Many patients suffering from developmental disorders harbor submicroscopic deletions or duplications that, by affecting the copy number of dosage-sensitive genes or disrupting normal gene expression, lead to disease. However, many aberrations are novel or extremely rare, making clinical interpretation problematic and genotype-phenotype correlations uncertain. Identification of patients sharing a genomic rearrangement and having phenotypic features in common leads to greater certainty in the pathogenic nature of the rearrangement and enables new syndromes to be defined. To facilitate the analysis of these rare events, we have developed an interactive web-based database called DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance, inversions, and translocations. DECIPHER catalogs common copy-number changes in normal populations and thus, by exclusion, enables changes that are novel and potentially pathogenic to be identified. DECIPHER enhances genetic counseling by retrieving relevant information from a variety of bioinformatics resources. Known and predicted genes within an aberration are listed in the DECIPHER patient report, and genes of recognized clinical importance are highlighted and prioritized. DECIPHER enables clinical scientists worldwide to maintain records of phenotype and chromosome rearrangement for their patients and, with informed consent, share this information with the wider clinical research community through display in the genome browser Ensembl. By sharing cases worldwide, clusters of rare cases having phenotype and structural rearrangement in common can be identified, leading to the delineation of new syndromes and furthering understanding of gene function.

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.