Prioritize candidate genes.

    This tool allows to search for genes with similar annotations with a training set. This can be used to prioritize candidate genes having similar properties with a set of disease genes.

* Enter the Ensembl IDs or HUGO names corresponding to the training set of genes in the "training genes" box.

* For advanced users: alternatively, you can enter your own selection of annotation keywords with their type ( among "Phenotype", "Gene Ontology BP", "Gene Ontology MF", "Gene Ontology CC", "Protein motif" or "Chromosome distribution") and Pvalues in a tabulated format in the "Pvalue mode" panel.

* Enter the Ensembl IDs or HUGO names corresponding to the candidate genes in the "candidate genes" box.

* Select the type of annotation you want to include in the analysis.

* Press "Submit".

Note: if you don't have Ensembl IDs or HUGO names, use "Batch Gene Entry" to enter your gene names or identifiers then select "Export gene ID list" or directly "Lookalike" in the "Refine" menu at the bottom of the page.

If no candidate genes are provided, the entire genome will be analyzed.

     E.g. Myopathies:

Training gene ID list*:

Candidate gene ID list*:

Do not use Orthology.
Convert training and candidate gene sets to mouse orthologs.
Convert human gene annotation to prioritize mouse genes.
Use phenotype from mouse orthologs.

Annotation sets to include in the search
Gene Ontology Biological Process Gene Ontology Molecular function Gene Ontology Cellular component
Phenotype annotation
Protein motifs
Chromosomal locus distribution
co-occurrence in PubMed articles

 Enter your IDs one per line, separated by a space or a ":"
 You can use ENSEMBL IDs or HUGO biological names. For other names or identifiers please use our conversion tool first.


1 s.

External programs and data are copyrighted by and are the property of their respective authors.
The Manteia system, data and analyses are provided "as is" with no warranties, expressed or implied as to capabilities or accuracy. User assumes the entire risk as to the results and performance of the software, data and documentation


© Olivier Tassy / Olivier Pourquie 2007-2018