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PhenCode: connecting ENCODE data with mutations and phenotype.

Giardine, Belinda; Riemer, Cathy; Hefferon, Tim; Thomas, Daryl; Hsu, Fan; Zielenski, Julian; Sang, Yunhua; Elnitski, Laura; Cutting, Garry and Trumbower, Heather, et al. (2007) In Human Mutation 28(6). p.554-562
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... (More)
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. (Less)
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@article{accec614-e143-4a8b-9078-c2e9ca709626,
  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.},
  author       = {Giardine, Belinda and Riemer, Cathy and Hefferon, Tim and Thomas, Daryl and Hsu, Fan and Zielenski, Julian and Sang, Yunhua and Elnitski, Laura and Cutting, Garry and Trumbower, Heather and Kern, Andrew and Kuhn, Robert and Patrinos, George P and Hughes, Jim and Higgs, Doug and Chui, David and Scriver, Charles and Phommarinh, Manyphong and Patnaik, Santosh K and Blumenfeld, Olga and Gottlieb, Bruce and Vihinen, Mauno and Väliaho, Jouni and Kent, Jim and Miller, Webb and Hardison, Ross C},
  issn         = {1059-7794},
  keyword      = {Globins: genetics,Phenylalanine Hydroxylase: genetics,Genetic: standards,Databases,Blood Group Antigens: genetics,Cystic Fibrosis Transmembrane Conductance Regulator: genetics,Protein-Tyrosine Kinases: genetics,Receptors,Androgen: genetics},
  language     = {eng},
  number       = {6},
  pages        = {554--562},
  publisher    = {John Wiley & Sons},
  series       = {Human Mutation},
  title        = {PhenCode: connecting ENCODE data with mutations and phenotype.},
  url          = {http://dx.doi.org/10.1002/humu.20484},
  volume       = {28},
  year         = {2007},
}