Go analysis Universal

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There are both pre-set and custom universe options available.

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Entries

Annotations S. cerevisiae (yeast) - ORF (i.e. YNR023W) S. cerevisiae (yeast) - UniprotAC H. sapiens (human) - UniprotAC (i.e. M0R2A7) H. sapiens (human) - ENSEMBL protein (i.e. ENSP00000414321) H. sapiens (human) - ENSEMBL transcript (i.e. ENST00000520420) H. sapiens (human) - ENSEMBL gene (i.e. ENSG00000166558) H. sapiens (human) - gene symbol (i.e. CO039_HUMAN) M. musculus (mouse) - Uniprot AC (i.e. Q60860) M. musculus (mouse) - MGI (i.e. MGI:1858303) M. musculus (mouse) - ENSELBL protein (i.e. ENSMUSP00000134772) M. musculus (mouse) - ENSELBL transcript (i.e. ENSMUST00000000543) M. musculus (mouse) - ENSELBL gene (i.e. ENSMUSG00000070385) M. musculus (mouse) - gene symbol (i.e. Prtn3) C. elegans (caeel) - Uniprot AC (i.e. Q95YA4) D. melanogaster (drome) - Uniprot AC (i.e. Q8IR73) D. melanogaster (drome) - FlyBase (i.e. FBgn0033395) E. coli (ecoli) - Uniprot AC (i.e. P0AG51) D. rerio (danre) - Uniprot AC (i.e. F1R7F7) D. rerio (danre) - ZFIN (i.e. ZDB-GENE-060503-156)

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Just browsing?

• See our sample submission pre-calculated: Proteins up-regulated in prostate cancer
• Pre-load our example and run the tool yourself: click here!
  You can read more about the datasets used in the examples in the multiCM tutorial, section "Example datasets".

Further information

• there are both pre-set and custom universe options
• tutorial - how to submit data, output explanation
• documentation - explains how we all do it!

cleverGO analysis

Newest addition to the cleverSuite is integration of a Gene Ontology analysis. Apart from a twist on traditional GO-term enrichment table (dynamic filtering + term depth filter applicable in realtime), the novelty of the tools comes from visualisation of semantic similarity between enriched GO terms.

To illustrate the tool with an example, you can see a screenshot of the tool below. Where you can see each of the GO terms is represented as a node on the graph. Connections and their strengths are based on semantic similarity between each term pair. Individual GO terms got transformed into clusters terms based on their semantic similarity, providing more complete and easy to digest view of the functionality.

Sample output