The NMC Annotation Tool provides information from UniGene (NCBI), EntrezGene, SwissProt and Gene Ontology (GO). The underlying database is updated weekly and contains the most recent and accurate information available for most model organisms.

The 6 major features are:

• Single search: extraction of data for one gene or protein.

• Batch search: extraction of data for batches of genes or proteins.

• Both single and batch mode allow for search with a large variety of reporter IDs including UniGene Cluster IDs, Agilent Oligo ID, GeneBank accession numbers, Entrez Gene IDs, Heebo ID - Invitrogen, Operon Oligo ID, Swissprot, Affymetrix IDs, Arabidopsis IDs, IMAGE clone ID, Uni. of Iowa Clone ID, symbols and names.

• Manage reporter lists: in folders and share selected lists with other users. When new information is available the user is noticed and the lists can be updated.

• Manual GO Annotation: our GO Annotator Tool allows users to add their own Gene Ontology (GO) annotations to their genes of interest.

• Export: selected information can be exported in excel, text or XML format.

eGOn V2.0 facilitates interpretation of GO annotation. GO terms are retrieved in batch modus from EntrezGene and the GO database and displayed in the GO di-acyclic hierarchical graph (DAG).

Essential features of eGOn V2.0 are:

• Visualization: gene annotations are visualized in the GO DAG or as a table view. The granularity of the GO DAG can be edited freely by the user.

• Filtering: GO annotations can be filtered on evidence codes.

• Include user defined GO annotations: previously added to the Annotation database.

• Statistical analysis: Several gene lists are analyzed simultaneously to compare the distribution of the annotated genes over the GO hierarchy. Statistical tests are implemented to allow the user to compute GO annotation dissimilarity within or between gene lists.

• Connection to Annotation database: Links to Annotation database gene and protein information are offered directly from the GO DAG or in exported data.

• Export: GO DAG information, statistical results and gene and protein information can be exported in excel, text or XML format.

 Reference :

Beisvag et al.: "GeneTools - application for functional annotation and statistical hypothesis testing" (BMC Bioinformatics 2006, 7:470)

Comments:

This is a really interesting online tool. Apart from the annotation features that it has , it also features comparison between the different datasets that one can store therein. 

The supported identifiers include GenBank Accession Numbers, UniGene Cluster ID, IMAGE Clone ID, University of Iowa clones, Agilent Oligo ID, Operon Oligo and Affymetrix ID.

Concerning the comparison between the different sets the following choices are available quoting from the site

 1) Master-Target test:

 One of the two lists of genes compared is the list containing all genes present in the full experiment. This list is called the Master list, e.g. all genes assayed on the chip in a microarray experiment where inference was possible. The test is performed using Fisher's exact test.

2) Mutually Exclusive Target-Target test:

 Two gene lists, A and B, are compared, and there are no genes that are on both lists, e.g. A is a list of genes associated with up-regulation and B is a list of genes associated with down-regulation. This question can be translated into testing if two independent binomial proportions are equal. The test is performed using Fisher's exact test.

3) Intersecting Target-Target Situation:

  Two gene lists, A and B, are compared, and there exist genes that are on both lists, e.g. A is a list of genes associated with treatment A, and B is a list of genes associated with treatment B and there exist genes that have responded to both treatments. Based on a generalized linear model and generalized estimation equations Leisering, Alonzo and Pepe (Biometrics, 2000) defined a test statistic for comparing positive predictive values for diagnostic test for large samples. We have translated their test into the situation of two intersecting gene lists.