Author

Janet Cady

Virginia Energy

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 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:polygenic risk· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Ellen McRae GreytakiD· 2 shared Steven L. Armentrout· 2 shared Carlos CruchagaiD· 1 shared Charla K. MarshalliD· 1 shared Erin M. GordeniD· 1 shared James O’Connor· 1 shared Kimberly Sturk‐AndreaggiiD· 1 shared Sarah E. CarlsoniD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Ellen McRae GreytakORCID

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2 papers

Recent·Most cited

Epistatic Features and Machine Learning Improve Alzheimer's Risk Prediction Over Polygenic Risk Scores

Stephen Hermes, Janet Cady, Steven L. Armentrout, James O’Connor, Sarah E. Carlson, Carlos Cruchaga, Thomas S. Wingo, Ellen McRae Greytak, The Alzheimer’s Disease Neuroimaging Initiative

This study develops a paragenic risk score that improves Alzheimer's disease risk prediction by incorporating epistatic interactions and machine learning, outperforming traditional polygenic risk scores.

medRxiv · Feb 10, 2023 · PreprintGenetic & Genomic Medicine

Extended kinship analysis of historical remains using SNP capture

Erin M. Gorden, Ellen McRae Greytak, Kimberly Sturk‐Andreaggi, Janet Cady, Timothy P. McMahon, Steven L. Armentrout, Charla K. Marshall

This study uses SNP capture panels to analyze degraded historical DNA samples and estimate kinship up to 4th degree relatives with varying success based on panel size.

Forensic Science International Genetics · Nov 23, 2021Peer-reviewedGenomics