FLAGS, frequently mutated genes in public exomes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Casper Shyr, Maja Tarailo-Graovac, Michael Gottlieb, Jessica JY Lee, Clara van Karnebeek, Wyeth W Wasserman

ABSTRACT

BACKGROUND: Dramatic improvements in DNA-sequencing technologies and computational analyses have led to wide use of whole exome sequencing (WES) to identify the genetic basis of Mendelian disorders. More than 180 novel rare-disease-causing genes with Mendelian inheritance patterns have been discovered through sequencing the exomes of just a few unrelated individuals or family members. As rare/novel genetic variants continue to be uncovered, there is a major challenge in distinguishing true pathogenic variants from rare benign mutations. METHODS: We used publicly available exome cohorts, together with the dbSNP database, to derive a list of genes (n = 100) that most frequently exhibit rare (<1%) non-synonymous/splice-site variants in general populations. We termed these genes FLAGS for FrequentLy mutAted GeneS and analyzed their properties. RESULTS: Analysis of FLAGS revealed that these genes have significantly longer protein coding sequences, a greater number of paralogs and display less evolutionarily selective pressure than expected. FLAGS are more frequently reported in PubMed clinical literature and more frequently associated with diseased phenotypes compared to the set of human protein-coding genes. We demonstrated an overlap between FLAGS and the rare-disease causing genes recently discovered through WES studies (n = 10) and the need for replication studies and rigorous statistical and biological analyses when associating FLAGS to rare disease. Finally, we showed how FLAGS are applied in disease-causing variant prioritization approach on exome data from a family affected by an unknown rare genetic disorder. CONCLUSIONS: We showed that some genes are frequently affected by rare, likely functional variants in general population, and are frequently observed in WES studies analyzing diverse rare phenotypes. We found that the rate at which genes accumulate rare mutations is beneficial information for prioritizing candidates. We provided a ranking system based on the mutation accumulation rates for prioritizing exome-captured human genes, and propose that clinical reports associating any disease/phenotype to FLAGS be evaluated with extra caution. More... »

PAGES

64

References to SciGraph publications

  • 2007-10-18. A second generation human haplotype map of over 3.1 million SNPs in NATURE
  • 2014-06. Identification of KMT2D and KDM6A mutations by exome sequencing in Korean patients with Kabuki syndrome in JOURNAL OF HUMAN GENETICS
  • 2005-10. A haplotype map of the human genome in NATURE
  • 2009-07. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm in NATURE PROTOCOLS
  • 2012-04-04. Patterns and rates of exonic de novo mutations in autism spectrum disorders in NATURE
  • 2012-04-04. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations in NATURE
  • 2011-02. Charting a course for genomic medicine from base pairs to bedside in NATURE
  • 2012. Inferring Orthology and Paralogy in EVOLUTIONARY GENOMICS
  • 2011-11. Exome sequencing as a tool for Mendelian disease gene discovery in NATURE REVIEWS GENETICS
  • 2013-10. Rare-disease genetics in the era of next-generation sequencing: discovery to translation in NATURE REVIEWS GENETICS
  • 2014-04. Guidelines for investigating causality of sequence variants in human disease in NATURE
  • 2011-04. Revisiting Mendelian disorders through exome sequencing in HUMAN GENETICS
  • 2012-08. Computational tools for prioritizing candidate genes: boosting disease gene discovery in NATURE REVIEWS GENETICS
  • 2014-03. A general framework for estimating the relative pathogenicity of human genetic variants in NATURE GENETICS
  • 2010-09. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome in NATURE GENETICS
  • 2010-10-28. A map of human genome variation from population-scale sequencing in NATURE
  • 2012-10. Next-generation sequencing: impact of exome sequencing in characterizing Mendelian disorders in JOURNAL OF HUMAN GENETICS
  • 2013-05. Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity in BMC MEDICAL GENOMICS
  • 2010-04. A method and server for predicting damaging missense mutations in NATURE METHODS
  • 2011-09. Unlocking Mendelian disease using exome sequencing in GENOME BIOLOGY
  • 2012-04-04. De novo mutations revealed by whole-exome sequencing are strongly associated with autism in NATURE
  • 2012-10. Samaritan myopathy, an ultimately benign congenital myopathy, is caused by a RYR1 mutation in ACTA NEUROPATHOLOGICA
  • 2008-02. A navigator for human genome epidemiology in NATURE GENETICS
  • 2014-01. The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine in HUMAN GENETICS
  • 2008-05. Genome-wide association studies for complex traits: consensus, uncertainty and challenges in NATURE REVIEWS GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12920-014-0064-y

    DOI

    http://dx.doi.org/10.1186/s12920-014-0064-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1008675542

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25466818


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Biomarkers", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Child, Preschool", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Databases, Factual", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Datasets as Topic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Exome", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Frequency", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mutation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Oligonucleotide Array Sequence Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, RNA", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada", 
                "Treatable Intellectual Disability Endeavour in British Columbia, Vancouver, Canada", 
                "Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shyr", 
            "givenName": "Casper", 
            "id": "sg:person.01166054153.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166054153.39"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada", 
                "Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada", 
                "Treatable Intellectual Disability Endeavour in British Columbia, Vancouver, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tarailo-Graovac", 
            "givenName": "Maja", 
            "id": "sg:person.01016721737.77", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01016721737.77"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gottlieb", 
            "givenName": "Michael", 
            "id": "sg:person.0764773472.70", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764773472.70"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada", 
                "Genome Science and Technology Graduate Program, University of British Columbia, Vancouver, BC, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Jessica JY", 
            "id": "sg:person.0665735235.12", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0665735235.12"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Treatable Intellectual Disability Endeavour in British Columbia, Vancouver, Canada", 
                "Division of Biochemical Diseases, BC Children\u2019s Hospital, Vancouver, BC, Canada", 
                "Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "van Karnebeek", 
            "givenName": "Clara", 
            "id": "sg:person.01037477313.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01037477313.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of British Columbia", 
              "id": "https://www.grid.ac/institutes/grid.17091.3e", 
              "name": [
                "Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada", 
                "Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada", 
                "Treatable Intellectual Disability Endeavour in British Columbia, Vancouver, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wasserman", 
            "givenName": "Wyeth W", 
            "id": "sg:person.01164162122.26", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01164162122.26"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.4137/ebo.s12813", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000827324"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3555", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001268995", 
              "https://doi.org/10.1038/nrg3555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-013-1358-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001440472", 
              "https://doi.org/10.1007/s00439-013-1358-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-013-1358-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001440472", 
              "https://doi.org/10.1007/s00439-013-1358-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13127", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002821806", 
              "https://doi.org/10.1038/nature13127"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13127", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002821806", 
              "https://doi.org/10.1038/nature13127"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng0208-124", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002893574", 
              "https://doi.org/10.1038/ng0208-124"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1215040", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005548694"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/29.1.308", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005817660"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1084/jem.20092215", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006157385"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3253", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006783083", 
              "https://doi.org/10.1038/nrg3253"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth0410-248", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007489634", 
              "https://doi.org/10.1038/nmeth0410-248"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth0410-248", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007489634", 
              "https://doi.org/10.1038/nmeth0410-248"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/jhg.2012.91", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008178877", 
              "https://doi.org/10.1038/jhg.2012.91"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkq953", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009987680"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1755-8794-6-s2-s3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010386267", 
              "https://doi.org/10.1186/1755-8794-6-s2-s3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gks1066", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010434151"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/humu.22547", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010454294"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/jhg.2014.25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013281647", 
              "https://doi.org/10.1038/jhg.2014.25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/jhg.2014.25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013281647", 
              "https://doi.org/10.1038/jhg.2014.25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1003709", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013368129"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/jez.b.22555", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015094625"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2009.86", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015642657", 
              "https://doi.org/10.1038/nprot.2009.86"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkt1196", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015989191"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2014.01.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016608185"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017293702", 
              "https://doi.org/10.1038/nature04226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017293702", 
              "https://doi.org/10.1038/nature04226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017293702", 
              "https://doi.org/10.1038/nature04226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/514346", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017937639"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btt359", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018269189"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2011-12-9-228", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019772105", 
              "https://doi.org/10.1186/gb-2011-12-9-228"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021093950", 
              "https://doi.org/10.1038/nature11011"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbt013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021253735"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbs086", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021271185"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/humu.22237", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021560240"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0248-8663(98)90021-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021689000"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0248-8663(98)90021-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021689000"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ymgme.2014.01.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022834924"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/jmedgenet-2012-101367", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023449353"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-61779-582-4_9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023979622", 
              "https://doi.org/10.1007/978-1-61779-582-4_9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2344", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025856526", 
              "https://doi.org/10.1038/nrg2344"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/amiajnl-2012-001563", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025978126"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/hmg/ddu156", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026835646"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature10989", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027113143", 
              "https://doi.org/10.1038/nature10989"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.110.122549", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028850611"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.110.122549", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028850611"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/0471142905.hg0720s76", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029270941"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1159/000355930", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034082350"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pcbi.1003073", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034526448"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-011-0964-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035732863", 
              "https://doi.org/10.1007/s00439-011-0964-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-011-0964-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035732863", 
              "https://doi.org/10.1007/s00439-011-0964-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/mcb.25.12.5171-5182.2005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036200460"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09764", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037658930", 
              "https://doi.org/10.1038/nature09764"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2174/138920210793175886", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038379070"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.neuron.2012.04.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038724905"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkt1026", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039936775"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.646", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040149061", 
              "https://doi.org/10.1038/ng.646"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.646", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040149061", 
              "https://doi.org/10.1038/ng.646"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/jmg.14.5.316", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040597967"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.molcel.2011.12.026", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041296785"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2013.06.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041976887"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4161/fly.19695", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046734556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047038706", 
              "https://doi.org/10.1038/nrg3031"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.097857.109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047484720"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00401-012-1007-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047608348", 
              "https://doi.org/10.1007/s00401-012-1007-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.3715005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048048079"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature10945", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050249412", 
              "https://doi.org/10.1038/nature10945"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.2892", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050728268", 
              "https://doi.org/10.1038/ng.2892"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature06258", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051134045", 
              "https://doi.org/10.1038/nature06258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/humu.21260", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052120369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/humu.21260", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052120369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/cmb.2013.0158", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059246217"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1079702720", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2014-12", 
        "datePublishedReg": "2014-12-01", 
        "description": "BACKGROUND: Dramatic improvements in DNA-sequencing technologies and computational analyses have led to wide use of whole exome sequencing (WES) to identify the genetic basis of Mendelian disorders. More than 180 novel rare-disease-causing genes with Mendelian inheritance patterns have been discovered through sequencing the exomes of just a few unrelated individuals or family members. As rare/novel genetic variants continue to be uncovered, there is a major challenge in distinguishing true pathogenic variants from rare benign mutations.\nMETHODS: We used publicly available exome cohorts, together with the dbSNP database, to derive a list of genes (n\u2009=\u2009100) that most frequently exhibit rare (<1%) non-synonymous/splice-site variants in general populations. We termed these genes FLAGS for FrequentLy mutAted GeneS and analyzed their properties.\nRESULTS: Analysis of FLAGS revealed that these genes have significantly longer protein coding sequences, a greater number of paralogs and display less evolutionarily selective pressure than expected. FLAGS are more frequently reported in PubMed clinical literature and more frequently associated with diseased phenotypes compared to the set of human protein-coding genes. We demonstrated an overlap between FLAGS and the rare-disease causing genes recently discovered through WES studies (n\u2009=\u200910) and the need for replication studies and rigorous statistical and biological analyses when associating FLAGS to rare disease. Finally, we showed how FLAGS are applied in disease-causing variant prioritization approach on exome data from a family affected by an unknown rare genetic disorder.\nCONCLUSIONS: We showed that some genes are frequently affected by rare, likely functional variants in general population, and are frequently observed in WES studies analyzing diverse rare phenotypes. We found that the rate at which genes accumulate rare mutations is beneficial information for prioritizing candidates. We provided a ranking system based on the mutation accumulation rates for prioritizing exome-captured human genes, and propose that clinical reports associating any disease/phenotype to FLAGS be evaluated with extra caution.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s12920-014-0064-y", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2977320", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1039191", 
            "issn": [
              "1755-8794"
            ], 
            "name": "BMC Medical Genomics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "7"
          }
        ], 
        "name": "FLAGS, frequently mutated genes in public exomes", 
        "pagination": "64", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "295515979f962336b7b977ebf74e6fe2d3dc1d80edbf777e1789c630fd044069"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "25466818"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101319628"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s12920-014-0064-y"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1008675542"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s12920-014-0064-y", 
          "https://app.dimensions.ai/details/publication/pub.1008675542"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T12:21", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87079_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs12920-014-0064-y"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12920-014-0064-y'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12920-014-0064-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12920-014-0064-y'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12920-014-0064-y'


     

    This table displays all metadata directly associated to this object as RDF triples.

    372 TRIPLES      21 PREDICATES      104 URIs      33 LITERALS      21 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s12920-014-0064-y schema:about N04c1eacc905c4a1db7381c2698e89099
    2 N0a035f72da714d6791ee08145ffe00c6
    3 N1b36e1508827491e8f2b6a7106756a6d
    4 N28ffccb4d5c940a2859a71f281ca105a
    5 N3728a01aba9549de898adb6361b35995
    6 N668f27cd10f044e3b03a03ac1112d128
    7 N8e02ecf41e2f4fd981a5daa4d40990ca
    8 Na19ddaed9b52452eaa4c3a498c68ad7e
    9 Nb345bc436a0b49cb859145ef75ed853c
    10 Nd0f07c9df94a4f129053f93adbd0550f
    11 Nd4f17802b6394375b8120f0d3f77178c
    12 Ne9e7dcaba6984fe69d4842fa94bd9bb1
    13 anzsrc-for:06
    14 anzsrc-for:0604
    15 schema:author N7d77f7665ccf4f4e89db6ce6616b79af
    16 schema:citation sg:pub.10.1007/978-1-61779-582-4_9
    17 sg:pub.10.1007/s00401-012-1007-3
    18 sg:pub.10.1007/s00439-011-0964-2
    19 sg:pub.10.1007/s00439-013-1358-4
    20 sg:pub.10.1038/jhg.2012.91
    21 sg:pub.10.1038/jhg.2014.25
    22 sg:pub.10.1038/nature04226
    23 sg:pub.10.1038/nature06258
    24 sg:pub.10.1038/nature09534
    25 sg:pub.10.1038/nature09764
    26 sg:pub.10.1038/nature10945
    27 sg:pub.10.1038/nature10989
    28 sg:pub.10.1038/nature11011
    29 sg:pub.10.1038/nature13127
    30 sg:pub.10.1038/ng.2892
    31 sg:pub.10.1038/ng.646
    32 sg:pub.10.1038/ng0208-124
    33 sg:pub.10.1038/nmeth0410-248
    34 sg:pub.10.1038/nprot.2009.86
    35 sg:pub.10.1038/nrg2344
    36 sg:pub.10.1038/nrg3031
    37 sg:pub.10.1038/nrg3253
    38 sg:pub.10.1038/nrg3555
    39 sg:pub.10.1186/1755-8794-6-s2-s3
    40 sg:pub.10.1186/gb-2011-12-9-228
    41 https://app.dimensions.ai/details/publication/pub.1079702720
    42 https://doi.org/10.1002/0471142905.hg0720s76
    43 https://doi.org/10.1002/humu.21260
    44 https://doi.org/10.1002/humu.22237
    45 https://doi.org/10.1002/humu.22547
    46 https://doi.org/10.1002/jez.b.22555
    47 https://doi.org/10.1016/j.ajhg.2013.06.013
    48 https://doi.org/10.1016/j.ajhg.2014.01.006
    49 https://doi.org/10.1016/j.molcel.2011.12.026
    50 https://doi.org/10.1016/j.neuron.2012.04.009
    51 https://doi.org/10.1016/j.ymgme.2014.01.011
    52 https://doi.org/10.1016/s0248-8663(98)90021-2
    53 https://doi.org/10.1084/jem.20092215
    54 https://doi.org/10.1086/514346
    55 https://doi.org/10.1089/cmb.2013.0158
    56 https://doi.org/10.1093/bib/bbs086
    57 https://doi.org/10.1093/bib/bbt013
    58 https://doi.org/10.1093/bioinformatics/btt359
    59 https://doi.org/10.1093/hmg/ddu156
    60 https://doi.org/10.1093/nar/29.1.308
    61 https://doi.org/10.1093/nar/gkq953
    62 https://doi.org/10.1093/nar/gks1066
    63 https://doi.org/10.1093/nar/gkt1026
    64 https://doi.org/10.1093/nar/gkt1196
    65 https://doi.org/10.1101/gr.097857.109
    66 https://doi.org/10.1101/gr.3715005
    67 https://doi.org/10.1126/science.1215040
    68 https://doi.org/10.1128/mcb.25.12.5171-5182.2005
    69 https://doi.org/10.1136/amiajnl-2012-001563
    70 https://doi.org/10.1136/jmedgenet-2012-101367
    71 https://doi.org/10.1136/jmg.14.5.316
    72 https://doi.org/10.1159/000355930
    73 https://doi.org/10.1371/journal.pcbi.1003073
    74 https://doi.org/10.1371/journal.pgen.1003709
    75 https://doi.org/10.1534/genetics.110.122549
    76 https://doi.org/10.2174/138920210793175886
    77 https://doi.org/10.4137/ebo.s12813
    78 https://doi.org/10.4161/fly.19695
    79 schema:datePublished 2014-12
    80 schema:datePublishedReg 2014-12-01
    81 schema:description BACKGROUND: Dramatic improvements in DNA-sequencing technologies and computational analyses have led to wide use of whole exome sequencing (WES) to identify the genetic basis of Mendelian disorders. More than 180 novel rare-disease-causing genes with Mendelian inheritance patterns have been discovered through sequencing the exomes of just a few unrelated individuals or family members. As rare/novel genetic variants continue to be uncovered, there is a major challenge in distinguishing true pathogenic variants from rare benign mutations. METHODS: We used publicly available exome cohorts, together with the dbSNP database, to derive a list of genes (n = 100) that most frequently exhibit rare (<1%) non-synonymous/splice-site variants in general populations. We termed these genes FLAGS for FrequentLy mutAted GeneS and analyzed their properties. RESULTS: Analysis of FLAGS revealed that these genes have significantly longer protein coding sequences, a greater number of paralogs and display less evolutionarily selective pressure than expected. FLAGS are more frequently reported in PubMed clinical literature and more frequently associated with diseased phenotypes compared to the set of human protein-coding genes. We demonstrated an overlap between FLAGS and the rare-disease causing genes recently discovered through WES studies (n = 10) and the need for replication studies and rigorous statistical and biological analyses when associating FLAGS to rare disease. Finally, we showed how FLAGS are applied in disease-causing variant prioritization approach on exome data from a family affected by an unknown rare genetic disorder. CONCLUSIONS: We showed that some genes are frequently affected by rare, likely functional variants in general population, and are frequently observed in WES studies analyzing diverse rare phenotypes. We found that the rate at which genes accumulate rare mutations is beneficial information for prioritizing candidates. We provided a ranking system based on the mutation accumulation rates for prioritizing exome-captured human genes, and propose that clinical reports associating any disease/phenotype to FLAGS be evaluated with extra caution.
    82 schema:genre research_article
    83 schema:inLanguage en
    84 schema:isAccessibleForFree true
    85 schema:isPartOf N22db49622fce45ff8df703e9d9f91b5f
    86 Nff2543c018974cd0bfc61e4a4f6b3c5f
    87 sg:journal.1039191
    88 schema:name FLAGS, frequently mutated genes in public exomes
    89 schema:pagination 64
    90 schema:productId N0512b57a66924e2b83d2925d17e5cefc
    91 N0574ea8c596d4335856e303e79a77f1f
    92 N258c89b039044035bd808458a446afd9
    93 Naf7ca4f030274d79ae1a111c9bb71d5a
    94 Nb06bc10323124bdabd1c9ced01d5d575
    95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008675542
    96 https://doi.org/10.1186/s12920-014-0064-y
    97 schema:sdDatePublished 2019-04-11T12:21
    98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    99 schema:sdPublisher N71017c4bc66142d59410bdc501d2c1df
    100 schema:url https://link.springer.com/10.1186%2Fs12920-014-0064-y
    101 sgo:license sg:explorer/license/
    102 sgo:sdDataset articles
    103 rdf:type schema:ScholarlyArticle
    104 N04c1eacc905c4a1db7381c2698e89099 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    105 schema:name Mutation
    106 rdf:type schema:DefinedTerm
    107 N0512b57a66924e2b83d2925d17e5cefc schema:name dimensions_id
    108 schema:value pub.1008675542
    109 rdf:type schema:PropertyValue
    110 N0574ea8c596d4335856e303e79a77f1f schema:name pubmed_id
    111 schema:value 25466818
    112 rdf:type schema:PropertyValue
    113 N0a035f72da714d6791ee08145ffe00c6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    114 schema:name Gene Expression Profiling
    115 rdf:type schema:DefinedTerm
    116 N1b36e1508827491e8f2b6a7106756a6d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    117 schema:name Sequence Analysis, RNA
    118 rdf:type schema:DefinedTerm
    119 N22db49622fce45ff8df703e9d9f91b5f schema:volumeNumber 7
    120 rdf:type schema:PublicationVolume
    121 N258c89b039044035bd808458a446afd9 schema:name readcube_id
    122 schema:value 295515979f962336b7b977ebf74e6fe2d3dc1d80edbf777e1789c630fd044069
    123 rdf:type schema:PropertyValue
    124 N28ffccb4d5c940a2859a71f281ca105a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Child, Preschool
    126 rdf:type schema:DefinedTerm
    127 N2c04ea3005e244299a79c2a2465426b2 rdf:first sg:person.01016721737.77
    128 rdf:rest Nbf30b5a75ff64a01b17e62effa724f26
    129 N3728a01aba9549de898adb6361b35995 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    130 schema:name Oligonucleotide Array Sequence Analysis
    131 rdf:type schema:DefinedTerm
    132 N553b9ef3d02c45a694627c5afed7ebc5 rdf:first sg:person.01164162122.26
    133 rdf:rest rdf:nil
    134 N622eaffb63f64cf9835018317f9f6e81 rdf:first sg:person.0665735235.12
    135 rdf:rest Nb672c947f392410983b1a2f8ec17b507
    136 N668f27cd10f044e3b03a03ac1112d128 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Datasets as Topic
    138 rdf:type schema:DefinedTerm
    139 N71017c4bc66142d59410bdc501d2c1df schema:name Springer Nature - SN SciGraph project
    140 rdf:type schema:Organization
    141 N7d77f7665ccf4f4e89db6ce6616b79af rdf:first sg:person.01166054153.39
    142 rdf:rest N2c04ea3005e244299a79c2a2465426b2
    143 N8e02ecf41e2f4fd981a5daa4d40990ca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    144 schema:name Female
    145 rdf:type schema:DefinedTerm
    146 Na19ddaed9b52452eaa4c3a498c68ad7e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    147 schema:name Gene Frequency
    148 rdf:type schema:DefinedTerm
    149 Naf7ca4f030274d79ae1a111c9bb71d5a schema:name doi
    150 schema:value 10.1186/s12920-014-0064-y
    151 rdf:type schema:PropertyValue
    152 Nb06bc10323124bdabd1c9ced01d5d575 schema:name nlm_unique_id
    153 schema:value 101319628
    154 rdf:type schema:PropertyValue
    155 Nb345bc436a0b49cb859145ef75ed853c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    156 schema:name Exome
    157 rdf:type schema:DefinedTerm
    158 Nb672c947f392410983b1a2f8ec17b507 rdf:first sg:person.01037477313.40
    159 rdf:rest N553b9ef3d02c45a694627c5afed7ebc5
    160 Nbf30b5a75ff64a01b17e62effa724f26 rdf:first sg:person.0764773472.70
    161 rdf:rest N622eaffb63f64cf9835018317f9f6e81
    162 Nd0f07c9df94a4f129053f93adbd0550f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    163 schema:name Biomarkers
    164 rdf:type schema:DefinedTerm
    165 Nd4f17802b6394375b8120f0d3f77178c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    166 schema:name Databases, Factual
    167 rdf:type schema:DefinedTerm
    168 Ne9e7dcaba6984fe69d4842fa94bd9bb1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    169 schema:name Humans
    170 rdf:type schema:DefinedTerm
    171 Nff2543c018974cd0bfc61e4a4f6b3c5f schema:issueNumber 1
    172 rdf:type schema:PublicationIssue
    173 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    174 schema:name Biological Sciences
    175 rdf:type schema:DefinedTerm
    176 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    177 schema:name Genetics
    178 rdf:type schema:DefinedTerm
    179 sg:grant.2977320 http://pending.schema.org/fundedItem sg:pub.10.1186/s12920-014-0064-y
    180 rdf:type schema:MonetaryGrant
    181 sg:journal.1039191 schema:issn 1755-8794
    182 schema:name BMC Medical Genomics
    183 rdf:type schema:Periodical
    184 sg:person.01016721737.77 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    185 schema:familyName Tarailo-Graovac
    186 schema:givenName Maja
    187 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01016721737.77
    188 rdf:type schema:Person
    189 sg:person.01037477313.40 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    190 schema:familyName van Karnebeek
    191 schema:givenName Clara
    192 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01037477313.40
    193 rdf:type schema:Person
    194 sg:person.01164162122.26 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    195 schema:familyName Wasserman
    196 schema:givenName Wyeth W
    197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01164162122.26
    198 rdf:type schema:Person
    199 sg:person.01166054153.39 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    200 schema:familyName Shyr
    201 schema:givenName Casper
    202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166054153.39
    203 rdf:type schema:Person
    204 sg:person.0665735235.12 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    205 schema:familyName Lee
    206 schema:givenName Jessica JY
    207 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0665735235.12
    208 rdf:type schema:Person
    209 sg:person.0764773472.70 schema:affiliation https://www.grid.ac/institutes/grid.17091.3e
    210 schema:familyName Gottlieb
    211 schema:givenName Michael
    212 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764773472.70
    213 rdf:type schema:Person
    214 sg:pub.10.1007/978-1-61779-582-4_9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023979622
    215 https://doi.org/10.1007/978-1-61779-582-4_9
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1007/s00401-012-1007-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047608348
    218 https://doi.org/10.1007/s00401-012-1007-3
    219 rdf:type schema:CreativeWork
    220 sg:pub.10.1007/s00439-011-0964-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035732863
    221 https://doi.org/10.1007/s00439-011-0964-2
    222 rdf:type schema:CreativeWork
    223 sg:pub.10.1007/s00439-013-1358-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001440472
    224 https://doi.org/10.1007/s00439-013-1358-4
    225 rdf:type schema:CreativeWork
    226 sg:pub.10.1038/jhg.2012.91 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008178877
    227 https://doi.org/10.1038/jhg.2012.91
    228 rdf:type schema:CreativeWork
    229 sg:pub.10.1038/jhg.2014.25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013281647
    230 https://doi.org/10.1038/jhg.2014.25
    231 rdf:type schema:CreativeWork
    232 sg:pub.10.1038/nature04226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017293702
    233 https://doi.org/10.1038/nature04226
    234 rdf:type schema:CreativeWork
    235 sg:pub.10.1038/nature06258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051134045
    236 https://doi.org/10.1038/nature06258
    237 rdf:type schema:CreativeWork
    238 sg:pub.10.1038/nature09534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010608717
    239 https://doi.org/10.1038/nature09534
    240 rdf:type schema:CreativeWork
    241 sg:pub.10.1038/nature09764 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037658930
    242 https://doi.org/10.1038/nature09764
    243 rdf:type schema:CreativeWork
    244 sg:pub.10.1038/nature10945 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050249412
    245 https://doi.org/10.1038/nature10945
    246 rdf:type schema:CreativeWork
    247 sg:pub.10.1038/nature10989 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027113143
    248 https://doi.org/10.1038/nature10989
    249 rdf:type schema:CreativeWork
    250 sg:pub.10.1038/nature11011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021093950
    251 https://doi.org/10.1038/nature11011
    252 rdf:type schema:CreativeWork
    253 sg:pub.10.1038/nature13127 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002821806
    254 https://doi.org/10.1038/nature13127
    255 rdf:type schema:CreativeWork
    256 sg:pub.10.1038/ng.2892 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050728268
    257 https://doi.org/10.1038/ng.2892
    258 rdf:type schema:CreativeWork
    259 sg:pub.10.1038/ng.646 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040149061
    260 https://doi.org/10.1038/ng.646
    261 rdf:type schema:CreativeWork
    262 sg:pub.10.1038/ng0208-124 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002893574
    263 https://doi.org/10.1038/ng0208-124
    264 rdf:type schema:CreativeWork
    265 sg:pub.10.1038/nmeth0410-248 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007489634
    266 https://doi.org/10.1038/nmeth0410-248
    267 rdf:type schema:CreativeWork
    268 sg:pub.10.1038/nprot.2009.86 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015642657
    269 https://doi.org/10.1038/nprot.2009.86
    270 rdf:type schema:CreativeWork
    271 sg:pub.10.1038/nrg2344 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025856526
    272 https://doi.org/10.1038/nrg2344
    273 rdf:type schema:CreativeWork
    274 sg:pub.10.1038/nrg3031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047038706
    275 https://doi.org/10.1038/nrg3031
    276 rdf:type schema:CreativeWork
    277 sg:pub.10.1038/nrg3253 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006783083
    278 https://doi.org/10.1038/nrg3253
    279 rdf:type schema:CreativeWork
    280 sg:pub.10.1038/nrg3555 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001268995
    281 https://doi.org/10.1038/nrg3555
    282 rdf:type schema:CreativeWork
    283 sg:pub.10.1186/1755-8794-6-s2-s3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010386267
    284 https://doi.org/10.1186/1755-8794-6-s2-s3
    285 rdf:type schema:CreativeWork
    286 sg:pub.10.1186/gb-2011-12-9-228 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019772105
    287 https://doi.org/10.1186/gb-2011-12-9-228
    288 rdf:type schema:CreativeWork
    289 https://app.dimensions.ai/details/publication/pub.1079702720 schema:CreativeWork
    290 https://doi.org/10.1002/0471142905.hg0720s76 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029270941
    291 rdf:type schema:CreativeWork
    292 https://doi.org/10.1002/humu.21260 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052120369
    293 rdf:type schema:CreativeWork
    294 https://doi.org/10.1002/humu.22237 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021560240
    295 rdf:type schema:CreativeWork
    296 https://doi.org/10.1002/humu.22547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010454294
    297 rdf:type schema:CreativeWork
    298 https://doi.org/10.1002/jez.b.22555 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015094625
    299 rdf:type schema:CreativeWork
    300 https://doi.org/10.1016/j.ajhg.2013.06.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041976887
    301 rdf:type schema:CreativeWork
    302 https://doi.org/10.1016/j.ajhg.2014.01.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016608185
    303 rdf:type schema:CreativeWork
    304 https://doi.org/10.1016/j.molcel.2011.12.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041296785
    305 rdf:type schema:CreativeWork
    306 https://doi.org/10.1016/j.neuron.2012.04.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038724905
    307 rdf:type schema:CreativeWork
    308 https://doi.org/10.1016/j.ymgme.2014.01.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022834924
    309 rdf:type schema:CreativeWork
    310 https://doi.org/10.1016/s0248-8663(98)90021-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021689000
    311 rdf:type schema:CreativeWork
    312 https://doi.org/10.1084/jem.20092215 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006157385
    313 rdf:type schema:CreativeWork
    314 https://doi.org/10.1086/514346 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017937639
    315 rdf:type schema:CreativeWork
    316 https://doi.org/10.1089/cmb.2013.0158 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059246217
    317 rdf:type schema:CreativeWork
    318 https://doi.org/10.1093/bib/bbs086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021271185
    319 rdf:type schema:CreativeWork
    320 https://doi.org/10.1093/bib/bbt013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021253735
    321 rdf:type schema:CreativeWork
    322 https://doi.org/10.1093/bioinformatics/btt359 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018269189
    323 rdf:type schema:CreativeWork
    324 https://doi.org/10.1093/hmg/ddu156 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026835646
    325 rdf:type schema:CreativeWork
    326 https://doi.org/10.1093/nar/29.1.308 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005817660
    327 rdf:type schema:CreativeWork
    328 https://doi.org/10.1093/nar/gkq953 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009987680
    329 rdf:type schema:CreativeWork
    330 https://doi.org/10.1093/nar/gks1066 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010434151
    331 rdf:type schema:CreativeWork
    332 https://doi.org/10.1093/nar/gkt1026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039936775
    333 rdf:type schema:CreativeWork
    334 https://doi.org/10.1093/nar/gkt1196 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015989191
    335 rdf:type schema:CreativeWork
    336 https://doi.org/10.1101/gr.097857.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047484720
    337 rdf:type schema:CreativeWork
    338 https://doi.org/10.1101/gr.3715005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048048079
    339 rdf:type schema:CreativeWork
    340 https://doi.org/10.1126/science.1215040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005548694
    341 rdf:type schema:CreativeWork
    342 https://doi.org/10.1128/mcb.25.12.5171-5182.2005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036200460
    343 rdf:type schema:CreativeWork
    344 https://doi.org/10.1136/amiajnl-2012-001563 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025978126
    345 rdf:type schema:CreativeWork
    346 https://doi.org/10.1136/jmedgenet-2012-101367 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023449353
    347 rdf:type schema:CreativeWork
    348 https://doi.org/10.1136/jmg.14.5.316 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040597967
    349 rdf:type schema:CreativeWork
    350 https://doi.org/10.1159/000355930 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034082350
    351 rdf:type schema:CreativeWork
    352 https://doi.org/10.1371/journal.pcbi.1003073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034526448
    353 rdf:type schema:CreativeWork
    354 https://doi.org/10.1371/journal.pgen.1003709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013368129
    355 rdf:type schema:CreativeWork
    356 https://doi.org/10.1534/genetics.110.122549 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028850611
    357 rdf:type schema:CreativeWork
    358 https://doi.org/10.2174/138920210793175886 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038379070
    359 rdf:type schema:CreativeWork
    360 https://doi.org/10.4137/ebo.s12813 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000827324
    361 rdf:type schema:CreativeWork
    362 https://doi.org/10.4161/fly.19695 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046734556
    363 rdf:type schema:CreativeWork
    364 https://www.grid.ac/institutes/grid.17091.3e schema:alternateName University of British Columbia
    365 schema:name Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
    366 Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Vancouver, BC, Canada
    367 Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
    368 Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
    369 Division of Biochemical Diseases, BC Children’s Hospital, Vancouver, BC, Canada
    370 Genome Science and Technology Graduate Program, University of British Columbia, Vancouver, BC, Canada
    371 Treatable Intellectual Disability Endeavour in British Columbia, Vancouver, Canada
    372 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...