Next-generation sequencing using a pre-designed gene panel for the molecular diagnosis of congenital disorders in pediatric patients View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Eileen C. P. Lim, Maggie Brett, Angeline H. M. Lai, Siew-Peng Lee, Ee-Shien Tan, Saumya S. Jamuar, Ivy S. L. Ng, Ene-Choo Tan

ABSTRACT

BACKGROUND: Next-generation sequencing (NGS) has revolutionized genetic research and offers enormous potential for clinical application. Sequencing the exome has the advantage of casting the net wide for all known coding regions while targeted gene panel sequencing provides enhanced sequencing depths and can be designed to avoid incidental findings in adult-onset conditions. A HaloPlex panel consisting of 180 genes within commonly altered chromosomal regions is available for use on both the Ion Personal Genome Machine (PGM) and MiSeq platforms to screen for causative mutations in these genes. METHODS: We used this Haloplex ICCG panel for targeted sequencing of 15 patients with clinical presentations indicative of an abnormality in one of the 180 genes. Sequencing runs were done using the Ion 318 Chips on the Ion Torrent PGM. Variants were filtered for known polymorphisms and analysis was done to identify possible disease-causing variants before validation by Sanger sequencing. When possible, segregation of variants with phenotype in family members was performed to ascertain the pathogenicity of the variant. RESULTS: More than 97% of the target bases were covered at >20×. There was an average of 9.6 novel variants per patient. Pathogenic mutations were identified in five genes for six patients, with two novel variants. There were another five likely pathogenic variants, some of which were unreported novel variants. CONCLUSIONS: In a cohort of 15 patients, we were able to identify a likely genetic etiology in six patients (40%). Another five patients had candidate variants for which further evaluation and segregation analysis are ongoing. Our results indicate that the HaloPlex ICCG panel is useful as a rapid, high-throughput and cost-effective screening tool for 170 of the 180 genes. There is low coverage for some regions in several genes which might have to be supplemented by Sanger sequencing. However, comparing the cost, ease of analysis, and shorter turnaround time, it is a good alternative to exome sequencing for patients whose features are suggestive of a genetic etiology involving one of the genes in the panel. More... »

PAGES

33

References to SciGraph publications

  • 2011-09. An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities in GENETICS IN MEDICINE
  • 2014-12. Performance of chromosomal microarray for patients with intellectual disabilities/developmental delay, autism, and multiple congenital anomalies in a Chinese cohort in MOLECULAR CYTOGENETICS
  • 2015-04. Panel-based genetic diagnostic testing for inherited eye diseases is highly accurate and reproducible, and more sensitive for variant detection, than exome sequencing in GENETICS IN MEDICINE
  • 2013-07. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing in GENETICS IN MEDICINE
  • 2009-12. Mutation screening in 86 known X-linked mental retardation genes by droplet-based multiplex PCR and massive parallel sequencing in THE HUGO JOURNAL
  • 2013-09. ACMG clinical laboratory standards for next-generation sequencing in GENETICS IN MEDICINE
  • 2015-01. ACMG policy statement: updated recommendations regarding analysis and reporting of secondary findings in clinical genome-scale sequencing in GENETICS IN MEDICINE
  • 1999-10. Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2 in NATURE GENETICS
  • 2009-02. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing in NATURE BIOTECHNOLOGY
  • 2007-11. Multiplex amplification of large sets of human exons in NATURE METHODS
  • 2013-10. Using large clinical data sets to infer pathogenicity for rare copy number variants in autism cohorts in MOLECULAR PSYCHIATRY
  • 2010. The Prevalence of Congenital Anomalies in Europe in RARE DISEASES EPIDEMIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s40246-015-0055-x

    DOI

    http://dx.doi.org/10.1186/s40246-015-0055-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1036191054

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26666243


    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": "Child", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Child, Preschool", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cohort Studies", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Databases, Genetic", 
            "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 Library", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genetic Diseases, Inborn", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genetic Predisposition to Disease", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genome, Human", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genomics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "High-Throughput Nucleotide Sequencing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Infant", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Infant, Newborn", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Molecular Diagnostic Techniques", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mutation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Polymorphism, Single Nucleotide", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sensitivity and Specificity", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Alignment", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, DNA", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "KK Women's and Children's Hospital", 
              "id": "https://www.grid.ac/institutes/grid.414963.d", 
              "name": [
                "KK Research Centre, KK Women\u2019s and Children\u2019s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lim", 
            "givenName": "Eileen C. P.", 
            "id": "sg:person.011301562452.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011301562452.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "KK Women's and Children's Hospital", 
              "id": "https://www.grid.ac/institutes/grid.414963.d", 
              "name": [
                "KK Research Centre, KK Women\u2019s and Children\u2019s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Brett", 
            "givenName": "Maggie", 
            "id": "sg:person.01303250346.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01303250346.74"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National University of Singapore", 
              "id": "https://www.grid.ac/institutes/grid.4280.e", 
              "name": [
                "Genetics Service, Department of Paediatrics, KK Women\u2019s and Children\u2019s Hospital, 229899, Singapore, Singapore", 
                "Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lai", 
            "givenName": "Angeline H. M.", 
            "id": "sg:person.011031070402.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011031070402.46"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "KK Women's and Children's Hospital", 
              "id": "https://www.grid.ac/institutes/grid.414963.d", 
              "name": [
                "KK Research Centre, KK Women\u2019s and Children\u2019s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Siew-Peng", 
            "id": "sg:person.01111457743.64", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01111457743.64"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National University of Singapore", 
              "id": "https://www.grid.ac/institutes/grid.4280.e", 
              "name": [
                "Genetics Service, Department of Paediatrics, KK Women\u2019s and Children\u2019s Hospital, 229899, Singapore, Singapore", 
                "Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tan", 
            "givenName": "Ee-Shien", 
            "id": "sg:person.0632654064.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632654064.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National University of Singapore", 
              "id": "https://www.grid.ac/institutes/grid.4280.e", 
              "name": [
                "Genetics Service, Department of Paediatrics, KK Women\u2019s and Children\u2019s Hospital, 229899, Singapore, Singapore", 
                "Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jamuar", 
            "givenName": "Saumya S.", 
            "id": "sg:person.0705351175.53", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705351175.53"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National University of Singapore", 
              "id": "https://www.grid.ac/institutes/grid.4280.e", 
              "name": [
                "Genetics Service, Department of Paediatrics, KK Women\u2019s and Children\u2019s Hospital, 229899, Singapore, Singapore", 
                "Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ng", 
            "givenName": "Ivy S. L.", 
            "id": "sg:person.011302341612.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011302341612.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National University of Singapore", 
              "id": "https://www.grid.ac/institutes/grid.4280.e", 
              "name": [
                "KK Research Centre, KK Women\u2019s and Children\u2019s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore", 
                "Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tan", 
            "givenName": "Ene-Choo", 
            "id": "sg:person.01160256622.32", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160256622.32"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/13810", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002301472", 
              "https://doi.org/10.1038/13810"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/13810", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002301472", 
              "https://doi.org/10.1038/13810"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5858/arpa.2013-0625-oa", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007686399"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ab.2005.10.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010671200"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ab.2005.10.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010671200"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11568-010-9137-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011468063", 
              "https://doi.org/10.1007/s11568-010-9137-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pcbi.1003031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011830079"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-90-481-9485-8_20", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014129525", 
              "https://doi.org/10.1007/978-90-481-9485-8_20"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-90-481-9485-8_20", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014129525", 
              "https://doi.org/10.1007/978-90-481-9485-8_20"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejpn.2013.04.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014429157"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/gim.2014.172", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016507460", 
              "https://doi.org/10.1038/gim.2014.172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/gim.2013.73", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017226766", 
              "https://doi.org/10.1038/gim.2013.73"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/gim.2014.151", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019004528", 
              "https://doi.org/10.1038/gim.2014.151"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2015.05.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020712008"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2015.05.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020712008"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2010.04.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027541669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/ana.24303", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027848291"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1755-8166-7-34", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030657394", 
              "https://doi.org/10.1186/1755-8166-7-34"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0093409", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033378833"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/gim.2013.92", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036558007", 
              "https://doi.org/10.1038/gim.2013.92"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1542/peds.2010-2989", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036754755"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/jmedgenet-2014-102624", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040614845"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1523", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040653661", 
              "https://doi.org/10.1038/nbt.1523"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0078496", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042820586"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/mp.2012.138", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044963448", 
              "https://doi.org/10.1038/mp.2012.138"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth1110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045927978", 
              "https://doi.org/10.1038/nmeth1110"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jaci.2013.08.032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047797071"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1097/gim.0b013e31822c79f9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049056484", 
              "https://doi.org/10.1097/gim.0b013e31822c79f9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1097/gim.0b013e31822c79f9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049056484", 
              "https://doi.org/10.1097/gim.0b013e31822c79f9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/515582", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058789970"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/gtmb.2010.0101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059267687"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbu008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059413042"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2144/000114217", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1069096703"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1078965394", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015-12", 
        "datePublishedReg": "2015-12-01", 
        "description": "BACKGROUND: Next-generation sequencing (NGS) has revolutionized genetic research and offers enormous potential for clinical application. Sequencing the exome has the advantage of casting the net wide for all known coding regions while targeted gene panel sequencing provides enhanced sequencing depths and can be designed to avoid incidental findings in adult-onset conditions. A HaloPlex panel consisting of 180 genes within commonly altered chromosomal regions is available for use on both the Ion Personal Genome Machine (PGM) and MiSeq platforms to screen for causative mutations in these genes.\nMETHODS: We used this Haloplex ICCG panel for targeted sequencing of 15 patients with clinical presentations indicative of an abnormality in one of the 180 genes. Sequencing runs were done using the Ion 318 Chips on the Ion Torrent PGM. Variants were filtered for known polymorphisms and analysis was done to identify possible disease-causing variants before validation by Sanger sequencing. When possible, segregation of variants with phenotype in family members was performed to ascertain the pathogenicity of the variant.\nRESULTS: More than 97% of the target bases were covered at >20\u00d7. There was an average of 9.6 novel variants per patient. Pathogenic mutations were identified in five genes for six patients, with two novel variants. There were another five likely pathogenic variants, some of which were unreported novel variants.\nCONCLUSIONS: In a cohort of 15 patients, we were able to identify a likely genetic etiology in six patients (40%). Another five patients had candidate variants for which further evaluation and segregation analysis are ongoing. Our results indicate that the HaloPlex ICCG panel is useful as a rapid, high-throughput and cost-effective screening tool for 170 of the 180 genes. There is low coverage for some regions in several genes which might have to be supplemented by Sanger sequencing. However, comparing the cost, ease of analysis, and shorter turnaround time, it is a good alternative to exome sequencing for patients whose features are suggestive of a genetic etiology involving one of the genes in the panel.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s40246-015-0055-x", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2752768", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1033252", 
            "issn": [
              "1473-9542", 
              "1479-7364"
            ], 
            "name": "Human Genomics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "9"
          }
        ], 
        "name": "Next-generation sequencing using a pre-designed gene panel for the molecular diagnosis of congenital disorders in pediatric patients", 
        "pagination": "33", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "ac661c36aa5d6db98275cacf4ac6dd67d9c7a304f8068b5cf965d6d997362a2b"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "26666243"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101202210"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s40246-015-0055-x"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1036191054"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s40246-015-0055-x", 
          "https://app.dimensions.ai/details/publication/pub.1036191054"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T18:25", 
        "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/v90/0000000001_0000000264/records_8675_00000537.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1186%2Fs40246-015-0055-x"
      }
    ]
     

    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/s40246-015-0055-x'

    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/s40246-015-0055-x'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s40246-015-0055-x'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s40246-015-0055-x'


     

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

    311 TRIPLES      21 PREDICATES      80 URIs      43 LITERALS      31 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s40246-015-0055-x schema:about N005d8caa75d947a6a2a1d02f17bf354c
    2 N01f63fdd2bba4850bbd3f52e1c88217c
    3 N06f6cc8e150b49458aef059ffda4b8d0
    4 N07ffba3e746847f7a05fbdf2bf3e1453
    5 N190a5cae22fd4d01a144d05e92324676
    6 N1bf642465d7e4ea8ad6b7c63d2480829
    7 N1ec63a4de6ff483284e89162495dce94
    8 N1ffc21eb5ebc460bbf73534d2a2d0f83
    9 N2c56aa6576a843eba4a9ab0ded617893
    10 N2ff615babd714bab8f75132fdb036eb1
    11 N366f56942fbb48798f76b65abacc9865
    12 N385cffdac3d64c599fc1b7506aab2d7c
    13 N46e70702bd1044648aa8f7a8f92d527e
    14 N4f395b2fcfea416da87dfdbc08134dfb
    15 N69b3d572feeb47b5ab7360f70f3b3910
    16 N781a89ef352c468592b4c803eb0a9647
    17 N82065e765cc54e8fad37da5c36172eb3
    18 Nacf7bd54e0474e55a725ddf13d12e796
    19 Nbacb6169a40945e69ca12615e84e47c5
    20 Nc033c317d06949ec80a509f2e7819869
    21 Ndf97464094a344ce94d034dec0be00fc
    22 Nfccc0fb2dbb14228b3ee3474ea899b0e
    23 anzsrc-for:06
    24 anzsrc-for:0604
    25 schema:author N4ff60cb22d5642e8890bbc948b3cc644
    26 schema:citation sg:pub.10.1007/978-90-481-9485-8_20
    27 sg:pub.10.1007/s11568-010-9137-y
    28 sg:pub.10.1038/13810
    29 sg:pub.10.1038/gim.2013.73
    30 sg:pub.10.1038/gim.2013.92
    31 sg:pub.10.1038/gim.2014.151
    32 sg:pub.10.1038/gim.2014.172
    33 sg:pub.10.1038/mp.2012.138
    34 sg:pub.10.1038/nbt.1523
    35 sg:pub.10.1038/nmeth1110
    36 sg:pub.10.1097/gim.0b013e31822c79f9
    37 sg:pub.10.1186/1755-8166-7-34
    38 https://app.dimensions.ai/details/publication/pub.1078965394
    39 https://doi.org/10.1002/ana.24303
    40 https://doi.org/10.1016/j.ab.2005.10.001
    41 https://doi.org/10.1016/j.ajhg.2010.04.006
    42 https://doi.org/10.1016/j.ajhg.2015.05.022
    43 https://doi.org/10.1016/j.ejpn.2013.04.010
    44 https://doi.org/10.1016/j.jaci.2013.08.032
    45 https://doi.org/10.1086/515582
    46 https://doi.org/10.1089/gtmb.2010.0101
    47 https://doi.org/10.1093/bib/bbu008
    48 https://doi.org/10.1136/jmedgenet-2014-102624
    49 https://doi.org/10.1371/journal.pcbi.1003031
    50 https://doi.org/10.1371/journal.pone.0078496
    51 https://doi.org/10.1371/journal.pone.0093409
    52 https://doi.org/10.1542/peds.2010-2989
    53 https://doi.org/10.2144/000114217
    54 https://doi.org/10.5858/arpa.2013-0625-oa
    55 schema:datePublished 2015-12
    56 schema:datePublishedReg 2015-12-01
    57 schema:description BACKGROUND: Next-generation sequencing (NGS) has revolutionized genetic research and offers enormous potential for clinical application. Sequencing the exome has the advantage of casting the net wide for all known coding regions while targeted gene panel sequencing provides enhanced sequencing depths and can be designed to avoid incidental findings in adult-onset conditions. A HaloPlex panel consisting of 180 genes within commonly altered chromosomal regions is available for use on both the Ion Personal Genome Machine (PGM) and MiSeq platforms to screen for causative mutations in these genes. METHODS: We used this Haloplex ICCG panel for targeted sequencing of 15 patients with clinical presentations indicative of an abnormality in one of the 180 genes. Sequencing runs were done using the Ion 318 Chips on the Ion Torrent PGM. Variants were filtered for known polymorphisms and analysis was done to identify possible disease-causing variants before validation by Sanger sequencing. When possible, segregation of variants with phenotype in family members was performed to ascertain the pathogenicity of the variant. RESULTS: More than 97% of the target bases were covered at >20×. There was an average of 9.6 novel variants per patient. Pathogenic mutations were identified in five genes for six patients, with two novel variants. There were another five likely pathogenic variants, some of which were unreported novel variants. CONCLUSIONS: In a cohort of 15 patients, we were able to identify a likely genetic etiology in six patients (40%). Another five patients had candidate variants for which further evaluation and segregation analysis are ongoing. Our results indicate that the HaloPlex ICCG panel is useful as a rapid, high-throughput and cost-effective screening tool for 170 of the 180 genes. There is low coverage for some regions in several genes which might have to be supplemented by Sanger sequencing. However, comparing the cost, ease of analysis, and shorter turnaround time, it is a good alternative to exome sequencing for patients whose features are suggestive of a genetic etiology involving one of the genes in the panel.
    58 schema:genre research_article
    59 schema:inLanguage en
    60 schema:isAccessibleForFree true
    61 schema:isPartOf N9e8023484a0e44bcbf4f6ea977262434
    62 Nd72fd1cbc89c43d2b19a2e2750e3d3ea
    63 sg:journal.1033252
    64 schema:name Next-generation sequencing using a pre-designed gene panel for the molecular diagnosis of congenital disorders in pediatric patients
    65 schema:pagination 33
    66 schema:productId N04e9d774b38b4c9f9dbe22d4533a6742
    67 N1aa0633918dd4a7d90161c516aa86224
    68 N1bec6d2e50034e308b618ab67bfbb87c
    69 N8cc250412a1a41098129eee670664ff0
    70 Na18eb12fb5024516aa3b517ce0ca9690
    71 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036191054
    72 https://doi.org/10.1186/s40246-015-0055-x
    73 schema:sdDatePublished 2019-04-10T18:25
    74 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    75 schema:sdPublisher N77e10585e1e244ffa474c22945ddb0a5
    76 schema:url http://link.springer.com/10.1186%2Fs40246-015-0055-x
    77 sgo:license sg:explorer/license/
    78 sgo:sdDataset articles
    79 rdf:type schema:ScholarlyArticle
    80 N005d8caa75d947a6a2a1d02f17bf354c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    81 schema:name Child, Preschool
    82 rdf:type schema:DefinedTerm
    83 N01f63fdd2bba4850bbd3f52e1c88217c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    84 schema:name Mutation
    85 rdf:type schema:DefinedTerm
    86 N04e9d774b38b4c9f9dbe22d4533a6742 schema:name nlm_unique_id
    87 schema:value 101202210
    88 rdf:type schema:PropertyValue
    89 N06f6cc8e150b49458aef059ffda4b8d0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    90 schema:name Male
    91 rdf:type schema:DefinedTerm
    92 N07ffba3e746847f7a05fbdf2bf3e1453 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    93 schema:name Humans
    94 rdf:type schema:DefinedTerm
    95 N190a5cae22fd4d01a144d05e92324676 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    96 schema:name Sensitivity and Specificity
    97 rdf:type schema:DefinedTerm
    98 N19c641565b4e4f40abee7a23b3166e9a rdf:first sg:person.01111457743.64
    99 rdf:rest Nb9f27455c4f34b8e8f8d3eb91b166273
    100 N1aa0633918dd4a7d90161c516aa86224 schema:name doi
    101 schema:value 10.1186/s40246-015-0055-x
    102 rdf:type schema:PropertyValue
    103 N1bec6d2e50034e308b618ab67bfbb87c schema:name readcube_id
    104 schema:value ac661c36aa5d6db98275cacf4ac6dd67d9c7a304f8068b5cf965d6d997362a2b
    105 rdf:type schema:PropertyValue
    106 N1bf642465d7e4ea8ad6b7c63d2480829 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    107 schema:name Infant, Newborn
    108 rdf:type schema:DefinedTerm
    109 N1ec63a4de6ff483284e89162495dce94 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    110 schema:name Cohort Studies
    111 rdf:type schema:DefinedTerm
    112 N1ffc21eb5ebc460bbf73534d2a2d0f83 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    113 schema:name Gene Library
    114 rdf:type schema:DefinedTerm
    115 N2c56aa6576a843eba4a9ab0ded617893 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    116 schema:name Child
    117 rdf:type schema:DefinedTerm
    118 N2ff615babd714bab8f75132fdb036eb1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    119 schema:name Sequence Analysis, DNA
    120 rdf:type schema:DefinedTerm
    121 N366f56942fbb48798f76b65abacc9865 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    122 schema:name High-Throughput Nucleotide Sequencing
    123 rdf:type schema:DefinedTerm
    124 N385cffdac3d64c599fc1b7506aab2d7c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Polymorphism, Single Nucleotide
    126 rdf:type schema:DefinedTerm
    127 N46e70702bd1044648aa8f7a8f92d527e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    128 schema:name Infant
    129 rdf:type schema:DefinedTerm
    130 N4f395b2fcfea416da87dfdbc08134dfb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    131 schema:name Molecular Diagnostic Techniques
    132 rdf:type schema:DefinedTerm
    133 N4ff60cb22d5642e8890bbc948b3cc644 rdf:first sg:person.011301562452.04
    134 rdf:rest Nd9f751b0d3654811a2d85b38996fdd87
    135 N69b3d572feeb47b5ab7360f70f3b3910 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    136 schema:name Genetic Predisposition to Disease
    137 rdf:type schema:DefinedTerm
    138 N77e10585e1e244ffa474c22945ddb0a5 schema:name Springer Nature - SN SciGraph project
    139 rdf:type schema:Organization
    140 N781a89ef352c468592b4c803eb0a9647 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    141 schema:name Databases, Genetic
    142 rdf:type schema:DefinedTerm
    143 N82065e765cc54e8fad37da5c36172eb3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    144 schema:name Exome
    145 rdf:type schema:DefinedTerm
    146 N8cc250412a1a41098129eee670664ff0 schema:name dimensions_id
    147 schema:value pub.1036191054
    148 rdf:type schema:PropertyValue
    149 N9e8023484a0e44bcbf4f6ea977262434 schema:volumeNumber 9
    150 rdf:type schema:PublicationVolume
    151 Na18eb12fb5024516aa3b517ce0ca9690 schema:name pubmed_id
    152 schema:value 26666243
    153 rdf:type schema:PropertyValue
    154 Na3f946b961da4255a6d43e88a2dbd1a2 rdf:first sg:person.01160256622.32
    155 rdf:rest rdf:nil
    156 Nacf7bd54e0474e55a725ddf13d12e796 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Female
    158 rdf:type schema:DefinedTerm
    159 Nae1fbe81195d4dd6a8894bc2032644d8 rdf:first sg:person.011031070402.46
    160 rdf:rest N19c641565b4e4f40abee7a23b3166e9a
    161 Nb32517869f494f22ad2e0d209ee625ca rdf:first sg:person.011302341612.51
    162 rdf:rest Na3f946b961da4255a6d43e88a2dbd1a2
    163 Nb9f27455c4f34b8e8f8d3eb91b166273 rdf:first sg:person.0632654064.14
    164 rdf:rest Ne3ea009173d74f74b51f791bc7756012
    165 Nbacb6169a40945e69ca12615e84e47c5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    166 schema:name Genome, Human
    167 rdf:type schema:DefinedTerm
    168 Nc033c317d06949ec80a509f2e7819869 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    169 schema:name Sequence Alignment
    170 rdf:type schema:DefinedTerm
    171 Nd72fd1cbc89c43d2b19a2e2750e3d3ea schema:issueNumber 1
    172 rdf:type schema:PublicationIssue
    173 Nd9f751b0d3654811a2d85b38996fdd87 rdf:first sg:person.01303250346.74
    174 rdf:rest Nae1fbe81195d4dd6a8894bc2032644d8
    175 Ndf97464094a344ce94d034dec0be00fc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    176 schema:name Genomics
    177 rdf:type schema:DefinedTerm
    178 Ne3ea009173d74f74b51f791bc7756012 rdf:first sg:person.0705351175.53
    179 rdf:rest Nb32517869f494f22ad2e0d209ee625ca
    180 Nfccc0fb2dbb14228b3ee3474ea899b0e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    181 schema:name Genetic Diseases, Inborn
    182 rdf:type schema:DefinedTerm
    183 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    184 schema:name Biological Sciences
    185 rdf:type schema:DefinedTerm
    186 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    187 schema:name Genetics
    188 rdf:type schema:DefinedTerm
    189 sg:grant.2752768 http://pending.schema.org/fundedItem sg:pub.10.1186/s40246-015-0055-x
    190 rdf:type schema:MonetaryGrant
    191 sg:journal.1033252 schema:issn 1473-9542
    192 1479-7364
    193 schema:name Human Genomics
    194 rdf:type schema:Periodical
    195 sg:person.011031070402.46 schema:affiliation https://www.grid.ac/institutes/grid.4280.e
    196 schema:familyName Lai
    197 schema:givenName Angeline H. M.
    198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011031070402.46
    199 rdf:type schema:Person
    200 sg:person.01111457743.64 schema:affiliation https://www.grid.ac/institutes/grid.414963.d
    201 schema:familyName Lee
    202 schema:givenName Siew-Peng
    203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01111457743.64
    204 rdf:type schema:Person
    205 sg:person.011301562452.04 schema:affiliation https://www.grid.ac/institutes/grid.414963.d
    206 schema:familyName Lim
    207 schema:givenName Eileen C. P.
    208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011301562452.04
    209 rdf:type schema:Person
    210 sg:person.011302341612.51 schema:affiliation https://www.grid.ac/institutes/grid.4280.e
    211 schema:familyName Ng
    212 schema:givenName Ivy S. L.
    213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011302341612.51
    214 rdf:type schema:Person
    215 sg:person.01160256622.32 schema:affiliation https://www.grid.ac/institutes/grid.4280.e
    216 schema:familyName Tan
    217 schema:givenName Ene-Choo
    218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160256622.32
    219 rdf:type schema:Person
    220 sg:person.01303250346.74 schema:affiliation https://www.grid.ac/institutes/grid.414963.d
    221 schema:familyName Brett
    222 schema:givenName Maggie
    223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01303250346.74
    224 rdf:type schema:Person
    225 sg:person.0632654064.14 schema:affiliation https://www.grid.ac/institutes/grid.4280.e
    226 schema:familyName Tan
    227 schema:givenName Ee-Shien
    228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632654064.14
    229 rdf:type schema:Person
    230 sg:person.0705351175.53 schema:affiliation https://www.grid.ac/institutes/grid.4280.e
    231 schema:familyName Jamuar
    232 schema:givenName Saumya S.
    233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705351175.53
    234 rdf:type schema:Person
    235 sg:pub.10.1007/978-90-481-9485-8_20 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014129525
    236 https://doi.org/10.1007/978-90-481-9485-8_20
    237 rdf:type schema:CreativeWork
    238 sg:pub.10.1007/s11568-010-9137-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1011468063
    239 https://doi.org/10.1007/s11568-010-9137-y
    240 rdf:type schema:CreativeWork
    241 sg:pub.10.1038/13810 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002301472
    242 https://doi.org/10.1038/13810
    243 rdf:type schema:CreativeWork
    244 sg:pub.10.1038/gim.2013.73 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017226766
    245 https://doi.org/10.1038/gim.2013.73
    246 rdf:type schema:CreativeWork
    247 sg:pub.10.1038/gim.2013.92 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036558007
    248 https://doi.org/10.1038/gim.2013.92
    249 rdf:type schema:CreativeWork
    250 sg:pub.10.1038/gim.2014.151 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019004528
    251 https://doi.org/10.1038/gim.2014.151
    252 rdf:type schema:CreativeWork
    253 sg:pub.10.1038/gim.2014.172 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016507460
    254 https://doi.org/10.1038/gim.2014.172
    255 rdf:type schema:CreativeWork
    256 sg:pub.10.1038/mp.2012.138 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044963448
    257 https://doi.org/10.1038/mp.2012.138
    258 rdf:type schema:CreativeWork
    259 sg:pub.10.1038/nbt.1523 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040653661
    260 https://doi.org/10.1038/nbt.1523
    261 rdf:type schema:CreativeWork
    262 sg:pub.10.1038/nmeth1110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045927978
    263 https://doi.org/10.1038/nmeth1110
    264 rdf:type schema:CreativeWork
    265 sg:pub.10.1097/gim.0b013e31822c79f9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049056484
    266 https://doi.org/10.1097/gim.0b013e31822c79f9
    267 rdf:type schema:CreativeWork
    268 sg:pub.10.1186/1755-8166-7-34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030657394
    269 https://doi.org/10.1186/1755-8166-7-34
    270 rdf:type schema:CreativeWork
    271 https://app.dimensions.ai/details/publication/pub.1078965394 schema:CreativeWork
    272 https://doi.org/10.1002/ana.24303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027848291
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1016/j.ab.2005.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010671200
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.1016/j.ajhg.2010.04.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027541669
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.1016/j.ajhg.2015.05.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020712008
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.1016/j.ejpn.2013.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014429157
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.1016/j.jaci.2013.08.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047797071
    283 rdf:type schema:CreativeWork
    284 https://doi.org/10.1086/515582 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058789970
    285 rdf:type schema:CreativeWork
    286 https://doi.org/10.1089/gtmb.2010.0101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059267687
    287 rdf:type schema:CreativeWork
    288 https://doi.org/10.1093/bib/bbu008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059413042
    289 rdf:type schema:CreativeWork
    290 https://doi.org/10.1136/jmedgenet-2014-102624 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040614845
    291 rdf:type schema:CreativeWork
    292 https://doi.org/10.1371/journal.pcbi.1003031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011830079
    293 rdf:type schema:CreativeWork
    294 https://doi.org/10.1371/journal.pone.0078496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042820586
    295 rdf:type schema:CreativeWork
    296 https://doi.org/10.1371/journal.pone.0093409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033378833
    297 rdf:type schema:CreativeWork
    298 https://doi.org/10.1542/peds.2010-2989 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036754755
    299 rdf:type schema:CreativeWork
    300 https://doi.org/10.2144/000114217 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069096703
    301 rdf:type schema:CreativeWork
    302 https://doi.org/10.5858/arpa.2013-0625-oa schema:sameAs https://app.dimensions.ai/details/publication/pub.1007686399
    303 rdf:type schema:CreativeWork
    304 https://www.grid.ac/institutes/grid.414963.d schema:alternateName KK Women's and Children's Hospital
    305 schema:name KK Research Centre, KK Women’s and Children’s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore
    306 rdf:type schema:Organization
    307 https://www.grid.ac/institutes/grid.4280.e schema:alternateName National University of Singapore
    308 schema:name Genetics Service, Department of Paediatrics, KK Women’s and Children’s Hospital, 229899, Singapore, Singapore
    309 KK Research Centre, KK Women’s and Children’s Hospital, 100 Bukit Timah Road, 229899, Singapore, Singapore
    310 Paediatrics Academic Clinical Programme, SingHealth Duke-NUS Graduate Medical School, 169857, Singapore, Singapore
    311 rdf:type schema:Organization
     




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


    ...