Abstract for presentation at 11th International Congress of Human Genetics

Pathologene: A Genome-Scale Analysis Of Protein Sequence And Interaction Data For Candidate Gene Prediction

  • Dr Merridee Wouters, Victor Chang Cardiac Research Institute, Australia
  • Mr Jason Liu, Victor Chang Cardiac Research Institute, Australia
  • Ms Lena Feng, Victor Chang Cardiac Research Institute, Australia
  • A/Prof Diane Fatkin, Victor Chang Cardiac Research Institute, Australia
  • Dr Richard George, Victor Chang Cardiac Research Institute, Australia

    • Identification of genes responsible for human disease is essential in the development of diagnostics and therapeutics. Linkage analysis is a successful procedure to associate diseases with specific genomic regions. Unfortunately, isolating the disease-causing gene(s) is difficult. Gene intervals can be large, containing hundreds of genes, which make experimental methods time-consuming and expensive. We present a novel computational approach, Pathologene, to prioritise candidate disease genes for further experimental study. Starting with a gene interval Pathologene applies two methods of candidate gene prediction; Disease Gene Profiling and Common Pathway Scanning. Both methods use either known disease genes or disease intervals as starting points to identify novel disease genes. On a test set of 29 diseases, our combined methods of disease gene prediction have a sensitivity of 0.569 and specificity of 0.956. On average, Pathologene reduces the candidate list by over 10-fold. The Pathologene website, www.pathologene.org, is available to identify potential disease genes in a user-specified interval.

    Conference Organiser - ICMS Pty Ltd