Author

Kaylene J. Ready

Baylor Scott & White Health

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:variant calling· 2 Assay:whole-exome sequencing· 2 Assay:electronic health records· 1 Approach:experimental assay· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Hyunseok Peter KangiD· 2 shared Kevin R. Haas· 2 shared Alex D. Robertson· 1 shared Andi Hila· 1 shared Ashley Daley· 1 shared Callan D. Russell· 1 shared Cary M. Armstrong· 1 shared Clement S. Chu· 1 shared

Activity by Year

2017-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersGenomics

Hyunseok Peter KangORCID

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3 papers

Recent·Most cited

Validation of a guidelines-based digital tool to assess the need for germline cancer genetic testing

Callan D. Russell, Ashley Daley, Durand R. Van Arnem, Andi Hila, Kiley J. Johnson, Jill N. Davies, Hanah S. Cytron, Kaylene J. Ready, Cary M. Armstrong, Mark E. Sylvester, Colleen A. Caleshu

The paper validates a digital tool for assessing germline cancer genetic testing eligibility based on patient and family history, showing high agreement with genetic counselors.

Hereditary Cancer in Clinical Practice · Nov 8, 2024Peer-reviewedGenetic & Genomic Medicine

Software-assisted manual review of clinical NGS data:an alternative to routine Sanger sequencing confirmationwith equivalent results in >15,000 hereditary cancer screens

Dale Muzzey, Shera F. Kash, Jillian I. Johnson, Laura M. Melroy, Piotr Kaleta, Kelly A. Pierce, Kaylene J. Ready, Hyunseok Peter Kang, Kevin R. Haas

The paper demonstrates that software-assisted manual review of NGS data achieves equivalent accuracy to Sanger sequencing in confirming variant calls for hereditary cancer screening.

bioRxiv · Sep 23, 2018 · PreprintGenomics

Development and validation of a 36-gene sequencing assay for hereditary cancer risk assessment

Valentina S. Vysotskaia, Gregory J. Hogan, Genevieve M. Gould, Xin Wang, Alex D. Robertson, Kevin R. Haas, Mark R. Theilmann, Lindsay Spurka, Peter V. Grauman, Henry H. Lai, Diana Jeon, Genevieve Haliburton, Matt Leggett, Clement S. Chu, Kevin Iori, , Imran S. Haque

The paper develops and validates a 36-gene sequencing assay for hereditary cancer risk assessment, showing 100% sensitivity and high specificity across mutation types.

PeerJ · Feb 23, 2017Peer-reviewedGenetics