HGCS: an online tool for prioritizing disease-causing gene variants by biological distance.
BACKGROUND
Identifying the genotypes underlying human disease phenotypes is a fundamental step in human genetics and medicine. High-throughput genomic technologies provide thousands of genetic variants per individual. The causal genes of a specific phenotype are usually expected to be functionally close to each other. According to this hypothesis, candidate genes are picked from high-throughput data on the basis of their biological proximity to core genes - genes already known to be responsible for the phenotype. There is currently no effective gene-centric online interface for this purpose.


RESULTS
We describe here the human gene connectome server (HGCS), a powerful, easy-to-use interactive online tool enabling researchers to prioritize any list of genes according to their biological proximity to core genes associated with the phenotype of interest. We also make available an updated and extended version for all human gene-specific connectomes. The HGCS is freely available to noncommercial users from: http://hgc.rockefeller.edu.


CONCLUSIONS
The HGCS should help investigators from diverse fields to identify new disease-causing candidate genes more effectively, via a user-friendly online interface.
St, Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA. yitan@rockefeller.edu.
Yuval
Y
Itan
Mark
M
Mazel
Benjamin
B
Mazel
Avinash
A
Abhyankar
Patrick
P
Nitschke
Lluis
L
Quintana-Murci
Stephanie
S
Boisson-Dupuis
Bertrand
B
Boisson
Laurent
L
Abel
Shen-Ying
SY
Zhang
Jean-Laurent
JL
Casanova
D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D056726:Genetic Association Studies / Q000379:methods*; D023281:Genomics / Q000379:methods; D006801:Humans; D015203:Reproducibility of Results; D012984:Software; D014584:User-Computer Interface; D064878:Web Browser