PhenCode: connecting ENCODE data with mutations and phenotype

Belinda Giardine(Pennsylvania State University), Cathy Riemer(Pennsylvania State University), Tim Hefferon(National Human Genome Research Institute), Daryl J. Thomas(University of California, Santa Cruz), Fan Hsu(University of California, Santa Cruz), Julian Zielenski(Hospital for Sick Children), Yunhua Sang(Hospital for Sick Children), Laura Elnitski(National Human Genome Research Institute), Garry R. Cutting(Johns Hopkins University), Heather Trumbower(University of California, Santa Cruz), Andrew D. Kern(University of California, Santa Cruz), Robert M. Kuhn(University of California, Santa Cruz), George P. Patrinos(Erasmus MC), Jim R. Hughes(MRC Weatherall Institute of Molecular Medicine), Douglas R. Higgs(MRC Weatherall Institute of Molecular Medicine), David H.K. Chui(Boston University), Charles R. Scriver(Montreal Children's Hospital), Manyphong Phommarinh(Montreal Children's Hospital), Santosh K. Patnaik(Albert Einstein College of Medicine), Olga O. Blumenfeld(Albert Einstein College of Medicine), Bruce Gottlieb(Jewish General Hospital), Mauno Vihinen(Tampere University of Applied Sciences), Jouni Väliaho(Tampere University of Applied Sciences), Jim Kent(University of California, Santa Cruz), Webb Miller(Pennsylvania State University), Ross C. Hardison(Pennsylvania State University)
Human Mutation
January 1, 2007
Cited by 82Open Access
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Abstract

PhenCode (Phenotypes for ENCODE; http://www.bx.psu.edu/phencode) is a collaborative, exploratory project to help understand phenotypes of human mutations in the context of sequence and functional data from genome projects. Currently, it connects human phenotype and clinical data in various locus-specific databases (LSDBs) with data on genome sequences, evolutionary history, and function from the ENCODE project and other resources in the UCSC Genome Browser. Initially, we focused on a few selected LSDBs covering genes encoding alpha- and beta-globins (HBA, HBB), phenylalanine hydroxylase (PAH), blood group antigens (various genes), androgen receptor (AR), cystic fibrosis transmembrane conductance regulator (CFTR), and Bruton's tyrosine kinase (BTK), but we plan to include additional loci of clinical importance, ultimately genomewide. We have also imported variant data and associated OMIM links from Swiss-Prot. Users can find interesting mutations in the UCSC Genome Browser (in a new Locus Variants track) and follow links back to the LSDBs for more detailed information. Alternatively, they can start with queries on mutations or phenotypes at an LSDB and then display the results at the Genome Browser to view complementary information such as functional data (e.g., chromatin modifications and protein binding from the ENCODE consortium), evolutionary constraint, regulatory potential, and/or any other tracks they choose. We present several examples illustrating the power of these connections for exploring phenotypes associated with functional elements, and for identifying genomic data that could help to explain clinical phenotypes.


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