Author

George A. R. Wiggins

University of OtagoORCID 0000-0003-2471-2267Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:variant effect prediction· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1

Frequent Co-Authors

Amanda B. SpurdleiD· 3 shared Logan C. WalkeriD· 3 shared Michael T. ParsonsiD· 2 shared Miguel de la HoyaiD· 2 shared Rachid KaramiD· 2 shared Tina F. PesaraniD· 2 shared Alexander Y. Tchourbanov· 1 shared Alexandra MartinsiD· 1 shared

Activity by Year

2017-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersGenetic & Genomic Medicine

Amanda B. SpurdleORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Genetic & Genomic MedicineThe American Journal of Human GeneticsPeer-reviewedAug 13, 2024

Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel

Michael T. Parsons, Miguel de la Hoya, Marcy E. Richardson…·Amanda B. Spurdle

The paper refines ACMG/AMP variant classification criteria for BRCA1 and BRCA2 by calibrating evidence strength and improving classification consistency through expert panel review.

104 citationstop 1%

humanDNA methylation

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Genetic & Genomic MedicinemedRxivPreprintFeb 24, 2023

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP

Logan C. Walker, Miguel de la Hoya, George A. R. Wiggins…·Amanda B. Spurdle

The paper refines ACMG/AMP splicing variant classification codes using empirical evidence to improve consistency in variant pathogenicity classification.

20 citations

statistical modelvariant effect prediction

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GenomicsBreast Cancer ResearchPeer-reviewedNov 28, 2017

Nanopore sequencing of full-length BRCA1 mRNA transcripts reveals co-occurrence of known exon skipping events

Lucy C. de Jong, Simone L. Cree, Vanessa Lattimore…·Logan C. Walker

The paper uses nanopore sequencing to analyze full-length BRCA1 mRNA transcripts, identifying novel isoforms and co-occurring exon skipping events.

53 citations

humanlong-read sequencing

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