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Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey

Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey
Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey

BACKGROUND: National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS: In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS: Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION: The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.

Clinical Laboratory Techniques, Genetic Testing, Genetics, Genomics, Molecular Diagnostic Techniques
0022-2593
305-312
Allen, Sophie
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Loong, Lucy
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Garrett, Alice
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Torr, Bethany
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Durkie, Miranda
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Drummond, James
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Callaway, Alison
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Robinson, Rachel
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Burghel, George J.
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Hanson, Helen
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Field, Joanne
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McDevitt, Trudi
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McVeigh, Terri P.
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Bedenham, Tina
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Bowles, Christopher
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Bradshaw, Kirsty
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Brooks, Claire
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Butler, Samantha
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Del Rey Jimenez, Juan Carlos
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Hawkes, Lorraine
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Stinton, Victoria
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MacMahon, Suzanne
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Owens, Martina
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Palmer-Smith, Sheila
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Smith, Kenneth
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Tellez, James
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Valganon-Petrizan, Mikel
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Waskiewicz, Erik
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Yau, Michael
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Eccles, Diana M.
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Tischkowitz, Marc
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Goel, Shilpi
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McRonald, Fiona
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Antoniou, Antonis C.
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Morris, Eva
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Hardy, Steven
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Turnbull, Clare
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Allen, Sophie
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Loong, Lucy
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Garrett, Alice
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Torr, Bethany
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Durkie, Miranda
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Hanson, Helen
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Field, Joanne
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McDevitt, Trudi
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Bedenham, Tina
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Bowles, Christopher
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Bradshaw, Kirsty
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Butler, Samantha
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Del Rey Jimenez, Juan Carlos
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Hawkes, Lorraine
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Stinton, Victoria
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MacMahon, Suzanne
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Owens, Martina
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Palmer-Smith, Sheila
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Smith, Kenneth
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Tellez, James
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Valganon-Petrizan, Mikel
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Waskiewicz, Erik
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Yau, Michael
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Eccles, Diana M.
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Tischkowitz, Marc
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Goel, Shilpi
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McRonald, Fiona
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Antoniou, Antonis C.
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Morris, Eva
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Hardy, Steven
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Turnbull, Clare
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Allen, Sophie, Loong, Lucy, Garrett, Alice, Torr, Bethany, Durkie, Miranda, Drummond, James, Callaway, Alison, Robinson, Rachel, Burghel, George J., Hanson, Helen, Field, Joanne, McDevitt, Trudi, McVeigh, Terri P., Bedenham, Tina, Bowles, Christopher, Bradshaw, Kirsty, Brooks, Claire, Butler, Samantha, Del Rey Jimenez, Juan Carlos, Hawkes, Lorraine, Stinton, Victoria, MacMahon, Suzanne, Owens, Martina, Palmer-Smith, Sheila, Smith, Kenneth, Tellez, James, Valganon-Petrizan, Mikel, Waskiewicz, Erik, Yau, Michael, Eccles, Diana M., Tischkowitz, Marc, Goel, Shilpi, McRonald, Fiona, Antoniou, Antonis C., Morris, Eva, Hardy, Steven and Turnbull, Clare (2024) Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey. Journal of Medical Genetics, 61 (4), 305-312. (doi:10.1136/jmg-2023-109645).

Record type: Article

Abstract

BACKGROUND: National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS: In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS: Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION: The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.

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Accepted/In Press date: 28 October 2023
e-pub ahead of print date: 22 December 2023
Published date: 21 March 2024
Keywords: Clinical Laboratory Techniques, Genetic Testing, Genetics, Genomics, Molecular Diagnostic Techniques

Identifiers

Local EPrints ID: 489031
URI: http://eprints.soton.ac.uk/id/eprint/489031
ISSN: 0022-2593
PURE UUID: 48c6f7e5-19da-4b88-864f-da3556813a8f
ORCID for Diana M. Eccles: ORCID iD orcid.org/0000-0002-9935-3169

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Date deposited: 11 Apr 2024 16:45
Last modified: 13 Apr 2024 01:33

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Contributors

Author: Sophie Allen
Author: Lucy Loong
Author: Alice Garrett
Author: Bethany Torr
Author: Miranda Durkie
Author: James Drummond
Author: Alison Callaway
Author: Rachel Robinson
Author: George J. Burghel
Author: Helen Hanson
Author: Joanne Field
Author: Trudi McDevitt
Author: Terri P. McVeigh
Author: Tina Bedenham
Author: Christopher Bowles
Author: Kirsty Bradshaw
Author: Claire Brooks
Author: Samantha Butler
Author: Juan Carlos Del Rey Jimenez
Author: Lorraine Hawkes
Author: Victoria Stinton
Author: Suzanne MacMahon
Author: Martina Owens
Author: Sheila Palmer-Smith
Author: Kenneth Smith
Author: James Tellez
Author: Mikel Valganon-Petrizan
Author: Erik Waskiewicz
Author: Michael Yau
Author: Diana M. Eccles ORCID iD
Author: Marc Tischkowitz
Author: Shilpi Goel
Author: Fiona McRonald
Author: Antonis C. Antoniou
Author: Eva Morris
Author: Steven Hardy
Author: Clare Turnbull

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