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MetaRanker Server ver. 1.0

MetaRanker prioritizes the entire protein-coding part of the human genome based on heterogeneous user-specified data sets:

  1. Genome-wide association study SNP to phenotype associations.
  2. Known susceptibility genes, which based on high-confidence protein-protein interaction data are used to identify interacting candidate protein-products.
  3. Data from linkage studies capturing co-segregation of chromosomal regions and disease-specific phenotypes in families.
  4. Quantitative data on disease similarities, which may add information that cross normal disease and risk-phenotype definition barriers.
  5. Differential gene expression data, which may add important tissue-specific information.

Instructions Output format Article abstract

SUBMISSION

Metaranker options

    Please select the gene ID nomenclature used in the input files:
    


1. Genome-wide association data

    Please choose SNP p-value file (mandatory):
    
      File includes header:
      SNP ID column: P-value column:
      File type:

    SNP to gene mapping file (if left blank default mapping is used):
    
      File type:


2. Candidate gene interaction data

    Please choose susceptibility gene list file:
    

    or enter Ensembl gene identifyers:
    

3. Linkage study data

    Please choose file with linkage intervals:
    
     File includes header:

    or enter intervals:
    

4. Phenotype-similarity data

    Please choose the keyword most similar to the phenotype of interest:
    

5. Differential gene expression data

    Please choose gene p-value file:
    
      File includes header:
      Gene ID column: P-value column:
      Sort in ascending or descending order:




  Computation time for a 5 mio. SNP GWAS is ~30 minutes.

  Please Note: Currently the email returned upon completion of the webservice contains a broken link. In case You specified Your email address please prefix that link with 'www.cbs.dtu.dk' to access the results.


Confidentiality:
The data are kept confidential and will be deleted after processing.

CITATION

For publication of results, please cite:

Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes
Tune H. Pers, Niclas Tue Hansen, Kasper Lage, Pernille Koefoed, Piotr Dworzynski, Martin Lee Miller, Tracey J. Flint, Erling Mellerup, Henrik Dam, Ole A. Andreassen, Srdjan Djurovic, Ingrid Melle, Anders D. Borglum, Thomas Werge, Shaun Purcel, Manuel A. Ferreira, Irene Kouskoumvekaki, Christopher T. Workman, Torben Hansen, Ole Mors, Soren Brunak

Genetic Epidemiology, Volume 35, Issue 5, pages 318-332, July 2011

View the abstract.


GETTING HELP

Scientific issues:        Technical problems: