 
Basics
The foundation of DDD is UniGene. UniGene employs a conservative method to assign all the human EST sequences that meet minimal standards of quality to distinct "clusters", each representing a unique human expressed gene. DDD takes advantage of UniGene by comparing the number of times sequences from different libraries were assigned to a particular UniGene cluster. This has the advantage that DDD will only report on sequences that we have confidence in and represent bona fide expressed genes in a species.
There will of course be many differences in the number of sequences contained in each library that are assigned to a particular UniGene cluster, but only some of these differences are likely to reflect biological reality. Therefore DDD employs a statistical method of comparison - The Fisher Exact Test - to identify only those differences that are likely to be real. One important factor in determining statistical relevance is the absolute number of sequences in each library that have been successfully assigned to a UniGene cluster. In many cases there are not enough sequences in dbEST libraries to meet the threshold of significance employed in the Fisher Exact Test. Since DDD will only yield a report if there are differences that exceed this threshold, it is expected that many comparisons will yield nothing.
Select species
Define pools
A pool is a collection of libraries (minimum 1 library) that you want to group together on the basis of your own criteria for comparison with other pools you will (later) define. Enter the name of the pool in the text box. Select libraries by clicking the checkboxes on individual libraries (you can edit the pool later if you wish) and click 'Continue'. Click on 'Start Over' if you want to abandon the current session and begin DDD for another species.
Define the second pool for comparison in the same way.
You can add more pools or edit the existing ones using 'Edit Pool' and 'New Pool' links.
View Results
DDD only reports on a cluster if at least one pairwise comparison results in a statistically significant difference. Each row in the results table represents a UniGene cluster. The numerical value is the fraction of sequences within the pool that mapped to the cluster shown. The dot is a visual aid that reflects the numerical values.
