The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification
Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation o...
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Gespeichert in:
| Autor*in: |
Alex H. Wagner [verfasserIn] Lawrence Babb [verfasserIn] Gil Alterovitz [verfasserIn] Michael Baudis [verfasserIn] Matthew Brush [verfasserIn] Daniel L. Cameron [verfasserIn] Melissa Cline [verfasserIn] Malachi Griffith [verfasserIn] Obi L. Griffith [verfasserIn] Sarah E. Hunt [verfasserIn] David Kreda [verfasserIn] Jennifer M. Lee [verfasserIn] Stephanie Li [verfasserIn] Javier Lopez [verfasserIn] Eric Moyer [verfasserIn] Tristan Nelson [verfasserIn] Ronak Y. Patel [verfasserIn] Kevin Riehle [verfasserIn] Peter N. Robinson [verfasserIn] Shawn Rynearson [verfasserIn] Helen Schuilenburg [verfasserIn] Kirill Tsukanov [verfasserIn] Brian Walsh [verfasserIn] Melissa Konopko [verfasserIn] Heidi L. Rehm [verfasserIn] Andrew D. Yates [verfasserIn] Robert R. Freimuth [verfasserIn] Reece K. Hart [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Cell Genomics - Elsevier, 2022, 1(2021), 2, Seite 100027- |
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| Übergeordnetes Werk: |
volume:1 ; year:2021 ; number:2 ; pages:100027- |
| Links: |
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| DOI / URN: |
10.1016/j.xgen.2021.100027 |
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| Katalog-ID: |
DOAJ029958024 |
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| 245 | 1 | 4 | |a The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification |
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| 520 | |a Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). | ||
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| 700 | 0 | |a Gil Alterovitz |e verfasserin |4 aut | |
| 700 | 0 | |a Michael Baudis |e verfasserin |4 aut | |
| 700 | 0 | |a Matthew Brush |e verfasserin |4 aut | |
| 700 | 0 | |a Daniel L. Cameron |e verfasserin |4 aut | |
| 700 | 0 | |a Melissa Cline |e verfasserin |4 aut | |
| 700 | 0 | |a Malachi Griffith |e verfasserin |4 aut | |
| 700 | 0 | |a Obi L. Griffith |e verfasserin |4 aut | |
| 700 | 0 | |a Sarah E. Hunt |e verfasserin |4 aut | |
| 700 | 0 | |a David Kreda |e verfasserin |4 aut | |
| 700 | 0 | |a Jennifer M. Lee |e verfasserin |4 aut | |
| 700 | 0 | |a Stephanie Li |e verfasserin |4 aut | |
| 700 | 0 | |a Javier Lopez |e verfasserin |4 aut | |
| 700 | 0 | |a Eric Moyer |e verfasserin |4 aut | |
| 700 | 0 | |a Tristan Nelson |e verfasserin |4 aut | |
| 700 | 0 | |a Ronak Y. Patel |e verfasserin |4 aut | |
| 700 | 0 | |a Kevin Riehle |e verfasserin |4 aut | |
| 700 | 0 | |a Peter N. Robinson |e verfasserin |4 aut | |
| 700 | 0 | |a Shawn Rynearson |e verfasserin |4 aut | |
| 700 | 0 | |a Helen Schuilenburg |e verfasserin |4 aut | |
| 700 | 0 | |a Kirill Tsukanov |e verfasserin |4 aut | |
| 700 | 0 | |a Brian Walsh |e verfasserin |4 aut | |
| 700 | 0 | |a Melissa Konopko |e verfasserin |4 aut | |
| 700 | 0 | |a Heidi L. Rehm |e verfasserin |4 aut | |
| 700 | 0 | |a Andrew D. Yates |e verfasserin |4 aut | |
| 700 | 0 | |a Robert R. Freimuth |e verfasserin |4 aut | |
| 700 | 0 | |a Reece K. Hart |e verfasserin |4 aut | |
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10.1016/j.xgen.2021.100027 doi (DE-627)DOAJ029958024 (DE-599)DOAJ3859bdfa7d3c4f77bb01c6a9ee4f69c7 DE-627 ger DE-627 rakwb eng QH426-470 RC31-1245 Alex H. Wagner verfasserin aut The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). variation genomics GA4GH standard VOCA computed identifiers Genetics Internal medicine Lawrence Babb verfasserin aut Gil Alterovitz verfasserin aut Michael Baudis verfasserin aut Matthew Brush verfasserin aut Daniel L. Cameron verfasserin aut Melissa Cline verfasserin aut Malachi Griffith verfasserin aut Obi L. Griffith verfasserin aut Sarah E. Hunt verfasserin aut David Kreda verfasserin aut Jennifer M. Lee verfasserin aut Stephanie Li verfasserin aut Javier Lopez verfasserin aut Eric Moyer verfasserin aut Tristan Nelson verfasserin aut Ronak Y. Patel verfasserin aut Kevin Riehle verfasserin aut Peter N. Robinson verfasserin aut Shawn Rynearson verfasserin aut Helen Schuilenburg verfasserin aut Kirill Tsukanov verfasserin aut Brian Walsh verfasserin aut Melissa Konopko verfasserin aut Heidi L. Rehm verfasserin aut Andrew D. Yates verfasserin aut Robert R. Freimuth verfasserin aut Reece K. Hart verfasserin aut In Cell Genomics Elsevier, 2022 1(2021), 2, Seite 100027- (DE-627)178991650X 2666979X nnns volume:1 year:2021 number:2 pages:100027- https://doi.org/10.1016/j.xgen.2021.100027 kostenfrei https://doaj.org/article/3859bdfa7d3c4f77bb01c6a9ee4f69c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666979X21000343 kostenfrei https://doaj.org/toc/2666-979X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2021 2 100027- |
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10.1016/j.xgen.2021.100027 doi (DE-627)DOAJ029958024 (DE-599)DOAJ3859bdfa7d3c4f77bb01c6a9ee4f69c7 DE-627 ger DE-627 rakwb eng QH426-470 RC31-1245 Alex H. Wagner verfasserin aut The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). variation genomics GA4GH standard VOCA computed identifiers Genetics Internal medicine Lawrence Babb verfasserin aut Gil Alterovitz verfasserin aut Michael Baudis verfasserin aut Matthew Brush verfasserin aut Daniel L. Cameron verfasserin aut Melissa Cline verfasserin aut Malachi Griffith verfasserin aut Obi L. Griffith verfasserin aut Sarah E. Hunt verfasserin aut David Kreda verfasserin aut Jennifer M. Lee verfasserin aut Stephanie Li verfasserin aut Javier Lopez verfasserin aut Eric Moyer verfasserin aut Tristan Nelson verfasserin aut Ronak Y. Patel verfasserin aut Kevin Riehle verfasserin aut Peter N. Robinson verfasserin aut Shawn Rynearson verfasserin aut Helen Schuilenburg verfasserin aut Kirill Tsukanov verfasserin aut Brian Walsh verfasserin aut Melissa Konopko verfasserin aut Heidi L. Rehm verfasserin aut Andrew D. Yates verfasserin aut Robert R. Freimuth verfasserin aut Reece K. Hart verfasserin aut In Cell Genomics Elsevier, 2022 1(2021), 2, Seite 100027- (DE-627)178991650X 2666979X nnns volume:1 year:2021 number:2 pages:100027- https://doi.org/10.1016/j.xgen.2021.100027 kostenfrei https://doaj.org/article/3859bdfa7d3c4f77bb01c6a9ee4f69c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666979X21000343 kostenfrei https://doaj.org/toc/2666-979X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2021 2 100027- |
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10.1016/j.xgen.2021.100027 doi (DE-627)DOAJ029958024 (DE-599)DOAJ3859bdfa7d3c4f77bb01c6a9ee4f69c7 DE-627 ger DE-627 rakwb eng QH426-470 RC31-1245 Alex H. Wagner verfasserin aut The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). variation genomics GA4GH standard VOCA computed identifiers Genetics Internal medicine Lawrence Babb verfasserin aut Gil Alterovitz verfasserin aut Michael Baudis verfasserin aut Matthew Brush verfasserin aut Daniel L. Cameron verfasserin aut Melissa Cline verfasserin aut Malachi Griffith verfasserin aut Obi L. Griffith verfasserin aut Sarah E. Hunt verfasserin aut David Kreda verfasserin aut Jennifer M. Lee verfasserin aut Stephanie Li verfasserin aut Javier Lopez verfasserin aut Eric Moyer verfasserin aut Tristan Nelson verfasserin aut Ronak Y. Patel verfasserin aut Kevin Riehle verfasserin aut Peter N. Robinson verfasserin aut Shawn Rynearson verfasserin aut Helen Schuilenburg verfasserin aut Kirill Tsukanov verfasserin aut Brian Walsh verfasserin aut Melissa Konopko verfasserin aut Heidi L. Rehm verfasserin aut Andrew D. Yates verfasserin aut Robert R. Freimuth verfasserin aut Reece K. Hart verfasserin aut In Cell Genomics Elsevier, 2022 1(2021), 2, Seite 100027- (DE-627)178991650X 2666979X nnns volume:1 year:2021 number:2 pages:100027- https://doi.org/10.1016/j.xgen.2021.100027 kostenfrei https://doaj.org/article/3859bdfa7d3c4f77bb01c6a9ee4f69c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666979X21000343 kostenfrei https://doaj.org/toc/2666-979X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2021 2 100027- |
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10.1016/j.xgen.2021.100027 doi (DE-627)DOAJ029958024 (DE-599)DOAJ3859bdfa7d3c4f77bb01c6a9ee4f69c7 DE-627 ger DE-627 rakwb eng QH426-470 RC31-1245 Alex H. Wagner verfasserin aut The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). variation genomics GA4GH standard VOCA computed identifiers Genetics Internal medicine Lawrence Babb verfasserin aut Gil Alterovitz verfasserin aut Michael Baudis verfasserin aut Matthew Brush verfasserin aut Daniel L. Cameron verfasserin aut Melissa Cline verfasserin aut Malachi Griffith verfasserin aut Obi L. Griffith verfasserin aut Sarah E. Hunt verfasserin aut David Kreda verfasserin aut Jennifer M. Lee verfasserin aut Stephanie Li verfasserin aut Javier Lopez verfasserin aut Eric Moyer verfasserin aut Tristan Nelson verfasserin aut Ronak Y. Patel verfasserin aut Kevin Riehle verfasserin aut Peter N. Robinson verfasserin aut Shawn Rynearson verfasserin aut Helen Schuilenburg verfasserin aut Kirill Tsukanov verfasserin aut Brian Walsh verfasserin aut Melissa Konopko verfasserin aut Heidi L. Rehm verfasserin aut Andrew D. Yates verfasserin aut Robert R. Freimuth verfasserin aut Reece K. Hart verfasserin aut In Cell Genomics Elsevier, 2022 1(2021), 2, Seite 100027- (DE-627)178991650X 2666979X nnns volume:1 year:2021 number:2 pages:100027- https://doi.org/10.1016/j.xgen.2021.100027 kostenfrei https://doaj.org/article/3859bdfa7d3c4f77bb01c6a9ee4f69c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666979X21000343 kostenfrei https://doaj.org/toc/2666-979X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2021 2 100027- |
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10.1016/j.xgen.2021.100027 doi (DE-627)DOAJ029958024 (DE-599)DOAJ3859bdfa7d3c4f77bb01c6a9ee4f69c7 DE-627 ger DE-627 rakwb eng QH426-470 RC31-1245 Alex H. Wagner verfasserin aut The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). variation genomics GA4GH standard VOCA computed identifiers Genetics Internal medicine Lawrence Babb verfasserin aut Gil Alterovitz verfasserin aut Michael Baudis verfasserin aut Matthew Brush verfasserin aut Daniel L. Cameron verfasserin aut Melissa Cline verfasserin aut Malachi Griffith verfasserin aut Obi L. Griffith verfasserin aut Sarah E. Hunt verfasserin aut David Kreda verfasserin aut Jennifer M. Lee verfasserin aut Stephanie Li verfasserin aut Javier Lopez verfasserin aut Eric Moyer verfasserin aut Tristan Nelson verfasserin aut Ronak Y. Patel verfasserin aut Kevin Riehle verfasserin aut Peter N. Robinson verfasserin aut Shawn Rynearson verfasserin aut Helen Schuilenburg verfasserin aut Kirill Tsukanov verfasserin aut Brian Walsh verfasserin aut Melissa Konopko verfasserin aut Heidi L. Rehm verfasserin aut Andrew D. Yates verfasserin aut Robert R. Freimuth verfasserin aut Reece K. Hart verfasserin aut In Cell Genomics Elsevier, 2022 1(2021), 2, Seite 100027- (DE-627)178991650X 2666979X nnns volume:1 year:2021 number:2 pages:100027- https://doi.org/10.1016/j.xgen.2021.100027 kostenfrei https://doaj.org/article/3859bdfa7d3c4f77bb01c6a9ee4f69c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2666979X21000343 kostenfrei https://doaj.org/toc/2666-979X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 1 2021 2 100027- |
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Alex H. Wagner @@aut@@ Lawrence Babb @@aut@@ Gil Alterovitz @@aut@@ Michael Baudis @@aut@@ Matthew Brush @@aut@@ Daniel L. Cameron @@aut@@ Melissa Cline @@aut@@ Malachi Griffith @@aut@@ Obi L. Griffith @@aut@@ Sarah E. Hunt @@aut@@ David Kreda @@aut@@ Jennifer M. Lee @@aut@@ Stephanie Li @@aut@@ Javier Lopez @@aut@@ Eric Moyer @@aut@@ Tristan Nelson @@aut@@ Ronak Y. Patel @@aut@@ Kevin Riehle @@aut@@ Peter N. Robinson @@aut@@ Shawn Rynearson @@aut@@ Helen Schuilenburg @@aut@@ Kirill Tsukanov @@aut@@ Brian Walsh @@aut@@ Melissa Konopko @@aut@@ Heidi L. Rehm @@aut@@ Andrew D. Yates @@aut@@ Robert R. Freimuth @@aut@@ Reece K. Hart @@aut@@ |
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The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification |
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Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). |
| abstractGer |
Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). |
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Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH). |
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